What's to Come is Still Unsure
|
|
- Doris Marjorie Byrd
- 5 years ago
- Views:
Transcription
1 What's to Come is Still Unsure Synthesizing Controllers Resilient to Delayed Interaction Mingshuai Chen, Martin Fränzle, Yangjia Li 3,, Peter N Mosaad, Naijun Zhan chenms@iosaccn lcsiosaccn/~chenms/ State Key Lab of Computer Science, Institute of Software, Chinese Academy of Sciences, China Dpt of Computing Science, Carl v Ossietzky Universität Oldenburg, Germany 3 University of Tartu, Estonia Los Angeles, October 08 William Shakespeare, Twelfth Night/What You Will, Act, Scene 3 Mingshuai Chen Institute of Software, CAS Synthesizing Controllers Resilient to Delay Los Angeles, ATVA 08 / 5
2 Staying Safe When Observation & Actuation Suffer from Serious Delays You could move slowly (Well, can you?) You could trust autonomy Or you have to anticipate and issue actions early ESA Mingshuai Chen Institute of Software, CAS Synthesizing Controllers Resilient to Delay Los Angeles, ATVA 08 / 5
3 A Pearl of Wisdom izquotes Mingshuai Chen Institute of Software, CAS Synthesizing Controllers Resilient to Delay Los Angeles, ATVA 08 3 / 5
4 A Pearl of Wisdom Only relevant to ordinary people's life? Or to scientists, in particular comp sci and control folks, too? izquotes Mingshuai Chen Institute of Software, CAS Synthesizing Controllers Resilient to Delay Los Angeles, ATVA 08 3 / 5
5 A Pearl of Wisdom Only relevant to ordinary people's life? Or to scientists, in particular comp sci and control folks, too? izquotes Remember that Canning briefly controlled Great Britain! Mingshuai Chen Institute of Software, CAS Synthesizing Controllers Resilient to Delay Los Angeles, ATVA 08 3 / 5
6 Outline Safety Games under Delay 3 Synthesizing Controllers Resilient to Delayed Interaction 4 5 Mingshuai Chen Institute of Software, CAS Synthesizing Controllers Resilient to Delay Los Angeles, ATVA 08 4 / 5
7 Outline Safety Games under Delay Delayed observation and actuation Reducibility to standard safety games 3 Synthesizing Controllers Resilient to Delayed Interaction Incremental handling of order-preserving delays Out-of-order delivery 4 Performance 5 Summary Mingshuai Chen Institute of Software, CAS Synthesizing Controllers Resilient to Delay Los Angeles, ATVA 08 5 / 5
8 Hybrid Systems disturbances ("noise") Plant environmental influence observable state control Analog switch Continuous controllers Plant Control selection setpoints active control law D/A setpoints Discrete supervisor A/D part of observable state task selection Mingshuai Chen Institute of Software, CAS Synthesizing Controllers Resilient to Delay Los Angeles, ATVA 08 6 / 5
9 Hybrid Systems disturbances ("noise") Plant environmental influence observable state control selection Analog switch setpoints active control law Continuous controllers D/A setpoints Discrete supervisor A/D part of observable state task selection Plant Control Loads of continuous computations interleaved with discrete decisions Mingshuai Chen Institute of Software, CAS Synthesizing Controllers Resilient to Delay Los Angeles, ATVA 08 6 / 5
10 Hybrid Systems disturbances ("noise") Plant environmental influence observable state Crucial question : control Analog switch selection setpoints active control law Continuous controllers D/A setpoints Discrete supervisor How do the controller and the plant interact? Traditional answer : A/D part of observable state task selection Plant Control Loads of continuous computations interleaved with discrete decisions Coupling assumed to be (or at least modeled as) delay-free Mode dynamics is covered by the conjunction of the individual ODEs Switching btw modes is an immediate reaction to environmental conditions Mingshuai Chen Institute of Software, CAS Synthesizing Controllers Resilient to Delay Los Angeles, ATVA 08 6 / 5
11 Instantaneous Coupling 4 a i o i o i3 o3 timer h brake a_brake a s x o v 00 len s x o 3 v xh xr 4 xr_l 400 s 3 a_free v_init xr_init Following the tradition, above (rather typical) Simulink model assumes delay-free coupling between all components, instantaneous feed-through within all functional blocks ETCS-3 Central questions : Is this realistic? If not, does it have observable effect on control performance? 3 May that effect be detrimental or even harmful? Mingshuai Chen Institute of Software, CAS Synthesizing Controllers Resilient to Delay Los Angeles, ATVA 08 7 / 5
12 Q : Is Instantaneous Coupling Realistic? Mingshuai Chen Institute of Software, CAS Synthesizing Controllers Resilient to Delay Los Angeles, ATVA 08 8 / 5
13 Q : Is Instantaneous Coupling Realistic? We are no better : As soon as computer scientists enter the scene, serious delays are ahead Mingshuai Chen Institute of Software, CAS Synthesizing Controllers Resilient to Delay Los Angeles, ATVA 08 8 / 5
14 Q : Is Instantaneous Coupling Realistic? Digital control needs A/D and D/A conversion, which induces latency in signal forwarding Digital signal processing, especially in complex sensors like CV, needs processing time, adding signal delays Networked control introduces communication latency into the feedback control loop Harvesting, fusing, and forwarding data through sensor networks enlarge the latter by orders of magnitude Mingshuai Chen Institute of Software, CAS Synthesizing Controllers Resilient to Delay Los Angeles, ATVA 08 9 / 5
15 Q : Is Instantaneous Coupling Realistic? -- No Digital control needs A/D and D/A conversion, which induces latency in signal forwarding Digital signal processing, especially in complex sensors like CV, needs processing time, adding signal delays Networked control introduces communication latency into the feedback control loop Harvesting, fusing, and forwarding data through sensor networks enlarge the latter by orders of magnitude Mingshuai Chen Institute of Software, CAS Synthesizing Controllers Resilient to Delay Los Angeles, ATVA 08 9 / 5
16 Qa : Resultant Forms of Delay Delayed reaction : Reaction to a stimulus is not immediate Easy to model in timed automata, hybrid automata, : a / x:=0 x<4 x > 3 / b Thus amenable to the pertinent analysis tools Not of interest today Mingshuai Chen Institute of Software, CAS Synthesizing Controllers Resilient to Delay Los Angeles, ATVA 08 0 / 5
17 Qa : Resultant Forms of Delay Delayed reaction : Reaction to a stimulus is not immediate Easy to model in timed automata, hybrid automata, : a / x:=0 x<4 x > 3 / b Thus amenable to the pertinent analysis tools Not of interest today Network delay : Information of different age coexists and is queuing in the network when piped towards target End-to-end latency may exceed sampling intervals etc by orders of magnitude Not (continuous-time pipelined delay) or not efficiently (discrete-time pipelined delay) expressible in our std models Our theme today : discrete-time pipelined delay [M Chen, M Fränzle et al ATVA'8], [M Zimmermann LICS'8, GandALF'7], [F Klein & M Zimmermann ICALP'5, CSL'5] Mingshuai Chen Institute of Software, CAS Synthesizing Controllers Resilient to Delay Los Angeles, ATVA 08 0 / 5
18 Q : Do Delays Have Observable Effect? y x Figure : A robot escape game in a 4 4 room, with Σ r = {RU, UR, LU, UL, RD, DR, LD, DL, ϵ}, Σ k = {R, L, U, D} Mingshuai Chen Institute of Software, CAS Synthesizing Controllers Resilient to Delay Los Angeles, ATVA 08 / 5
19 Q : Do Delays Have Observable Effect? y x Figure : A robot escape game in a 4 4 room, with Σ r = {RU, UR, LU, UL, RD, DR, LD, DL, ϵ}, Σ k = {R, L, U, D} Mingshuai Chen Institute of Software, CAS Synthesizing Controllers Resilient to Delay Los Angeles, ATVA 08 / 5
20 Q : Do Delays Have Observable Effect? y x Figure : A robot escape game in a 4 4 room, with Σ r = {RU, UR, LU, UL, RD, DR, LD, DL, ϵ}, Σ k = {R, L, U, D} Mingshuai Chen Institute of Software, CAS Synthesizing Controllers Resilient to Delay Los Angeles, ATVA 08 / 5
21 Q : Do Delays Have Observable Effect? y 3 No delay : x Figure : A robot escape game in a 4 4 room, with Σ r = {RU, UR, LU, UL, RD, DR, LD, DL, ϵ}, Σ k = {R, L, U, D} Mingshuai Chen Institute of Software, CAS Synthesizing Controllers Resilient to Delay Los Angeles, ATVA 08 / 5
22 Q : Do Delays Have Observable Effect? y 3 No delay : Robot always wins by circling around the obstacle at (,) x Figure : A robot escape game in a 4 4 room, with Σ r = {RU, UR, LU, UL, RD, DR, LD, DL, ϵ}, Σ k = {R, L, U, D} Mingshuai Chen Institute of Software, CAS Synthesizing Controllers Resilient to Delay Los Angeles, ATVA 08 / 5
23 Q : Do Delays Have Observable Effect? y 3 No delay : Robot always wins by circling around the obstacle at (,) step delay : x Figure : A robot escape game in a 4 4 room, with Σ r = {RU, UR, LU, UL, RD, DR, LD, DL, ϵ}, Σ k = {R, L, U, D} Mingshuai Chen Institute of Software, CAS Synthesizing Controllers Resilient to Delay Los Angeles, ATVA 08 / 5
24 Q : Do Delays Have Observable Effect? y 3 No delay : Robot always wins by circling around the obstacle at (,) step delay : Robot wins by -step pre-decision x Figure : A robot escape game in a 4 4 room, with Σ r = {RU, UR, LU, UL, RD, DR, LD, DL, ϵ}, Σ k = {R, L, U, D} Mingshuai Chen Institute of Software, CAS Synthesizing Controllers Resilient to Delay Los Angeles, ATVA 08 / 5
25 Q : Do Delays Have Observable Effect? y 3 No delay : Robot always wins by circling around the obstacle at (,) step delay : Robot wins by -step pre-decision steps delay : x Figure : A robot escape game in a 4 4 room, with Σ r = {RU, UR, LU, UL, RD, DR, LD, DL, ϵ}, Σ k = {R, L, U, D} Mingshuai Chen Institute of Software, CAS Synthesizing Controllers Resilient to Delay Los Angeles, ATVA 08 / 5
26 Q : Do Delays Have Observable Effect? y 3 No delay : Robot always wins by circling around the obstacle at (,) step delay : Robot wins by -step pre-decision x steps delay : Robot still wins, yet extra memory is needed Figure : A robot escape game in a 4 4 room, with Σ r = {RU, UR, LU, UL, RD, DR, LD, DL, ϵ}, Σ k = {R, L, U, D} Mingshuai Chen Institute of Software, CAS Synthesizing Controllers Resilient to Delay Los Angeles, ATVA 08 / 5
27 Q : Do Delays Have Observable Effect? y 3 No delay : Robot always wins by circling around the obstacle at (,) step delay : Robot wins by -step pre-decision 0 0 Figure : A robot escape game in a 4 4 room, with Σ r = {RU, UR, LU, UL, RD, DR, LD, DL, ϵ}, Σ k = {R, L, U, D} 3 x steps delay : Robot still wins, yet extra memory is needed 3 steps delay : Mingshuai Chen Institute of Software, CAS Synthesizing Controllers Resilient to Delay Los Angeles, ATVA 08 / 5
28 Q : Do Delays Have Observable Effect? y 3 No delay : Robot always wins by circling around the obstacle at (,) step delay : Robot wins by -step pre-decision 0 0 Figure : A robot escape game in a 4 4 room, with Σ r = {RU, UR, LU, UL, RD, DR, LD, DL, ϵ}, Σ k = {R, L, U, D} 3 x steps delay : Robot still wins, yet extra memory is needed 3 steps delay : Robot is unwinnable (uncontrollable) anymore Mingshuai Chen Institute of Software, CAS Synthesizing Controllers Resilient to Delay Los Angeles, ATVA 08 / 5
29 Q : Do Delays Have Observable Effect? -- Yes, they have y 3 No delay : Robot always wins by circling around the obstacle at (,) step delay : Robot wins by -step pre-decision 0 0 Figure : A robot escape game in a 4 4 room, with Σ r = {RU, UR, LU, UL, RD, DR, LD, DL, ϵ}, Σ k = {R, L, U, D} 3 x steps delay : Robot still wins, yet extra memory is needed 3 steps delay : Robot is unwinnable (uncontrollable) anymore Mingshuai Chen Institute of Software, CAS Synthesizing Controllers Resilient to Delay Los Angeles, ATVA 08 / 5
30 Q3 : May the Effects be Harmful? -- Yes, delays may well annihilate control performance y 3 No delay : Robot always wins by circling around the obstacle at (,) step delay : Robot wins by -step pre-decision 0 0 Figure : A robot escape game in a 4 4 room, with Σ r = {RU, UR, LU, UL, RD, DR, LD, DL, ϵ}, Σ k = {R, L, U, D} 3 x steps delay : Robot still wins, yet extra memory is needed 3 steps delay : Robot is unwinnable (uncontrollable) anymore Mingshuai Chen Institute of Software, CAS Synthesizing Controllers Resilient to Delay Los Angeles, ATVA 08 / 5
31 Outline Safety Games under Delay Delayed observation and actuation Reducibility to standard safety games 3 Synthesizing Controllers Resilient to Delayed Interaction Incremental handling of order-preserving delays Out-of-order delivery 4 Performance 5 Summary Mingshuai Chen Institute of Software, CAS Synthesizing Controllers Resilient to Delay Los Angeles, ATVA 08 3 / 5
32 Delayed Observation & Actuation A Trivial Safety Game A Trivial Safety Game u a 3 e a b u a a 5 a u b a u a e e 3 v v Goal: Avoid a 5 by appropriate Goal : Avoid actions a 5 by of appropriate player e actions of player e b u a 4 PKU MAVeLoS Workshop, Beijing, Oct 8, 07 Martin Fränzle: Indecision and Delay 3 / 39 Mingshuai Chen Institute of Software, CAS Synthesizing Controllers Resilient to Delay Los Angeles, ATVA 08 4 / 5
33 Delayed Observation & Actuation A Trivial Safety Game A Trivial Safety Game u a 3 e a b u a a 5 a u b a u a e e 3 b v v Goal: Avoid a 5 by appropriate Goal : Avoid actions a 5 by of appropriate player e actions of player e Strategy : May always play "a" except in e 3 : e, e a e 3 b u a 4 PKU MAVeLoS Workshop, Beijing, Oct 8, 07 Martin Fränzle: Indecision and Delay 3 / 39 Mingshuai Chen Institute of Software, CAS Synthesizing Controllers Resilient to Delay Los Angeles, ATVA 08 4 / 5
34 Delayed Observation & Actuation Playing Safety Game Subject to Discrete Delay Playing Subject to Discrete Delay Ego player Shift registers Game state Adversary Observation : It doesn't make an observable difference for the joint dynamics Observation: whetheritdelay doesn t occurs make in perception, an observable actuation, difference or both for the joint dynamics whether delay occurs in perception, actuation, or both Mingshuai Chen Institute of Software, CAS Synthesizing Controllers Resilient to Delay Los Angeles, ATVA 08 5 / 5
35 Delayed Observation & Actuation Playing Safety Game Subject to Discrete Delay Playing Subject to Discrete Delay Ego player Shift registers Game state Adversary Observation : It doesn't make an observable difference for the joint dynamics Observation: whetheritdelay doesn t occurs make in perception, an observable actuation, difference or both for the joint dynamics Consequence whether : There delayisoccurs an obvious in perception, reduction to actuation, a safety game or both of perfect information In fact, two different ones : To mimic opacity of the shift registers, delay has to be moved to actuation/sensing for ego/adversary, resp The two thus play different games! Mingshuai Chen Institute of Software, CAS Synthesizing Controllers Resilient to Delay Los Angeles, ATVA 08 5 / 5
36 Reduction Reduction to Delay-Free Games from Ego-Player Perspective The Reduction from Ego-Player Perspective Σ / Ego inp Adv inp Ego input Shift register Σ Game graph Σ Safe / unsafe PKU MAVeLoS Workshop, Beijing, Oct 8, 07 Martin Fränzle: Indecision and Delay 5 / 39 Mingshuai Chen Institute of Software, CAS Synthesizing Controllers Resilient to Delay Los Angeles, ATVA 08 6 / 5
37 Reduction Reduction to Delay-Free Games from Ego-Player Perspective The Reduction from Ego-Player Perspective Σ / Ego inp Adv inp Ego input Shift register Σ Game graph Σ Safe / unsafe Safety games w delay can be solved algorithmically Game graph incurs blow-up by factor Alphabet(ego) delay Mingshuai Chen PKU Institute MAVeLoS of Software, Workshop, CAS Beijing, Synthesizing Oct 8, 07 Controllers Martin Resilient Fränzle: to DelayIndecision and Delay Los Angeles, 5 / ATVA / 5
38 Reduction The Simple Safety Game but with Delay A Trivial Safety Game u a 3 No delay : e, e a e 3 b e a b u a a 5 a u b a u a e e 3 v v Goal: step Avoid delay a: 5 Strategy by appropriate? actions a, of a 4 player a e a, a 3 b b u a 4 PKU MAVeLoS Workshop, Beijing, Oct 8, 07 Martin Fränzle: Indecision and Delay 3 / 39 Mingshuai Chen Institute of Software, CAS Synthesizing Controllers Resilient to Delay Los Angeles, ATVA 08 7 / 5
39 Reduction The Simple Safety Game but with Delay A Trivial Safety Game u a 3 No delay : e, e a e 3 b e a b u a a 5 a u u b a u a e e 3 b a 4 v v Goal: step Avoid delay a: 5 Strategy by appropriate? actions a, of a 4 player a e a, a 3 b steps delay : Strategy? a e b e b e 3 a if steps back an "a" was issued, if steps back a "b" was issued Need memory! PKU MAVeLoS Workshop, Beijing, Oct 8, 07 Martin Fränzle: Indecision and Delay 3 / 39 Mingshuai Chen Institute of Software, CAS Synthesizing Controllers Resilient to Delay Los Angeles, ATVA 08 7 / 5
40 Outline Safety Games under Delay Delayed observation and actuation Reducibility to standard safety games 3 Synthesizing Controllers Resilient to Delayed Interaction Incremental handling of order-preserving delays Out-of-order delivery 4 Performance 5 Summary Mingshuai Chen Institute of Software, CAS Synthesizing Controllers Resilient to Delay Los Angeles, ATVA 08 8 / 5
41 Order-Preserving Delays in a Nutshell Observation : A winning strategy for delay k > k can always be utilized for a safe win under delay k Consequence : That a position is winning for delay k is a necessary condition for it being winning under delay k > k Mingshuai Chen Institute of Software, CAS Synthesizing Controllers Resilient to Delay Los Angeles, ATVA 08 9 / 5
42 Order-Preserving Delays in a Nutshell Observation : A winning strategy for delay k > k can always be utilized for a safe win under delay k Consequence : That a position is winning for delay k is a necessary condition for it being winning under delay k > k Idea : Incrementally filter out loss states & incrementally synthesize winning strategy for the remaining : Synthesize winning strategy for underlying delay-free safety game For each winning state, lift strategy from delay k to k + 3 Remove states where this does not succeed 4 Repeat from until either delay-resilience suffices (winning) or initial state turns lossy (losing) M Chen, M Fränzle, Y Li, PN Mosaad, N Zhan : What's to come is still unsure : Synthesizing controllers resilient to delayed interaction To appear in Proc of ATVA 08 Mingshuai Chen Institute of Software, CAS Synthesizing Controllers Resilient to Delay Los Angeles, ATVA 08 9 / 5
43 Order-Preserving Delays of Delay-Tolerant Strategies Generate a maximally permissive strategy for delay k = 0 Mingshuai Chen Institute of Software, CAS Synthesizing Controllers Resilient to Delay Los Angeles, ATVA 08 0 / 5
44 Order-Preserving Delays of Delay-Tolerant Strategies Generate a maximally permissive strategy for delay k = 0 Advance to delay k + : If k odd : For each (ego-)winning adversarial state define strategy as a 5 u v e e 4 after playing σ, σ (k )/, play {a, c, e} u a5 v after playing σ, σ (k )/, play {b, c, e, f} 3 3 and eliminate any dead ends by bwd traversal e after playing σ, σ (k )/, play {a, c, e} {b, c, e, f} = {c, e} e 4 Mingshuai Chen Institute of Software, CAS Synthesizing Controllers Resilient to Delay Los Angeles, ATVA 08 0 / 5
45 Order-Preserving Delays of Delay-Tolerant Strategies Generate a maximally permissive strategy for delay k = 0 Advance to delay k + : If k odd : For each (ego-)winning adversarial state define strategy as a 5 u v e e 4 after playing σ, σ (k )/, play {a, c, e} u a5 v after playing σ, σ (k )/, play {b, c, e, f} 3 3 and eliminate any dead ends by bwd traversal If k even : For each winning ego state define strategy as e after playing σ, σ (k )/, play {a, c, e} {b, c, e, f} = {c, e} e 4 e 5 a b c a 3 a 4 a 5 play σ, σ k/, play σ, σ k/, e 5 a c a 3 play a, σ,, σ k/ or play c, σ,, σ k/ a 5 Mingshuai Chen Institute of Software, CAS Synthesizing Controllers Resilient to Delay Los Angeles, ATVA 08 0 / 5
46 Order-Preserving Delays of Delay-Tolerant Strategies Generate a maximally permissive strategy for delay k = 0 Advance to delay k + : If k odd : For each (ego-)winning adversarial state define strategy as a 5 u v e e 4 after playing σ, σ (k )/, play {a, c, e} u a5 v after playing σ, σ (k )/, play {b, c, e, f} 3 3 and eliminate any dead ends by bwd traversal If k even : For each winning ego state define strategy as e after playing σ, σ (k )/, play {a, c, e} {b, c, e, f} = {c, e} e 4 e 5 a b c a 3 a 4 a 5 play σ, σ k/, play σ, σ k/, e 5 a c a 3 play a, σ,, σ k/ or play c, σ,, σ k/ a 5 3 Repeat from until either delay-resilience suffices or initial state turns lossy Mingshuai Chen Institute of Software, CAS Synthesizing Controllers Resilient to Delay Los Angeles, ATVA 08 0 / 5
47 Non-Order-Preserving Delays How About Non-Order-Preserving Delays? Observations may arrive out-of-order : Maximum delay 5 Out of order! Sample # t Mingshuai Chen Institute of Software, CAS Synthesizing Controllers Resilient to Delay Los Angeles, ATVA 08 / 5
48 Non-Order-Preserving Delays How About Non-Order-Preserving Delays? Observations may arrive out-of-order : Maximum delay 5 Sample # Out of order! t But this may only reduce effective delay, improving controllability : Maximum delay 5 Factual delay 3 Sample # t ! Effective delay More recent state information available earlier 65 Mingshuai Chen Institute of Software, CAS Synthesizing Controllers Resilient to Delay Los Angeles, ATVA 08 / 5
49 Non-Order-Preserving Delays How About Non-Order-Preserving Delays? Observations may arrive out-of-order : Maximum delay 5 Sample # Out of order! t But this may only reduce effective delay, improving controllability : Maximum delay 5 Factual delay 3 Sample # t ! Effective delay More recent state information available earlier 65 Wrt qualitative controllability, the worst-case of out-of-order delivery is equivalent to order-preserving delay k Stochastically expected controllability even better than for strict delay k Mingshuai Chen Institute of Software, CAS Synthesizing Controllers Resilient to Delay Los Angeles, ATVA 08 / 5
50 Outline Safety Games under Delay Delayed observation and actuation Reducibility to standard safety games 3 Synthesizing Controllers Resilient to Delayed Interaction Incremental handling of order-preserving delays Out-of-order delivery 4 Performance 5 Summary Mingshuai Chen Institute of Software, CAS Synthesizing Controllers Resilient to Delay Los Angeles, ATVA 08 / 5
51 Performance Incremental vs Reduction-Based 4 M Chen et al Benchmark Reduction + Explicit-State Synthesis Incremental Explicit-State Synthesis name S U δmax δ = 0 δ = δ = δ = 3 δ = 4 δmax δ = 0 δ = δ = δ = 3 δ = 4 % Exmptrv Exmptrv 4 4 = = Escp = = Escp = = Escp ?? = Escp ?? = Escp ?? = Escp ?? = Escp ???? = Benchmark Reduction + Yosys + SafetySynth (symbolic) (explicit-state implementation) name δmax δ = 0 δ = δ = δ = 3 δ = 4 δ = 5 δ = 6 δ = 0 δ = δ = δ = 3 δ = 4 δ = 5 δ = 6 % Stub4 4 = Stub4 5 = Stub5 5 = Stub5 6 = Stub6 6 = Stub7 7 = δmax: the maximum delay under which Gδ is controllable δmax = δ : Gδ is verified controllable under delays 0 δ δ while uncontrollable under any delay δ > δ δmax Table δ : : Gδ is Benchmark verified controllable resultsunder in relation delays 0to reduction-based δ δ within hour approaches CPU time(time bound, inyet seconds) unknown under δ > δ due to the limitation of computing capability : already for smaller δ the controller has no winning strategy?: algorithm fails to answer the control/synthesis problem within hour of CPU time %: percentage of savings in state space compared to the reduction-based methods, as obtained on δmax + Table : Benchmark results in relation to reduction-based approaches (time in seconds) Mingshuai Chen Institute of Software, CAS Synthesizing Controllers Resilient to Delay Los Angeles, ATVA 08 3 / 5
52 Performance Incremental vs Reduction-Based 4 M Chen et al Benchmark Reduction + Explicit-State Synthesis Incremental Explicit-State Synthesis name S U δmax δ = 0 δ = δ = δ = 3 δ = 4 δmax δ = 0 δ = δ = δ = 3 δ = 4 % Exmptrv Exmptrv 4 4 = = Escp = = Escp = = Escp ?? = Escp ?? = Escp ?? = Escp ?? = Escp ???? = Benchmark Reduction + Yosys + SafetySynth (symbolic) (explicit-state implementation) name δmax δ = 0 δ = δ = δ = 3 δ = 4 δ = 5 δ = 6 δ = 0 δ = δ = δ = 3 δ = 4 δ = 5 δ = 6 % Stub4 4 = Stub4 5 = Stub5 5 = Stub5 6 = Stub6 6 = Stub7 7 = δmax: the maximum delay under which Gδ is controllable δmax = δ : Gδ is verified controllable under delays 0 δ δ while uncontrollable under any delay δ > δ δmax Table δ : : Gδ is Benchmark verified controllable resultsunder in relation delays 0to reduction-based δ δ within hour approaches CPU time(time bound, inyet seconds) unknown under δ > δ due to the limitation of computing capability : already for smaller δ the controller has no winning strategy?: algorithm fails to answer the control/synthesis problem within hour of CPU time %: percentage of savings in state space compared to the reduction-based methods, as obtained on δmax + Table : Benchmark results in relation to reduction-based approaches (time in seconds) Mingshuai Chen Institute of Software, CAS Synthesizing Controllers Resilient to Delay Los Angeles, ATVA 08 3 / 5
53 Outline Safety Games under Delay Delayed observation and actuation Reducibility to standard safety games 3 Synthesizing Controllers Resilient to Delayed Interaction Incremental handling of order-preserving delays Out-of-order delivery 4 Performance 5 Summary Mingshuai Chen Institute of Software, CAS Synthesizing Controllers Resilient to Delay Los Angeles, ATVA 08 4 / 5
54 Summary Problem : We face increasingly wide-spread use of networked distributed sensing and control, substantial delays thus impacting controllability and control performance, naïve reduction to delay-free settings, yet with an exponential blow-up Status : We present insufficiency of memoryless control strategies for discrete safety games under delay, incremental algorithm for efficient delay-tolerant control synthesis, the practically relevant case of non-order-preserving delays Future Work : We plan to integrate stochastic models of message delays into safety synthesis processes, let synthesis constructively leverage the advantages of (partial) control on out-of-order delivery, extend to hybrid setting combining delayed continuous and delayed discrete reactive behavior Mingshuai Chen Institute of Software, CAS Synthesizing Controllers Resilient to Delay Los Angeles, ATVA 08 5 / 5
Computation Tree Logic (CTL) & Basic Model Checking Algorithms
Computation Tree Logic (CTL) & Basic Model Checking Algorithms Martin Fränzle Carl von Ossietzky Universität Dpt. of Computing Science Res. Grp. Hybride Systeme Oldenburg, Germany 02917: CTL & Model Checking
More informationController Synthesis with UPPAAL-TIGA. Alexandre David Kim G. Larsen, Didier Lime, Franck Cassez, Jean-François Raskin
Controller Synthesis with UPPAAL-TIGA Alexandre David Kim G. Larsen, Didier Lime, Franck Cassez, Jean-François Raskin Overview Timed Games. Algorithm (CONCUR 05). Strategies. Code generation. Architecture
More informationGames with Costs and Delays
Games with Costs and Delays Martin Zimmermann Saarland University June 20th, 2017 LICS 2017, Reykjavik, Iceland Martin Zimmermann Saarland University Games with Costs and Delays 1/14 Gale-Stewart Games
More informationAdmissible Strategies for Synthesizing Systems
Admissible Strategies for Synthesizing Systems Ocan Sankur Univ Rennes, Inria, CNRS, IRISA, Rennes Joint with Romain Brenguier (DiffBlue), Guillermo Pérez (Antwerp), and Jean-François Raskin (ULB) (Multiplayer)
More informationArtificial Intelligence
Artificial Intelligence Roman Barták Department of Theoretical Computer Science and Mathematical Logic Summary of last lecture We know how to do probabilistic reasoning over time transition model P(X t
More informationLecture 7 Synthesis of Reactive Control Protocols
Lecture 7 Synthesis of Reactive Control Protocols Richard M. Murray Nok Wongpiromsarn Ufuk Topcu California Institute of Technology AFRL, 25 April 2012 Outline Review: networked control systems and cooperative
More informationProbabilistic Model Checking and Strategy Synthesis for Robot Navigation
Probabilistic Model Checking and Strategy Synthesis for Robot Navigation Dave Parker University of Birmingham (joint work with Bruno Lacerda, Nick Hawes) AIMS CDT, Oxford, May 2015 Overview Probabilistic
More informationValentin Goranko Stockholm University. ESSLLI 2018 August 6-10, of 29
ESSLLI 2018 course Logics for Epistemic and Strategic Reasoning in Multi-Agent Systems Lecture 5: Logics for temporal strategic reasoning with incomplete and imperfect information Valentin Goranko Stockholm
More informationThe Elusive Metric for Low-Power Architecture Research
The Elusive Metric for Low-Power Architecture Research Hsien-Hsin Hsin Sean Lee Joshua B. Fryman A. Utku Diril Yuvraj S. Dhillon Center for Experimental Research in Computer Systems Georgia Institute of
More informationFAULT-TOLERANT CONTROL OF CHEMICAL PROCESS SYSTEMS USING COMMUNICATION NETWORKS. Nael H. El-Farra, Adiwinata Gani & Panagiotis D.
FAULT-TOLERANT CONTROL OF CHEMICAL PROCESS SYSTEMS USING COMMUNICATION NETWORKS Nael H. El-Farra, Adiwinata Gani & Panagiotis D. Christofides Department of Chemical Engineering University of California,
More informationReach Sets and the Hamilton-Jacobi Equation
Reach Sets and the Hamilton-Jacobi Equation Ian Mitchell Department of Computer Science The University of British Columbia Joint work with Alex Bayen, Meeko Oishi & Claire Tomlin (Stanford) research supported
More informationRanked Predicate Abstraction for Branching Time. Complete, Incremental, and Precise
: Complete, Incremental, and Precise Harald Fecher 1 Michael Huth 2 1 Christian-Albrechts-University at Kiel, Germany 2 Imperial College London, United Kingdom Beijing, ATVA 2006 Main Issues Foundation
More informationLecture 9 Synthesis of Reactive Control Protocols
Lecture 9 Synthesis of Reactive Control Protocols Nok Wongpiromsarn Singapore-MIT Alliance for Research and Technology Richard M. Murray and Ufuk Topcu California Institute of Technology EECI, 16 May 2012
More informationDesign of Norm-Optimal Iterative Learning Controllers: The Effect of an Iteration-Domain Kalman Filter for Disturbance Estimation
Design of Norm-Optimal Iterative Learning Controllers: The Effect of an Iteration-Domain Kalman Filter for Disturbance Estimation Nicolas Degen, Autonomous System Lab, ETH Zürich Angela P. Schoellig, University
More informationSynthesis of Winning Strategies for Interaction under Partial Information
Synthesis of Winning Strategies for Interaction under Partial Information Oberseminar Informatik Bernd Puchala RWTH Aachen University June 10th, 2013 1 Introduction Interaction Strategy Synthesis 2 Main
More informationSRV02-Series Rotary Experiment # 1. Position Control. Student Handout
SRV02-Series Rotary Experiment # 1 Position Control Student Handout SRV02-Series Rotary Experiment # 1 Position Control Student Handout 1. Objectives The objective in this experiment is to introduce the
More informationSynthesizing Robust Systems
Synthesizing Robust Systems Roderick Bloem and Karin Greimel (TU-Graz) Thomas Henzinger (EPFL and IST-Austria) Barbara Jobstmann (CNRS/Verimag) FMCAD 2009 in Austin, Texas Barbara Jobstmann 1 Motivation
More informationUsing Theorem Provers to Guarantee Closed-Loop Properties
Using Theorem Provers to Guarantee Closed-Loop Properties Nikos Aréchiga Sarah Loos André Platzer Bruce Krogh Carnegie Mellon University April 27, 2012 Aréchiga, Loos, Platzer, Krogh (CMU) Theorem Provers
More informationANALYZING REAL TIME LINEAR CONTROL SYSTEMS USING SOFTWARE VERIFICATION. Parasara Sridhar Duggirala UConn Mahesh Viswanathan UIUC
ANALYZING REAL TIME LINEAR CONTROL SYSTEMS USING SOFTWARE VERIFICATION Parasara Sridhar Duggirala UConn Mahesh Viswanathan UIUC Real-Time Systems Linear Control Systems Verification Verification Control
More information: Cryptography and Game Theory Ran Canetti and Alon Rosen. Lecture 8
0368.4170: Cryptography and Game Theory Ran Canetti and Alon Rosen Lecture 8 December 9, 2009 Scribe: Naama Ben-Aroya Last Week 2 player zero-sum games (min-max) Mixed NE (existence, complexity) ɛ-ne Correlated
More information4 Arithmetic of Feedback Loops
ME 132, Spring 2005, UC Berkeley, A. Packard 18 4 Arithmetic of Feedback Loops Many important guiding principles of feedback control systems can be derived from the arithmetic relations, along with their
More informationSession-Based Queueing Systems
Session-Based Queueing Systems Modelling, Simulation, and Approximation Jeroen Horters Supervisor VU: Sandjai Bhulai Executive Summary Companies often offer services that require multiple steps on the
More informationTesting System Conformance for Cyber-Physical Systems
Testing System Conformance for Cyber-Physical Systems Testing systems by walking the dog Rupak Majumdar Max Planck Institute for Software Systems Joint work with Vinayak Prabhu (MPI-SWS) and Jyo Deshmukh
More informationCBE495 LECTURE IV MODEL PREDICTIVE CONTROL
What is Model Predictive Control (MPC)? CBE495 LECTURE IV MODEL PREDICTIVE CONTROL Professor Dae Ryook Yang Fall 2013 Dept. of Chemical and Biological Engineering Korea University * Some parts are from
More informationReal-Time Scheduling and Resource Management
ARTIST2 Summer School 2008 in Europe Autrans (near Grenoble), France September 8-12, 2008 Real-Time Scheduling and Resource Management Lecturer: Giorgio Buttazzo Full Professor Scuola Superiore Sant Anna
More informationSolving Stochastic Planning Problems With Large State and Action Spaces
Solving Stochastic Planning Problems With Large State and Action Spaces Thomas Dean, Robert Givan, and Kee-Eung Kim Thomas Dean and Kee-Eung Kim Robert Givan Department of Computer Science Department of
More informationarxiv: v1 [cs.gt] 14 Sep 2017
Synthesizing Optimally Resilient Controllers Daniel Neider 1, Alexander Weinert 2 and Martin Zimmermann 2 1 Max Planck Institute for Software Systems, 67663 Kaiserslautern, Germany neider@mpi-sws.org 2
More informationDynamic and Adversarial Reachavoid Symbolic Planning
Dynamic and Adversarial Reachavoid Symbolic Planning Laya Shamgah Advisor: Dr. Karimoddini July 21 st 2017 Thrust 1: Modeling, Analysis and Control of Large-scale Autonomous Vehicles (MACLAV) Sub-trust
More informationTraffic Modelling for Moving-Block Train Control System
Commun. Theor. Phys. (Beijing, China) 47 (2007) pp. 601 606 c International Academic Publishers Vol. 47, No. 4, April 15, 2007 Traffic Modelling for Moving-Block Train Control System TANG Tao and LI Ke-Ping
More informationThe priority promotion approach to parity games
The priority promotion approach to parity games Massimo Benerecetti 1, Daniele Dell Erba 1, and Fabio Mogavero 2 1 Università degli Studi di Napoli Federico II 2 Università degli Studi di Verona Abstract.
More informationWhere we ve been, where we are, and where we are going next.
6.302.0x, January 2016 Notes Set 2 1 MASSACHVSETTS INSTITVTE OF TECHNOLOGY Department of Electrical Engineering and Computer Science 6.302.0x Introduction to Feedback System Design January 2016 Notes Set
More informationInfluence of the gap and the friction on trajectory reproduction accuracy in a multiaxis machine with CNC
Influence of the gap and the friction on trajectory reproduction accuracy in a multiaxis machine with CNC O. V. Pas 1, N. A. Serkov 2 Blagonravov Institute of Engineering Science, Russian Academy of Sciences,
More informationGeneral procedure for formulation of robot dynamics STEP 1 STEP 3. Module 9 : Robot Dynamics & controls
Module 9 : Robot Dynamics & controls Lecture 32 : General procedure for dynamics equation forming and introduction to control Objectives In this course you will learn the following Lagrangian Formulation
More informationTimed Games and. Stochastic Priced Timed Games
STRATEGO Timed Games and TIGA Stochastic Priced Timed Games Synthesis & Machine Learning Kim G. Larsen Aalborg University DENMARK Overview Timed Automata Decidability (regions) Symbolic Verification (zones)
More informationBounded Model Checking with SAT/SMT. Edmund M. Clarke School of Computer Science Carnegie Mellon University 1/39
Bounded Model Checking with SAT/SMT Edmund M. Clarke School of Computer Science Carnegie Mellon University 1/39 Recap: Symbolic Model Checking with BDDs Method used by most industrial strength model checkers:
More informationControl System Design
ELEC ENG 4CL4: Control System Design Notes for Lecture #24 Wednesday, March 10, 2004 Dr. Ian C. Bruce Room: CRL-229 Phone ext.: 26984 Email: ibruce@mail.ece.mcmaster.ca Remedies We next turn to the question
More informationFailure Diagnosis of Discrete-Time Stochastic Systems subject to Temporal Logic Correctness Requirements
Failure Diagnosis of Discrete-Time Stochastic Systems subject to Temporal Logic Correctness Requirements Jun Chen, Student Member, IEEE and Ratnesh Kumar, Fellow, IEEE Dept. of Elec. & Comp. Eng., Iowa
More informationA Survey of Partial-Observation Stochastic Parity Games
Noname manuscript No. (will be inserted by the editor) A Survey of Partial-Observation Stochastic Parity Games Krishnendu Chatterjee Laurent Doyen Thomas A. Henzinger the date of receipt and acceptance
More informationLecture 2: Just married
COMP36111: Advanced Algorithms I Lecture 2: Just married Ian Pratt-Hartmann Room KB2.38: email: ipratt@cs.man.ac.uk 2017 18 Outline Matching Flow networks Third-year projects The stable marriage problem
More informationDES. 4. Petri Nets. Introduction. Different Classes of Petri Net. Petri net properties. Analysis of Petri net models
4. Petri Nets Introduction Different Classes of Petri Net Petri net properties Analysis of Petri net models 1 Petri Nets C.A Petri, TU Darmstadt, 1962 A mathematical and graphical modeling method. Describe
More informationSymbolic Reachability Analysis of Lazy Linear Hybrid Automata. Susmit Jha, Bryan Brady and Sanjit A. Seshia
Symbolic Reachability Analysis of Lazy Linear Hybrid Automata Susmit Jha, Bryan Brady and Sanjit A. Seshia Traditional Hybrid Automata Traditional Hybrid Automata do not model delay and finite precision
More informationA Robust Controller for Scalar Autonomous Optimal Control Problems
A Robust Controller for Scalar Autonomous Optimal Control Problems S. H. Lam 1 Department of Mechanical and Aerospace Engineering Princeton University, Princeton, NJ 08544 lam@princeton.edu Abstract Is
More informationComputer Science 385 Analysis of Algorithms Siena College Spring Topic Notes: Limitations of Algorithms
Computer Science 385 Analysis of Algorithms Siena College Spring 2011 Topic Notes: Limitations of Algorithms We conclude with a discussion of the limitations of the power of algorithms. That is, what kinds
More informationIC3 and Beyond: Incremental, Inductive Verification
IC3 and Beyond: Incremental, Inductive Verification Aaron R. Bradley ECEE, CU Boulder & Summit Middle School IC3 and Beyond: Incremental, Inductive Verification 1/62 Induction Foundation of verification
More informationME 132, Dynamic Systems and Feedback. Class Notes. Spring Instructor: Prof. A Packard
ME 132, Dynamic Systems and Feedback Class Notes by Andrew Packard, Kameshwar Poolla & Roberto Horowitz Spring 2005 Instructor: Prof. A Packard Department of Mechanical Engineering University of California
More informationComputational Complexity
p. 1/24 Computational Complexity The most sharp distinction in the theory of computation is between computable and noncomputable functions; that is, between possible and impossible. From the example of
More informationSupervisory Control of Hybrid Systems
X.D. Koutsoukos, P.J. Antsaklis, J.A. Stiver and M.D. Lemmon, "Supervisory Control of Hybrid Systems, in Special Issue on Hybrid Systems: Theory and Applications, Proceedings of the IEEE, P.J. Antsaklis,
More informationCOMP3702/7702 Artificial Intelligence Week1: Introduction Russell & Norvig ch.1-2.3, Hanna Kurniawati
COMP3702/7702 Artificial Intelligence Week1: Introduction Russell & Norvig ch.1-2.3, 3.1-3.3 Hanna Kurniawati Today } What is Artificial Intelligence? } Better know what it is first before committing the
More informationA Strategic Epistemic Logic for Bounded Memory Agents
CNRS, Université de Lorraine, Nancy, France Workshop on Resource Bounded Agents Barcelona 12 August, 2015 Contents 1 Introduction 2 3 4 5 Combining Strategic and Epistemic Reasoning The goal is to develop
More informationAlgorithmic Verification of Stability of Hybrid Systems
Algorithmic Verification of Stability of Hybrid Systems Pavithra Prabhakar Kansas State University University of Kansas February 24, 2017 1 Cyber-Physical Systems (CPS) Systems in which software "cyber"
More informationAutomatic Synthesis of Distributed Protocols
Automatic Synthesis of Distributed Protocols Rajeev Alur Stavros Tripakis 1 Introduction Protocols for coordination among concurrent processes are an essential component of modern multiprocessor and distributed
More informationImplementing Uniform Reliable Broadcast with Binary Consensus in Systems with Fair-Lossy Links
Implementing Uniform Reliable Broadcast with Binary Consensus in Systems with Fair-Lossy Links Jialin Zhang Tsinghua University zhanggl02@mails.tsinghua.edu.cn Wei Chen Microsoft Research Asia weic@microsoft.com
More informationInfinite Games. Sumit Nain. 28 January Slides Credit: Barbara Jobstmann (CNRS/Verimag) Department of Computer Science Rice University
Infinite Games Sumit Nain Department of Computer Science Rice University 28 January 2013 Slides Credit: Barbara Jobstmann (CNRS/Verimag) Motivation Abstract games are of fundamental importance in mathematics
More informationEE C128 / ME C134 Feedback Control Systems
EE C128 / ME C134 Feedback Control Systems Lecture Additional Material Introduction to Model Predictive Control Maximilian Balandat Department of Electrical Engineering & Computer Science University of
More informationProblem Set #2 Due: 1:00pm on Monday, Oct 15th
Chris Piech PSet #2 CS109 October 5, 2018 Problem Set #2 Due: 1:00pm on Monday, Oct 15th For each problem, briefly explain/justify how you obtained your answer in order to obtain full credit. Your explanations
More informationEnergy Modeling of Processors in Wireless Sensor Networks based on Petri Nets
Energy Modeling of Processors in Wireless Sensor Networks based on Petri Nets Ali Shareef, Yifeng Zhu Department of Electrical and Computer Engineering University of Maine, Orono, USA Email: {ashareef,
More informationControl Synthesis of Discrete Manufacturing Systems using Timed Finite Automata
Control Synthesis of Discrete Manufacturing Systems using Timed Finite utomata JROSLV FOGEL Institute of Informatics Slovak cademy of Sciences ratislav Dúbravská 9, SLOVK REPULIC bstract: - n application
More informationSENSE: Abstraction-Based Synthesis of Networked Control Systems
SENSE: Abstraction-Based Synthesis of Networked Control Systems Mahmoud Khaled, Matthias Rungger, and Majid Zamani Hybrid Control Systems Group Electrical and Computer Engineering Technical University
More informationDistributed games with causal memory are decidable for series-parallel systems
Distributed games with causal memory are decidable for series-parallel systems Paul Gastin, enjamin Lerman, Marc Zeitoun Firstname.Name@liafa.jussieu.fr LIF, Université Paris 7, UMR CNRS 7089 FSTTCS, dec.
More informationWind Turbine Control
Wind Turbine Control W. E. Leithead University of Strathclyde, Glasgow Supergen Student Workshop 1 Outline 1. Introduction 2. Control Basics 3. General Control Objectives 4. Constant Speed Pitch Regulated
More informationOnline Convex Optimization Using Predictions
Online Convex Optimization Using Predictions Niangjun Chen Joint work with Anish Agarwal, Lachlan Andrew, Siddharth Barman, and Adam Wierman 1 c " c " (x " ) F x " 2 c ) c ) x ) F x " x ) β x ) x " 3 F
More informationRobot Autonomy Notes
Robot Autonomy Notes January 25, 2017 Andy Tracy - atracy@andrew.cmu.edu Nima Rahnemoon - nrahnemo@andrew.cmu.edu Samuel Chandler - sxchandl@andrew.cmu.edu Manipulation Planning There are 2 main components
More informationBridging the Gap between Reactive Synthesis and Supervisory Control
Bridging the Gap between Reactive Synthesis and Supervisory Control Stavros Tripakis University of California, Berkeley Joint work with Ruediger Ehlers (Berkeley, Cornell), Stéphane Lafortune (Michigan)
More informationTrajectory planning and feedforward design for electromechanical motion systems version 2
2 Trajectory planning and feedforward design for electromechanical motion systems version 2 Report nr. DCT 2003-8 Paul Lambrechts Email: P.F.Lambrechts@tue.nl April, 2003 Abstract This report considers
More informationCompositional Synthesis with Parametric Reactive Controllers
Compositional Synthesis with Parametric Reactive Controllers Rajeev Alur University of Pennsylvania alur@seas.upenn.edu Salar Moarref University of Pennsylvania moarref@seas.upenn.edu Ufuk Topcu University
More informationAN INTERNATIONAL SOLAR IRRADIANCE DATA INGEST SYSTEM FOR FORECASTING SOLAR POWER AND AGRICULTURAL CROP YIELDS
AN INTERNATIONAL SOLAR IRRADIANCE DATA INGEST SYSTEM FOR FORECASTING SOLAR POWER AND AGRICULTURAL CROP YIELDS James Hall JHTech PO Box 877 Divide, CO 80814 Email: jameshall@jhtech.com Jeffrey Hall JHTech
More informationThe science behind these computers originates in
A Methodology for Quantum Risk Assessment Author: Dr. Michele Mosca & John Mulholland DISRUPTIVE TECHNOLOGY INTRODUCTION Until recently, quantum computing was often viewed as a capability that might emerge
More informationSolving Bateman Equation for Xenon Transient Analysis Using Numerical Methods
Solving Bateman Equation for Xenon Transient Analysis Using Numerical Methods Zechuan Ding Illume Research, 405 Xintianshiji Business Center, 5 Shixia Road, Shenzhen, China Abstract. After a nuclear reactor
More informationInnovative Solutions from the Process Control Professionals
Control Station Innovative Solutions from the Process Control Professionals Software For Process Control Analysis, Tuning & Training Control Station Software For Process Control Analysis, Tuning & Training
More informationExercises Solutions. Automation IEA, LTH. Chapter 2 Manufacturing and process systems. Chapter 5 Discrete manufacturing problems
Exercises Solutions Note, that we have not formulated the answers for all the review questions. You will find the answers for many questions by reading and reflecting about the text in the book. Chapter
More informationAbstraction-based synthesis: Challenges and victories
Abstraction-based synthesis: Challenges and victories Majid Zamani Hybrid Control Systems Group Electrical Engineering Department Technische Universität München December 14, 2015 Majid Zamani (TU München)
More informationChapter 7 Control. Part Classical Control. Mobile Robotics - Prof Alonzo Kelly, CMU RI
Chapter 7 Control 7.1 Classical Control Part 1 1 7.1 Classical Control Outline 7.1.1 Introduction 7.1.2 Virtual Spring Damper 7.1.3 Feedback Control 7.1.4 Model Referenced and Feedforward Control Summary
More informationVerification of Hybrid Systems with Ariadne
Verification of Hybrid Systems with Ariadne Davide Bresolin 1 Luca Geretti 2 Tiziano Villa 3 1 University of Bologna 2 University of Udine 3 University of Verona An open workshop on Formal Methods for
More informationNUCLEAR POPCORN OBJECTIVE: Grade: Help students visualize the rate of radioactive decay. Intended Learning Outcome:
NUCLEAR POPCORN Teacher s Notes OBJECTIVE: Help students visualize the rate of radioactive decay. Grade: 7 12 Intended Learning Outcome: Reason mathematically Make predictions Construct tables and graphs
More informationNeural Networks 2. 2 Receptive fields and dealing with image inputs
CS 446 Machine Learning Fall 2016 Oct 04, 2016 Neural Networks 2 Professor: Dan Roth Scribe: C. Cheng, C. Cervantes Overview Convolutional Neural Networks Recurrent Neural Networks 1 Introduction There
More informationSpecification models and their analysis Petri Nets
Specification models and their analysis Petri Nets Kai Lampka December 10, 2010 1 30 Part I Petri Nets Basics Petri Nets Introduction A Petri Net (PN) is a weighted(?), bipartite(?) digraph(?) invented
More informationResearch on State-of-Charge (SOC) estimation using current integration based on temperature compensation
IOP Conference Series: Earth and Environmental Science PAPER OPEN ACCESS Research on State-of-Charge (SOC) estimation using current integration based on temperature compensation To cite this article: J
More informationalgorithms Alpha-Beta Pruning and Althöfer s Pathology-Free Negamax Algorithm Algorithms 2012, 5, ; doi: /a
Algorithms 01, 5, 51-58; doi:10.3390/a504051 Article OPEN ACCESS algorithms ISSN 1999-4893 www.mdpi.com/journal/algorithms Alpha-Beta Pruning and Althöfer s Pathology-Free Negamax Algorithm Ashraf M. Abdelbar
More informationSystem Model. Real-Time systems. Giuseppe Lipari. Scuola Superiore Sant Anna Pisa -Italy
Real-Time systems System Model Giuseppe Lipari Scuola Superiore Sant Anna Pisa -Italy Corso di Sistemi in tempo reale Laurea Specialistica in Ingegneria dell Informazione Università di Pisa p. 1/?? Task
More informationH -Optimal Control and Related Minimax Design Problems
Tamer Başar Pierre Bernhard H -Optimal Control and Related Minimax Design Problems A Dynamic Game Approach Second Edition 1995 Birkhäuser Boston Basel Berlin Contents Preface v 1 A General Introduction
More information4.0 Update Algorithms For Linear Closed-Loop Systems
4. Update Algorithms For Linear Closed-Loop Systems A controller design methodology has been developed that combines an adaptive finite impulse response (FIR) filter with feedback. FIR filters are used
More informationIntroduction to Modelling and Simulation
Introduction to Modelling and Simulation Prof. Cesar de Prada Dpt. Systems Engineering and Automatic Control EII, University of Valladolid, Spain prada@autom.uva.es Digital simulation Methods and tools
More informationExpectations or Guarantees? I Want It All! A Crossroad between Games and MDPs
Expectations or Guarantees? I Want It All! A Crossroad between Games and MDPs V. Bruyère (UMONS) E. Filiot (ULB) M. Randour (UMONS-ULB) J.-F. Raskin (ULB) Grenoble - 0.04.04 SR 04 - nd International Workshop
More information1 Introduction (January 21)
CS 97: Concrete Models of Computation Spring Introduction (January ). Deterministic Complexity Consider a monotonically nondecreasing function f : {,,..., n} {, }, where f() = and f(n) =. We call f a step
More informationLyapunov Stability of Linear Predictor Feedback for Distributed Input Delays
IEEE TRANSACTIONS ON AUTOMATIC CONTROL VOL. 56 NO. 3 MARCH 2011 655 Lyapunov Stability of Linear Predictor Feedback for Distributed Input Delays Nikolaos Bekiaris-Liberis Miroslav Krstic In this case system
More informationProbReach: Probabilistic Bounded Reachability for Uncertain Hybrid Systems
ProbReach: Probabilistic Bounded Reachability for Uncertain Hybrid Systems Fedor Shmarov, Paolo Zuliani School of Computing Science, Newcastle University, UK 1 / 41 Introduction ProbReach tool for probabilistic
More informationDoing It Now or Later
Doing It Now or Later Ted O Donoghue and Matthew Rabin published in American Economic Review, 1999 October 31, 2011 Introduction Economists almost always capture impatience by exponential discounting of
More informationOn evaluating decision procedures for modal logic
On evaluating decision procedures for modal logic Ullrich Hustadt and Renate A. Schmidt Max-Planck-Institut fur Informatik, 66123 Saarbriicken, Germany {hustadt, schmidt} topi-sb.mpg.de Abstract This paper
More information6.852: Distributed Algorithms Fall, Class 10
6.852: Distributed Algorithms Fall, 2009 Class 10 Today s plan Simulating synchronous algorithms in asynchronous networks Synchronizers Lower bound for global synchronization Reading: Chapter 16 Next:
More informationSwitched Systems: Mixing Logic with Differential Equations
research supported by NSF Switched Systems: Mixing Logic with Differential Equations João P. Hespanha Center for Control Dynamical Systems and Computation Outline Logic-based switched systems framework
More information6196 IEEE TRANSACTIONS ON INFORMATION THEORY, VOL. 57, NO. 9, SEPTEMBER 2011
6196 IEEE TRANSACTIONS ON INFORMATION THEORY, VOL. 57, NO. 9, SEPTEMBER 2011 On the Structure of Real-Time Encoding and Decoding Functions in a Multiterminal Communication System Ashutosh Nayyar, Student
More informationOFFSHORE. Advanced Weather Technology
Contents 3 Advanced Weather Technology 5 Working Safely, While Limiting Downtime 6 Understanding the Weather Forecast Begins at the Tender Stage 7 Reducing Time and Costs on Projects is a Priority Across
More informationOutline. Classical Control. Lecture 1
Outline Outline Outline 1 Introduction 2 Prerequisites Block diagram for system modeling Modeling Mechanical Electrical Outline Introduction Background Basic Systems Models/Transfers functions 1 Introduction
More informationSynthesis of Designs from Property Specifications
Synthesis of Designs from Property Specifications Amir Pnueli New York University and Weizmann Institute of Sciences FMCAD 06 San Jose, November, 2006 Joint work with Nir Piterman, Yaniv Sa ar, Research
More informationAbstractions and Decision Procedures for Effective Software Model Checking
Abstractions and Decision Procedures for Effective Software Model Checking Prof. Natasha Sharygina The University of Lugano, Carnegie Mellon University Microsoft Summer School, Moscow, July 2011 Lecture
More informationVerification and Synthesis. Using Real Quantifier Elimination. Ashish Tiwari, SRI Intl. Verif. and Synth. Using Real QE: 1
Verification and Synthesis Using Real Quantifier Elimination Thomas Sturm Max-Planck-Institute for Informatik Saarbrucken, Germany sturm@mpi-inf.mpg.de Ashish Tiwari SRI International Menlo Park, USA tiwari@csl.sri.com
More informationUnderstanding IC3. Aaron R. Bradley. ECEE, CU Boulder & Summit Middle School. Understanding IC3 1/55
Understanding IC3 Aaron R. Bradley ECEE, CU Boulder & Summit Middle School Understanding IC3 1/55 Further Reading This presentation is based on Bradley, A. R. Understanding IC3. In SAT, June 2012. http://theory.stanford.edu/~arbrad
More informationBoundedness Games. Séminaire de l équipe MoVe, LIF, Marseille, May 2nd, Nathanaël Fijalkow. Institute of Informatics, Warsaw University Poland
Boundedness Games Séminaire de l équipe MoVe, LIF, Marseille, May 2nd, 2013 Nathanaël Fijalkow Institute of Informatics, Warsaw University Poland LIAFA, Université Paris 7 Denis Diderot France (based on
More informationSequential Equivalence Checking without State Space Traversal
Sequential Equivalence Checking without State Space Traversal C.A.J. van Eijk Design Automation Section, Eindhoven University of Technology P.O.Box 53, 5600 MB Eindhoven, The Netherlands e-mail: C.A.J.v.Eijk@ele.tue.nl
More informationDecentralized Control of Discrete Event Systems with Bounded or Unbounded Delay Communication 1
Decentralized Control of Discrete Event Systems with Bounded or Unbounded Delay Communication 1 Stavros Tripakis 2 VERIMAG Technical Report TR-2004-26 November 2004 Abstract We introduce problems of decentralized
More information