DSSynth: An Automated Digital Controller Synthesis Tool for Physical Plants ASE 2017

Transcription

1 DSSynth: An Automated Digital Controller Synthesis Tool for Physical Plants ASE 2017 Alessandro Abate, Iury Bessa, Dario Cattaruzza, Lennon Chaves, Lucas Cordeiro, Cristina David, Pascal Kesseli, Daniel Kroening and Elizabeth Polgreen Diffblue Ltd., University of Oxford, Federal University of Amazonas November 1 st, 2017

2 Motivation 2 of 13

3 Motivation Automatically synthesise digital controllers 2 of 13

4 Typical closed-loop control system Representation of the digital controller and plant state-space: matrices A, B, C, and D transfer-function: coefficients b 0, b 1,...,b m and a 0, a 1,...,a m 3 of 13

5 Typical closed-loop control system Representation of the digital controller and plant state-space: matrices A, B, C, and D transfer-function: coefficients b 0, b 1,...,b m and a 0, a 1,...,a m Stability of closed-loop systems presents a bnded response for any bnded excitation 3 of 13

6 Typical closed-loop control system Representation of the digital controller and plant state-space: matrices A, B, C, and D transfer-function: coefficients b 0, b 1,...,b m and a 0, a 1,...,a m Stability of closed-loop systems presents a bnded response for any bnded excitation Safety of closed-loop systems defines a requirement on the states of the model 3 of 13

7 Typical closed-loop control system Representation of the digital controller and plant state-space: matrices A, B, C, and D transfer-function: coefficients b 0, b 1,...,b m and a 0, a 1,...,a m Stability of closed-loop systems presents a bnded response for any bnded excitation Safety of closed-loop systems defines a requirement on the states of the model Numerical erros (truncation and rnding) 3 of 13

8 Objectives Generate snd digital controllers for stability and safety specifications with a very high degree of automation 4 of 13

9 Objectives Generate snd digital controllers for stability and safety specifications with a very high degree of automation support for transfer-function and state-space representations in closed-loop form 4 of 13

10 Objectives Generate snd digital controllers for stability and safety specifications with a very high degree of automation support for transfer-function and state-space representations in closed-loop form synthesize different numerical representations of the controller using CnterExample Guided Inductive Synthesis (CEGIS) 4 of 13

11 Objectives Generate snd digital controllers for stability and safety specifications with a very high degree of automation support for transfer-function and state-space representations in closed-loop form synthesize different numerical representations of the controller using CnterExample Guided Inductive Synthesis (CEGIS) provide a MATLAB toolbox to synthesize digital controllers while taking into accnt finite word-length effects 4 of 13

12 The Proposed Synthesis Methodology Phases of the controller synthesis: 5 of 13

13 CEGIS for Control Systems CEGIS with multi-staged verification: Increase Unfolding Bnd Increase Precision Synthesize K C-ex Verify PASS 1.Safety 2.Precision 3.Complete Done Program Search BMC-based Verifier Fixed-point Arithmetic Verifier Completeness Verifier 6 of 13

14 DSSynth Usage - Transfer Function Physical plant for an unmanned aerial vehicle (UAV) plant: G(z) = B(z) A(z) = z 2 z z (1) Synthesizing the digital controller: >> num = [ ]; >> den = [ ]; >> system = tf(num,den,0.002); >> y = synthesize (system,8,8,1, -1); >> SYNTHESIS SUCCESSFUL >> y = >> z^ z >> >> z^ z of 13

15 DSSynth Usage - Transfer Function Digital controller synthesized by DSSynth: C(z) = z z 2. (2) z Computing the general equation (plant and controller): >> num = [ ]; >> den = [ ]; >> controller = tf(num,den,0.002); >> num = [ ]; >> den = [ ]; >> plant = tf(num,den,0.002); >> sys = feedback ( series ( controller, plant ),1) >> sys = >> z^ z^ z^2 >> >> z^ z^ z^ z of 13

16 DSSynth Usage - Step Response Step response for the UAV plant describing a stable system: 0.7 Step Response Amplitude Time (seconds) 9 of 13

17 DSSynth Usage - MATLAB Application (a) Definition of the system representation and the physical plant (b) Definition of implementation aspects and input ranges 10 of 13

18 DSSynth Usage - MATLAB Application (c) Digital controller synthesized by DSSynth (d) Step response for the synthesized digital controller 11 of 13

19 Experimental Evaluation Our evaluation consists of 18 Single-Input and Single-Output control system benchmarks extracted from the literature: 12 of 13

20 Experimental Evaluation Our evaluation consists of 18 Single-Input and Single-Output control system benchmarks extracted from the literature: Experimental Objectives: Evaluate the DSSynth performance to produce digital controllers Confirm the stability and safety tside of r model using MATLAB 12 of 13

21 Experimental Evaluation Our evaluation consists of 18 Single-Input and Single-Output control system benchmarks extracted from the literature: Experimental Objectives: Evaluate the DSSynth performance to produce digital controllers Confirm the stability and safety tside of r model using MATLAB Experimental Setup: Signal input range: 1, 1 Implementation features: 8, 8 Intel Core i GHz processor with 24 GB of RAM 12 of 13

22 Experimental Evaluation Experimental Results: The digital controller order ranges from 1 to 8 13 of 13

23 Experimental Evaluation Experimental Results: The digital controller order ranges from 1 to 8 The number of state variables ranges from 1 to 9 13 of 13

24 Experimental Evaluation Experimental Results: The digital controller order ranges from 1 to 8 The number of state variables ranges from 1 to 9 The average synthesis time amnts to 35.5 s for state-space systems 13 of 13

25 Experimental Evaluation Experimental Results: The digital controller order ranges from 1 to 8 The number of state variables ranges from 1 to 9 The average synthesis time amnts to 35.5 s for state-space systems The average synthesis time amnts to s for transfer functions 13 of 13

26 Experimental Evaluation Experimental Results: The digital controller order ranges from 1 to 8 The number of state variables ranges from 1 to 9 The average synthesis time amnts to 35.5 s for state-space systems The average synthesis time amnts to s for transfer functions On average r engine spent 52% in the synthesis and 48% in the verification phase 13 of 13

27 Experimental Evaluation Experimental Results: The digital controller order ranges from 1 to 8 The number of state variables ranges from 1 to 9 The average synthesis time amnts to 35.5 s for state-space systems The average synthesis time amnts to s for transfer functions On average r engine spent 52% in the synthesis and 48% in the verification phase DSSynth Matlab toolbox: of 13