Course Summary Unit 1: Introduction Unit 2: Modeling in the Frequency Domain Unit 3: Time Response Unit 4: Block Diagram Reduction Unit 5: Stability Unit 6: Steady-State Error Unit 7: Root Locus Techniques Unit 8: Design via Root Locus Course Summary The course cannot be summarized in one lecture. ENGI 5821 Course Summary
Course Summary Unit 1: Introduction Unit 2: Modeling in the Frequency Domain Unit 3: Time Response Unit 4: Block Diagram Reduction Unit 5: Stability Unit 6: Steady-State Error Unit 7: Root Locus Techniques Unit 8: Design via Root Locus Course Summary The course cannot be summarized in one lecture. The intent here is to go through each unit of the course and mention some of the most important or poorly understood concepts. ENGI 5821 Course Summary
Course Summary Unit 1: Introduction Unit 2: Modeling in the Frequency Domain Unit 3: Time Response Unit 4: Block Diagram Reduction Unit 5: Stability Unit 6: Steady-State Error Unit 7: Root Locus Techniques Unit 8: Design via Root Locus Course Summary The course cannot be summarized in one lecture. The intent here is to go through each unit of the course and mention some of the most important or poorly understood concepts. This brief tour is no replacement for the course itself! ENGI 5821 Course Summary
Course Summary Unit 1: Introduction Unit 2: Modeling in the Frequency Domain Unit 3: Time Response Unit 4: Block Diagram Reduction Unit 5: Stability Unit 6: Steady-State Error Unit 7: Root Locus Techniques Unit 8: Design via Root Locus Course Summary The course cannot be summarized in one lecture. The intent here is to go through each unit of the course and mention some of the most important or poorly understood concepts. This brief tour is no replacement for the course itself! Many important details will be skipped. ENGI 5821 Course Summary
Unit 1: Introduction Introduction
Unit 1: Introduction Introduction System Configurations
Unit 1: Introduction Introduction System Configurations Open-loop vs. Closed-loop
Unit 1: Introduction Introduction System Configurations Open-loop vs. Closed-loop Measuring Performance
Unit 1: Introduction Introduction System Configurations Open-loop vs. Closed-loop Measuring Performance Transient response, steady-state error, stability
Unit 1: Introduction Introduction System Configurations Open-loop vs. Closed-loop Measuring Performance Transient response, steady-state error, stability The Design Process
Unit 1: Introduction Introduction System Configurations Open-loop vs. Closed-loop Measuring Performance Transient response, steady-state error, stability The Design Process specifications
Unit 1: Introduction Introduction System Configurations Open-loop vs. Closed-loop Measuring Performance Transient response, steady-state error, stability The Design Process specifications required performance measures
Unit 1: Introduction Introduction System Configurations Open-loop vs. Closed-loop Measuring Performance Transient response, steady-state error, stability The Design Process specifications required performance measures schematic
Unit 1: Introduction Introduction System Configurations Open-loop vs. Closed-loop Measuring Performance Transient response, steady-state error, stability The Design Process specifications required performance measures schematic transfer function for components
Unit 1: Introduction Introduction System Configurations Open-loop vs. Closed-loop Measuring Performance Transient response, steady-state error, stability The Design Process specifications required performance measures schematic transfer function for components transfer function for system
Unit 1: Introduction Introduction System Configurations Open-loop vs. Closed-loop Measuring Performance Transient response, steady-state error, stability The Design Process specifications required performance measures schematic transfer function for components transfer function for system analysis and design
Unit 2: Modeling in the Frequency Domain Complex Frequency: x(t) = R{Xe st } We can express constants, exponentials, sinusoids, and exponentially decaying or growing sinusoids by varying s. The actual amplitude and phase of a particular signal is expressed in X.
Unit 2: Modeling in the Frequency Domain Complex Frequency: x(t) = R{Xe st } We can express constants, exponentials, sinusoids, and exponentially decaying or growing sinusoids by varying s. The actual amplitude and phase of a particular signal is expressed in X.
Unit 2: Modeling in the Frequency Domain Complex Frequency: x(t) = R{Xe st } We can express constants, exponentials, sinusoids, and exponentially decaying or growing sinusoids by varying s. The actual amplitude and phase of a particular signal is expressed in X. Laplace Transform
Unit 2: Modeling in the Frequency Domain Complex Frequency: x(t) = R{Xe st } We can express constants, exponentials, sinusoids, and exponentially decaying or growing sinusoids by varying s. The actual amplitude and phase of a particular signal is expressed in X. Laplace Transform Transforms any signal into a combination of complex exponentials
Unit 2: Modeling in the Frequency Domain Complex Frequency: x(t) = R{Xe st } We can express constants, exponentials, sinusoids, and exponentially decaying or growing sinusoids by varying s. The actual amplitude and phase of a particular signal is expressed in X. Laplace Transform Transforms any signal into a combination of complex exponentials Tables of transform pairs and theorems
Unit 2: Modeling in the Frequency Domain Complex Frequency: x(t) = R{Xe st } We can express constants, exponentials, sinusoids, and exponentially decaying or growing sinusoids by varying s. The actual amplitude and phase of a particular signal is expressed in X. Laplace Transform Transforms any signal into a combination of complex exponentials Tables of transform pairs and theorems Use partial-fraction expansion to decompose ratio of polynomials
Transfer Functions
Transfer Functions Can be developed for LTI systems with zero-initial conditions
Transfer Functions Can be developed for LTI systems with zero-initial conditions Transfer function G(s) gives the system output C(s) for any input R(s): C(s) = R(s)G(s)
Transfer Functions Can be developed for LTI systems with zero-initial conditions Transfer function G(s) gives the system output C(s) for any input R(s): C(s) = R(s)G(s) Electrical Systems
Transfer Functions Can be developed for LTI systems with zero-initial conditions Transfer function G(s) gives the system output C(s) for any input R(s): C(s) = R(s)G(s) Electrical Systems Slow method: Develop DE s, apply Laplace, form TF
Transfer Functions Can be developed for LTI systems with zero-initial conditions Transfer function G(s) gives the system output C(s) for any input R(s): C(s) = R(s)G(s) Electrical Systems Slow method: Develop DE s, apply Laplace, form TF Fast method: Define transfer functions for individual components and state the problem in the freq. domain
Transfer Functions Can be developed for LTI systems with zero-initial conditions Transfer function G(s) gives the system output C(s) for any input R(s): C(s) = R(s)G(s) Electrical Systems Slow method: Develop DE s, apply Laplace, form TF Fast method: Define transfer functions for individual components and state the problem in the freq. domain Circuit analysis techniques developed for resistive circuits automatically work for L s and C s in the freq. domain!
Transfer Functions Can be developed for LTI systems with zero-initial conditions Transfer function G(s) gives the system output C(s) for any input R(s): C(s) = R(s)G(s) Electrical Systems Slow method: Develop DE s, apply Laplace, form TF Fast method: Define transfer functions for individual components and state the problem in the freq. domain Circuit analysis techniques developed for resistive circuits automatically work for L s and C s in the freq. domain! Op-Amps: Utilize ideal op-amp assumptions
Mechanical Systems
Mechanical Systems Mechanical components in translational and rotational forms
Mechanical Systems Mechanical components in translational and rotational forms opposing forces = applied forces
Mechanical Systems Mechanical components in translational and rotational forms opposing forces = applied forces One equation of motion for each linearly independent motion
Mechanical Systems Mechanical components in translational and rotational forms opposing forces = applied forces One equation of motion for each linearly independent motion In rotational systems torque replaces force (T = FR if F axis of rot.) and moment-of-inertia replaces mass
Mechanical Systems Mechanical components in translational and rotational forms opposing forces = applied forces One equation of motion for each linearly independent motion In rotational systems torque replaces force (T = FR if F axis of rot.) and moment-of-inertia replaces mass Gears linearly relate the motions of multiple shafts
Mechanical Systems Mechanical components in translational and rotational forms opposing forces = applied forces One equation of motion for each linearly independent motion In rotational systems torque replaces force (T = FR if F axis of rot.) and moment-of-inertia replaces mass Gears linearly relate the motions of multiple shafts Mechanical impedances can be reflected between shafts to simplify the calculation of TF
Mechanical Systems Mechanical components in translational and rotational forms opposing forces = applied forces One equation of motion for each linearly independent motion In rotational systems torque replaces force (T = FR if F axis of rot.) and moment-of-inertia replaces mass Gears linearly relate the motions of multiple shafts Mechanical impedances can be reflected between shafts to simplify the calculation of TF Motors: Electromechanical systems
Mechanical Systems Mechanical components in translational and rotational forms opposing forces = applied forces One equation of motion for each linearly independent motion In rotational systems torque replaces force (T = FR if F axis of rot.) and moment-of-inertia replaces mass Gears linearly relate the motions of multiple shafts Mechanical impedances can be reflected between shafts to simplify the calculation of TF Motors: Electromechanical systems Derived θ m (s)/e a (s) = K/s(s + α)
Mechanical Systems Mechanical components in translational and rotational forms opposing forces = applied forces One equation of motion for each linearly independent motion In rotational systems torque replaces force (T = FR if F axis of rot.) and moment-of-inertia replaces mass Gears linearly relate the motions of multiple shafts Mechanical impedances can be reflected between shafts to simplify the calculation of TF Motors: Electromechanical systems Derived θ m (s)/e a (s) = K/s(s + α) Jump back to the time-domain to run tests and evaluate motor parameters
Mechanical Systems Mechanical components in translational and rotational forms opposing forces = applied forces One equation of motion for each linearly independent motion In rotational systems torque replaces force (T = FR if F axis of rot.) and moment-of-inertia replaces mass Gears linearly relate the motions of multiple shafts Mechanical impedances can be reflected between shafts to simplify the calculation of TF Motors: Electromechanical systems Derived θ m (s)/e a (s) = K/s(s + α) Jump back to the time-domain to run tests and evaluate motor parameters Linearization
Mechanical Systems Mechanical components in translational and rotational forms opposing forces = applied forces One equation of motion for each linearly independent motion In rotational systems torque replaces force (T = FR if F axis of rot.) and moment-of-inertia replaces mass Gears linearly relate the motions of multiple shafts Mechanical impedances can be reflected between shafts to simplify the calculation of TF Motors: Electromechanical systems Derived θ m (s)/e a (s) = K/s(s + α) Jump back to the time-domain to run tests and evaluate motor parameters Linearization Final exam will cover only the concept and application to a simple DE
Unit 3: Time Response The poles give the form of the response, the zeros give the weights
Unit 3: Time Response The poles give the form of the response, the zeros give the weights First-order systems yield exponential responses characterized by time constant
Unit 3: Time Response The poles give the form of the response, the zeros give the weights First-order systems yield exponential responses characterized by time constant Second-order systems yield four different responses characterized by ζ and ω n
Unit 3: Time Response The poles give the form of the response, the zeros give the weights First-order systems yield exponential responses characterized by time constant Second-order systems yield four different responses characterized by ζ and ω n Response specifications: T p, %OS, and T s
Unit 3: Time Response The poles give the form of the response, the zeros give the weights First-order systems yield exponential responses characterized by time constant Second-order systems yield four different responses characterized by ζ and ω n Response specifications: T p, %OS, and T s Relationship between response specs. and pole position
Unit 3: Time Response The poles give the form of the response, the zeros give the weights First-order systems yield exponential responses characterized by time constant Second-order systems yield four different responses characterized by ζ and ω n Response specifications: T p, %OS, and T s Relationship between response specs. and pole position Additional poles or zeros
Unit 3: Time Response The poles give the form of the response, the zeros give the weights First-order systems yield exponential responses characterized by time constant Second-order systems yield four different responses characterized by ζ and ω n Response specifications: T p, %OS, and T s Relationship between response specs. and pole position Additional poles or zeros Real-axis poles or zeros far to the left have little effect
Unit 3: Time Response The poles give the form of the response, the zeros give the weights First-order systems yield exponential responses characterized by time constant Second-order systems yield four different responses characterized by ζ and ω n Response specifications: T p, %OS, and T s Relationship between response specs. and pole position Additional poles or zeros Real-axis poles or zeros far to the left have little effect A pole can cancel a nearby zero
Unit 4: Block Diagram Reduction Recognize and reduce cascade, parallel, and feedback forms
Unit 4: Block Diagram Reduction Recognize and reduce cascade, parallel, and feedback forms If none of the forms are apparent, blocks can be shift to the left or right of summing junctions and pickoff points
Unit 4: Block Diagram Reduction Recognize and reduce cascade, parallel, and feedback forms If none of the forms are apparent, blocks can be shift to the left or right of summing junctions and pickoff points Moving blocks = algebraic manipulation
Unit 4: Block Diagram Reduction Recognize and reduce cascade, parallel, and feedback forms If none of the forms are apparent, blocks can be shift to the left or right of summing junctions and pickoff points Moving blocks = algebraic manipulation Signal-flow graphs
Unit 4: Block Diagram Reduction Recognize and reduce cascade, parallel, and feedback forms If none of the forms are apparent, blocks can be shift to the left or right of summing junctions and pickoff points Moving blocks = algebraic manipulation Signal-flow graphs nodes are signals; edges are systems
Unit 5: Stability Definitions: Stability of the total response and the natural response (we focused on the natural response)
Unit 5: Stability Definitions: Stability of the total response and the natural response (we focused on the natural response) RHP: Unstable, jω: Marginally stable, LHP: Stable
Unit 5: Stability Definitions: Stability of the total response and the natural response (we focused on the natural response) RHP: Unstable, jω: Marginally stable, LHP: Stable All it takes is one RHP pole for instability (or one pair of jω poles for marginal stability)
Unit 5: Stability Definitions: Stability of the total response and the natural response (we focused on the natural response) RHP: Unstable, jω: Marginally stable, LHP: Stable All it takes is one RHP pole for instability (or one pair of jω poles for marginal stability) Characteristic coef s missing or differing in sign unstable (opposite is not true)
Unit 5: Stability Definitions: Stability of the total response and the natural response (we focused on the natural response) RHP: Unstable, jω: Marginally stable, LHP: Stable All it takes is one RHP pole for instability (or one pair of jω poles for marginal stability) Characteristic coef s missing or differing in sign unstable (opposite is not true) Routh-Hurwitz
Unit 5: Stability Definitions: Stability of the total response and the natural response (we focused on the natural response) RHP: Unstable, jω: Marginally stable, LHP: Stable All it takes is one RHP pole for instability (or one pair of jω poles for marginal stability) Characteristic coef s missing or differing in sign unstable (opposite is not true) Routh-Hurwitz Special case: zero in first column
Unit 5: Stability Definitions: Stability of the total response and the natural response (we focused on the natural response) RHP: Unstable, jω: Marginally stable, LHP: Stable All it takes is one RHP pole for instability (or one pair of jω poles for marginal stability) Characteristic coef s missing or differing in sign unstable (opposite is not true) Routh-Hurwitz Special case: zero in first column Special case: ROZ EP factor
Unit 5: Stability Definitions: Stability of the total response and the natural response (we focused on the natural response) RHP: Unstable, jω: Marginally stable, LHP: Stable All it takes is one RHP pole for instability (or one pair of jω poles for marginal stability) Characteristic coef s missing or differing in sign unstable (opposite is not true) Routh-Hurwitz Special case: zero in first column Special case: ROZ EP factor EP has symmetric roots so system is either unstable or marginally stable
Unit 5: Stability Definitions: Stability of the total response and the natural response (we focused on the natural response) RHP: Unstable, jω: Marginally stable, LHP: Stable All it takes is one RHP pole for instability (or one pair of jω poles for marginal stability) Characteristic coef s missing or differing in sign unstable (opposite is not true) Routh-Hurwitz Special case: zero in first column Special case: ROZ EP factor EP has symmetric roots so system is either unstable or marginally stable Problem: find K such that...
Unit 6: Steady-State Error For any control system: E(s) = R(s) C(s)
Unit 6: Steady-State Error For any control system: E(s) = R(s) C(s) Apply final value theorem to determine e( )
Unit 6: Steady-State Error For any control system: E(s) = R(s) C(s) Apply final value theorem to determine e( ) Unity feedback systems
Unit 6: Steady-State Error For any control system: E(s) = R(s) C(s) Apply final value theorem to determine e( ) Unity feedback systems
Unit 6: Steady-State Error For any control system: E(s) = R(s) C(s) Apply final value theorem to determine e( ) Unity feedback systems Input Type 0: e( ) Type 1: e( ) Type 2: e( ) Step, u(t) 1 1+K p 0 0 1 Ramp, tu(t) K v 0 Para., t 2 1 u(t) K a
Unit 6: Steady-State Error For any control system: E(s) = R(s) C(s) Apply final value theorem to determine e( ) Unity feedback systems Input Type 0: e( ) Type 1: e( ) Type 2: e( ) Step, u(t) 1 1+K p 0 0 1 Ramp, tu(t) K v 0 Para., t 2 1 u(t) K a Disturbances: e( ) = e R ( ) + e D ( )
Unit 7: Root Locus Techniques Vector representation of complex numbers
Unit 7: Root Locus Techniques Vector representation of complex numbers Root locus: locations of closed-loop system poles as K is varied
Unit 7: Root Locus Techniques Vector representation of complex numbers Root locus: locations of closed-loop system poles as K is varied Properties of the RL
Unit 7: Root Locus Techniques Vector representation of complex numbers Root locus: locations of closed-loop system poles as K is varied Properties of the RL If KG(s)H(s) = (2k + 1)180 o we can find a K to satisfy KG(s)H(s) = 1
Unit 7: Root Locus Techniques Vector representation of complex numbers Root locus: locations of closed-loop system poles as K is varied Properties of the RL If KG(s)H(s) = (2k + 1)180 o we can find a K to satisfy KG(s)H(s) = 1 Sketching rules
Unit 7: Root Locus Techniques Vector representation of complex numbers Root locus: locations of closed-loop system poles as K is varied Properties of the RL If KG(s)H(s) = (2k + 1)180 o we can find a K to satisfy KG(s)H(s) = 1 Sketching rules Refinements: breakaway and break-in points, jω crossings, angles of departure and arrival
Unit 7: Root Locus Techniques Vector representation of complex numbers Root locus: locations of closed-loop system poles as K is varied Properties of the RL If KG(s)H(s) = (2k + 1)180 o we can find a K to satisfy KG(s)H(s) = 1 Sketching rules Refinements: breakaway and break-in points, jω crossings, angles of departure and arrival Search procedure required to find points with particular spec s
Unit 7: Root Locus Techniques Vector representation of complex numbers Root locus: locations of closed-loop system poles as K is varied Properties of the RL If KG(s)H(s) = (2k + 1)180 o we can find a K to satisfy KG(s)H(s) = 1 Sketching rules Refinements: breakaway and break-in points, jω crossings, angles of departure and arrival Search procedure required to find points with particular spec s Positive feedback requires changes to the RL definition and sketching rules
Unit 8: Design via Root Locus First check acceptable operating point on uncompensated RL
Unit 8: Design via Root Locus First check acceptable operating point on uncompensated RL PI compensation: increase system type while maintaining transient resp. G c (s) = K(s + z c) s Choose z c as a small number; Requires active amplification
Unit 8: Design via Root Locus First check acceptable operating point on uncompensated RL PI compensation: increase system type while maintaining transient resp. G c (s) = K(s + z c) s Choose z c as a small number; Requires active amplification Lag compensation: increase static error constant (which reduces e( ) G c (s) = K(s + z c) s + p c Choose p c as a small number and adjust z c accordingly
Unit 8: Design via Root Locus First check acceptable operating point on uncompensated RL PI compensation: increase system type while maintaining transient resp. G c (s) = K(s + z c) s Choose z c as a small number; Requires active amplification Lag compensation: increase static error constant (which reduces e( ) G c (s) = K(s + z c) s + p c Choose p c as a small number and adjust z c accordingly PD compensation: Adjust transient response G c (s) = K(s + z c ) Place z c to move RL to intersect desired operating point; Requires active amplification
Unit 8: Design via Root Locus First check acceptable operating point on uncompensated RL PI compensation: increase system type while maintaining transient resp. G c (s) = K(s + z c) s Choose z c as a small number; Requires active amplification Lag compensation: increase static error constant (which reduces e( ) G c (s) = K(s + z c) s + p c Choose p c as a small number and adjust z c accordingly PD compensation: Adjust transient response G c (s) = K(s + z c ) Place z c to move RL to intersect desired operating point; Requires active amplification All of our design techniques rely on 2 nd order approx.. Verify approx. validity and simulate
PID: Design for transient response, then e( )
PID: Design for transient response, then e( ) Analog PID implemented via op-amp
PID: Design for transient response, then e( ) Analog PID implemented via op-amp Digital PID can be implemented in software (or digital hardware)
PID: Design for transient response, then e( ) Analog PID implemented via op-amp Digital PID can be implemented in software (or digital hardware) PID tuning: Strategies to apply when system model is unknown
PID: Design for transient response, then e( ) Analog PID implemented via op-amp Digital PID can be implemented in software (or digital hardware) PID tuning: Strategies to apply when system model is unknown Ziegler-Nichols (rules of thumb)
PID: Design for transient response, then e( ) Analog PID implemented via op-amp Digital PID can be implemented in software (or digital hardware) PID tuning: Strategies to apply when system model is unknown Ziegler-Nichols (rules of thumb) Method 1: Unit-step response is S-shaped
PID: Design for transient response, then e( ) Analog PID implemented via op-amp Digital PID can be implemented in software (or digital hardware) PID tuning: Strategies to apply when system model is unknown Ziegler-Nichols (rules of thumb) Method 1: Unit-step response is S-shaped Method 2: System appears to involve integration and/or underdamped poles
PID: Design for transient response, then e( ) Analog PID implemented via op-amp Digital PID can be implemented in software (or digital hardware) PID tuning: Strategies to apply when system model is unknown Ziegler-Nichols (rules of thumb) Method 1: Unit-step response is S-shaped Method 2: System appears to involve integration and/or underdamped poles Computational search