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TUTORIAL on LOGIC-BASED CONTROL Part I: SWITCHED CONTROL SYSTEMS Daniel Liberzon Coordinated Science Laboratory and Dept. of Electrical & Computer Eng., Univ. of Illinois at Urbana-Champaign MED ’02, Lisbon
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OUTLINE Switched Control Systems Stability of Switched Systems Questions, Break
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OUTLINE Switched Control Systems Stability of Switched Systems Questions, Break
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SWITCHED and HYBRID SYSTEMS Switching can be: State-dependent or Time-dependent Hybrid systems: interaction of continuous and discrete dynamics Switched systems: continuous systems with discrete switchings emphasis on properties of continuous state and is a switching signal where is a family of systems Autonomous or Controlled
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SWITCHING CONTROL Classical continuous feedback paradigm: u y P C u y P Plant: But logical decisions are often necessary: The closed-loop system is hybrid u y C1C1 C2C2 l o g i c P
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REASONS for SWITCHING Nature of the control problem Sensor or actuator limitations Large modeling uncertainty Combinations of the above
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REASONS for SWITCHING Nature of the control problem Sensor or actuator limitations Large modeling uncertainty Combinations of the above
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PARKING PROBLEM Nonholonomic constraint: wheels do not slip
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OBSTRUCTION to STABILIZATION Solution: move away first ?
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REASONS for SWITCHING Nature of the control problem Sensor or actuator limitations Large modeling uncertainty Combinations of the above
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OUTPUT FEEDBACK switched system Example: harmonic oscillator
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QUANTIZED FEEDBACK PLANT QUANTIZER CONTROLLER u x q(x) x sensitivity M values
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OBSTRUCTION to STABILIZATION Assume: fixed Asymptotic stabilization is impossible
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MOTIVATING EXAMPLES 1. Temperature sensor normal too low too high 2. Camera with zoom Tracking a golf ball 3. Coding and decoding
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VARYING the SENSITIVITY zoom out zoom in Why switch ? More realistic Easier to design and analyze Robust to time delays
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LINEAR SYSTEMS is GAS:Assume: Along solutions of quantization error Then can achieve GAS we have for some s.t.
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SWITCHING POLICY We have level sets of V.
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NONLINEAR SYSTEMS is GAS: Assume: s.t. Need: along solutions of wh er e is pos. def., increasing, and unbounded (this is input-to-state stability wrt measurement error) Then can achieve GAS quantization error
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EXTENSIONS and APPLICATIONS Arbitrary quantization regions Active probing for information Output and input quantization Relaxing the assumptions Performance-based design Application to visual servoing
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REASONS for SWITCHING Nature of the control problem Sensor or actuator limitations Large modeling uncertainty Combinations of the above
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MODEL UNCERTAINTY parametric uncertainty unmodeled dynamics Also, noise and disturbances Adaptive control (continuous tuning) vs. supervisory control (switching)
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SUPERVISORY CONTROL switching signal Plant Supervisor Controller 2 Controller m Controller 1 u1u1 u2u2 umum y u...... candidate controllers......
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STABILITY of SWITCHED SYSTEMS switching stops in finite time Stable if: unstable slow switching (on the average) “locally confined” switching common Lyapunov function
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REASONS for SWITCHING Nature of the control problem Sensor or actuator limitations Large modeling uncertainty Combinations of the above
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PARKING PROBLEM under UNCERTAINTY Unknown parameters correspond to the radius of rear wheels and distance between them p 1 p 2 p 1
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SIMULATION
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OUTLINE Switched Control Systems Stability of Switched Systems Questions, Break
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OUTLINE Switched Control Systems Stability of Switched Systems Questions, Break
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TWO BASIC PROBLEMS Stability for arbitrary switching Stability for constrained switching
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UNIFORM STABILITY is a piecewise constant switching signal where is a family of GAS systems Want GUAS w.r.t. GUES: :
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COMMON LYAPUNOV FUNCTION is GUAS if and only if s.t. is not enough Example: if Usually we take P compact and f p continuous Corollary: is GAS
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SWITCHED LINEAR SYSTEMS LAS for every GUES but not necessarily quadratic common Lyapunov function
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COMMUTING STABLE MATRICES => GUES quadratic common Lyap fcn: … t …
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LIE ALGEBRAS and STABILITY Lie algebra: Lie bracket: g is nilpotent if s.t. g is solvable if s.t.
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SOLVABLE LIE ALGEBRA => GUES Lie’s Theorem: triangular form is solvable quadratic common Lyap fcn: D diagonal
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SOLVABLE + COMPACT => GUES Levi decomposition: radical (max solvable ideal) is compact => GUES quadratic common Lyap fcn
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SOLVABLE + NONCOMPACT => GUES is not compact a set of stable generators for that gives GUES a set of stable generators for that leads to an unstable system Lie algebra doesn’t provide enough information
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NONLINEAR SYSTEMS Commuting systems => GUAS Linearization ???
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REMARKS on LIE-ALGEBRAIC CRITERIA Checkable conditions In terms of the original data Independent of representation Not robust to small perturbations
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SYSTEMS with SPECIAL STRUCTURE Triangular systems Linear => GUES Nonlinear: need ISS conditions Passive: => GUAS Small gain: => GUES 2D systems convex combs of stable quadratic common Lyap fcn Feedback systems u y -
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MULTIPLE LYAPUNOV FUNCTIONS GAS respective Lyapunov functions t is GAS Very useful for analysis of state-dependent switching
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MULTIPLE LYAPUNOV FUNCTIONS t is GAS decreasing sequence
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DWELL TIME The switching times satisfy dwell time GES respective Lyapunov functions t Need: must be
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AVERAGE DWELL TIME # of switches on average dwell time dwell time: cannot switch twice if no switching: cannot switch if => is GAS if
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SWITCHED LINEAR SYSTEMS GUES over all with large enough Finite induced norms for The case when some subsystems are unstable
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STABILIZATION by SWITCHING both unstable Assume: stable for some So for each : either or
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UNSTABLE CONVEX COMBINATIONS Can also use multiple Lyapunov functions LMIs
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