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CONTROL with LIMITED INFORMATION

Explore constraint in control, robustness to measurement errors, dynamic quantization, active probing, and related research on robust control design. Research conducted at Coordinated Science Laboratory, Univ. of Illinois.

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CONTROL with LIMITED INFORMATION

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  1. CONTROL with LIMITED INFORMATION Daniel Liberzon Coordinated Science Laboratory and Dept. of Electrical & Computer Eng., Univ. of Illinois at Urbana-Champaign CDC ’02

  2. CONSTRAINED CONTROL Constraint: – given control commands 0 Control objectives: stabilize to 0 or to a desired set containing 0, exit Dthrough a specified facet, etc.

  3. LIMITED INFORMATION SCENARIO – partition of D – points in D, Quantizer/encoder: for Control:

  4. Issue: error Need to be robust w.r.t. measurement errors PERTURBATION APPROACH • Design ignoring constraint • View as approximation • Prove that this still solves the problem

  5. is asymptotically stable 9 Lyapunov function LINEAR SYSTEMS

  6. LINEAR SYSTEMS (continued) To have ultimate bound we need

  7. After ultimate bound is achieved we can recompute partition for smaller region DYNAMIC QUANTIZATION zoom in zoom out Zooming in and out, we recover global asymptotic stability

  8. ACTIVE PROBING for INFORMATION . . . . . . . . . . Can achieve GAS if we recompute often enough Related work: Wong-Brockett, Tatikonda-Mitter, Nair-Evans, Savkin-Petersen, Hespanha

  9. Robust control design • Facility location algorithms • Performance (nonstandard criteria) • Applications RESEARCH DIRECTIONS

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