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Event Detail Information

DCL Lecture Series: Prof. Semyon Meerkov, Quasilinear Control: Performance Analysis and Design of Feedback Systems with Nonlinear Actuators and Sensors

Speaker Professor Semyon M. Meerkov, Electrical Engineering & Computer Science, University of Michigan
Date Dec 5, 2012
Time 3:00 pm - 4:00 pm  
Location CSL Auditorium (B02 CSL)
Sponsor Decision and Control Laboratory, Coordinated Science Laboratory
Contact Angie Ellis
Phone 217-300-1910
Event type seminar
Views 1022
Originating Calendar CSL Decision and Control Group

Decision and Control Lecture Series

Decision and Control Laboratory, Coordinated Science Laboratory

Quasilinear Control: Performance Analysis and Design of Feedback Systems with Nonlinear Actuators and Sensors

Professor Semyon M. Meerkov

Department of Electrical Engineering and Computer Science

University of Michigan

Wednesday, December 5, 2012

3:00 p.m. to 4:00 p.m.

B02 Auditorium CSL

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Abstract

Quasilinear Control (QLC) is a set of methods for performance analysis and design of linear plant/nonlinear instrumentation (LPNI) feedback systems. The approach of QLC is based on the method of stochastic linearization, which reduces the nonlinearities of actuators and sensors to quasilinear gains. Unlike the usual, Jacobian linearization, stochastic linearization is global. The price to pay is that the quasilinear gain depends not on the operating point but on all functional blocks and exogenous signals of the system. Using this approximation, QLC extends most methods of linear control to LPNI systems.  These include system type, error coefficients, root locus, LQR/LQG, H∞, LMI, etc. The resulting equations consist of the usual control-theoretic relationships (e.g., Lyapunov and Ricatti equations) coupled with transcendental equations, which account for the quasilinear gains; a bisection algorithm for solving these equations is provided. In addition, QLC addresses LPNI-specific problems: instrumented LQR/LQG, where the optimal controller is designed simultaneously with the optimal actuator and sensor, and partial and complete performance recovery, where the degradation of linear performance is either contained or completely eliminated. In this talk, the method of stochastic linearization and the theory of QLC will be overviewed, and the topics of saturated root locus, instrumented LQR/LQG and performance recovery will be discussed in some details.

Biography

Semyon M. Meerkov received his MSEE degree from the Polytechnic of Kharkov, Ukraine, in 1962 and Ph.D. in Systems Science from the Institute of Control Sciences, Moscow, Russia, in 1966. He was with the Institute of Control Sciences until 1977. From 1979 to 1984 he was with the Department of Electrical and Computer Engineering, Illinois Institute of Technology, Chicago, IL. Since 1984 he has been a Professor at the Department of Electrical Engineering and Computer Science of the University of Michigan, Ann Arbor, MI. He has held visiting positions at UCLA (1978-1979), Stanford (1991), Technion, Israel (1997-1998 and 2008) and Tsinghua, China (2008). He was the Editor-in-Chief of Mathematical Problems in Engineering, Department Editor for Manufacturing Systems of IIE Transactions and Associate Editor of several other journals. His current research interests are in Systems and Control (with applications to production systems and communication networks) and in Theory of Rational Behavior (with applications to pay-for-performance and resilient monitoring and control).

PLEASE JOIN US FOR COOKIES AND COFFEE PRIOR TO THE SEMINAR IN ROOM 154 CSL AT 2:30PM