EECS500 Spring 2014 Department Seminar

Per-Olof Gutman
Constrained control of uncertain linear time-invariant systems: an interpolation based approach
Technion-Israel Institute of Technology
Bingham 204
11:30am - 12:30pm
February 17, 2014

In this talk, a novel approach to control uncertain discrete-time linear time-invariant systems with polytopic state and control constraints is proposed. The main idea is to use interpolation. The control law has an implicit and explicit form. In the implicit form, at each time instant, at most two linear programming problems are solved on-line. In the explicit form, the control law is given as a piecewise a-ne and continuous function of the state. The design method can be seen as a computationally favorable alternative to optimization-based control schemes such as Model Predictive Control. Proofs of recursive feasibility and asymptotic stability are given. Several simulations demonstrate the performance, also in comparison with MPC. Ext-ensions include output feedback, LPV and time-varying systems, and ellipsoidal constraint sets.

Main reference:  Hoai-Nam Nguyen, Constrained control of uncertain, time-varying systems: an interpolation based approach, accepted for publication as a Springer book, Lecture Notes in Control and Information Sciences, 2014.


B.Sc. 1973 (Lund, Sweden); M.Sc. 1977 (UCLA); Ph.D. 1982 (Lund)
After completing his doctorate in Automatic Control, Gutman spent a post-doctoral year with the Electrical Engineering Department, Technion, working on the control theory of systems with state and control constraints. During 1984-1990 he was with El-Op Electro-Optics Industries Ltd, Rehovot, analyzing and designing tank fire control systems, control systems for stabilized platforms, and other electro-optical systems. After joining the Agricultural Engineering Department, his research has dealt with control problems relevant to agricultural systems, in particular autonomous systems in agriculture. He has contributed to algorithms for automatic sorting (Ben-Hanan et al. 1992; Gutman et al. 1994) and is working on the modeling and optimal control of greenhouses (Gutman et al. 1993; Ioslovich et al. 1995; Ioslovich et al. 1996; Linker et al. 1996). For mechanical systems in agriculture operating in a harsh environment, Gutman is developing new models and robust and adaptive control design methods (Nordin et al 1997; Baril and Gutman 1997). A recent contribution to control systems theory is presented in Rotstein et al. (1997). Research interests: Greenhouse control, Autonomous systems in agriculture, Robust and adaptive control design methods.