Aiming control: design of residence probability controllers

Author

Kim, S. ; Meerkov, S.M. ; Runolfsson, T.

Author_Institution

Dept. of Electr. Eng. & Comput. Sci., Michigan Univ., Ann Arbor, MI, USA

fYear

1990

fDate

5-7 Dec 1990

Firstpage

2139

Abstract

Methods for the design of residence probability (RP) controllers for linear stochastic systems are developed. Comparisons with H ₂- and H_∞-optimal designs are given. In particular, it is shown that in the so-called strong RP-controllability case, every RP-optimal controller is H₂- and H_∞-optimal; the converse is not true. In the weak RP-controllability case, the H_∞-optimal controllers result in RP arbitrarily close to 0. The design of gains for RP-controllers is not more complex than that in the linear quadratic Gaussian (LQG) method: it only involves solving a Riccati equation. However, unlike the LQG, RP-controllers require the selection of the initial set D₀ as well; this is accomplished by solving a Lyapunov equation

Keywords

Lyapunov methods; control system synthesis; controllability; optimal control; probability; stochastic systems; Lyapunov equation; Riccati equation; controllability; design; linear stochastic systems; optimal control; residence probability controllers; Closed loop systems; Control systems; Controllability; Design methodology; Differential equations; Feedback loop; Force control; Force feedback; Indium tin oxide; Stochastic systems;

fLanguage

English

Publisher

ieee

Conference_Titel

Decision and Control, 1990., Proceedings of the 29th IEEE Conference on

Conference_Location

Honolulu, HI

Type

conf

DOI

10.1109/CDC.1990.204003

Filename

204003