DocumentCode :
2294192
Title :
Quasilinear quadratic Gaussian control for systems with saturating actuators and sensors
Author :
Gökçek, Cevat
Author_Institution :
Dept. of Mech. Eng., Michigan State Univ., East Lansing, MI
fYear :
2006
fDate :
14-16 June 2006
Abstract :
An extension of the linear quadratic Gaussian control method to systems with saturating actuators and sensors is obtained. The development is based on the method of stochastic linearization, whereby the actuator and sensor saturation characteristics are replaced by their equivalent gains. Using the stochastically linearized system, a quasilinear quadratic Gaussian optimal control problem is formulated and a solution to the problem is derived by employing the Lagrange multiplier method. The solution obtained is given in terms of standard Riccati and Lyapunov equations coupled with four transcendental equations that characterize the variance of the signals at the saturation inputs and the Lagrange multipliers associated with the constrained minimization problem. Under standard stabilizability and detectability conditions, an iterative algorithm is developed to find the solution of these equations. It is shown that proposed method is a proper extension of the linear quadratic Gaussian control in the sense that these equations reduce to their standard linear quadratic Gaussian counterparts when the saturation is removed. Additional analysis results are also developed for quasilinear systems. The developed synthesis method is illustrated by an example
Keywords :
Lyapunov methods; Riccati equations; linear quadratic Gaussian control; linearisation techniques; minimisation; optimal control; stochastic systems; Lagrange multiplier method; Lyapunov equations; Riccati equations; constrained minimization problem; equivalent gains; iterative algorithm; quasilinear quadratic Gaussian optimal control; saturating actuators; saturating sensors; stochastic linearization; transcendental equations; Control systems; Hydraulic actuators; Iterative algorithms; Lagrangian functions; Optimal control; Riccati equations; Sensor phenomena and characterization; Sensor systems; Standards development; Stochastic processes;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
American Control Conference, 2006
Conference_Location :
Minneapolis, MN
Print_ISBN :
1-4244-0209-3
Electronic_ISBN :
1-4244-0209-3
Type :
conf
DOI :
10.1109/ACC.2006.1657434
Filename :
1657434
Link To Document :
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