BMI-based stability and performance design for fuzzy-model-based control systems subject to parameter uncertainties.
This paper presents the stability and performance design of a fuzzy-model-based control system subject to parameter uncertainties. A nonlinear controller with a favorable characteristic to relax the stability conditions is proposed to drive the system states of the nonlinear plant to follow those of a stable reference model. Stability and performance conditions in terms of bilinear matrix inequalities (BMIs) will be derived based on a Lyapunov-based approach. A combined genetic algorithm and convex programming technique process will be developed to solve the solution to the BMIs. An application example will be given to illustrate the merits of the proposed approach.
Lam
H K
HK
Division of Engineering, King's College London, WC2R 2LS London, UK. hak-keung.lam@kcl.ac.uk
Seneviratne
Lakmal D
LD
D000465:Algorithms; D001185:Artificial Intelligence; D003198:Computer Simulation; D005246:Feedback; D017143:Fuzzy Logic; D015233:Models, Statistical; D010363:Pattern Recognition, Automated / Q000379:methods*; D013598:Systems Theory