Title :
Nonlinear adaptive control using networks of piecewise linear approximators
Author :
Choi, Jin Young ; Farrell, Jay A.
Author_Institution :
Dept. of Electr. Eng., Seoul Nat. Univ., South Korea
fDate :
3/1/2000 12:00:00 AM
Abstract :
Presents a stable nonparametric adaptive control approach using a piecewise local linear approximator. The continuous piecewise linear approximator is developed and its universal approximation capability is proved. The controller architecture is based on adaptive feedback linearization plus sliding mode control. A time varying activation region is introduced for efficient self-organization of the approximator during operation. We modify the adaptive control approach for piecewise linear approximation and self-organizing structures. In addition, we provide analyses of asymptotic stability of the tracking error and parameter convergence for the proposed adaptive control scheme with the online self-organizing structure. The method with a deadzone is also discussed to prevent a high-frequency input which might excite the unmodeled dynamics in practical applications. The application of the piecewise linear adaptive control method is demonstrated by a computational simulation
Keywords :
adaptive control; approximation theory; asymptotic stability; convergence; feedback; neurocontrollers; nonlinear control systems; piecewise linear techniques; self-adjusting systems; variable structure systems; adaptive feedback linearization; asymptotic stability; controller architecture; deadzone; nonlinear adaptive control; parameter convergence; piecewise linear approximators; self-organizing structures; sliding mode control; stable nonparametric adaptive control; time varying activation region; tracking error; universal approximation capability; unmodeled dynamics; Adaptive control; Asymptotic stability; Computational modeling; Convergence; Error correction; Linear feedback control systems; Piecewise linear approximation; Piecewise linear techniques; Programmable control; Sliding mode control;
Journal_Title :
Neural Networks, IEEE Transactions on