Title :
Neural adaptive regulation of unknown nonlinear dynamical systems
Author :
Rovithakis, George A. ; Christodoulou, Manolis A.
Author_Institution :
Dept. of Electron. & Comput. Eng., Tech. Univ. of Crete, Chania, Greece
fDate :
9/1/1997 12:00:00 AM
Abstract :
With this paper we extend our previous work on the subject, by including the case where the number of control inputs is different from the number of states which is frequently faced in control engineering problems. Uniform ultimate boundedness of the state and uniform boundedness of all other signals in the closed loop is guaranteed. Robustness of our algorithm due to the presence of a modeling error term which has linear growth with unknown growth coefficient is also established. Finally, the applicability of our control scheme is highlighted via simulation results
Keywords :
adaptive control; closed loop systems; neurocontrollers; nonlinear dynamical systems; robust control; adaptive regulation; boundedness; closed loop; modeling error term; neural networks; nonlinear dynamical systems; robustness; Adaptive control; Control systems; Neural networks; Nonlinear control systems; Nonlinear dynamical systems; Programmable control; Robust control; Robust stability; Robustness; Sliding mode control;
Journal_Title :
Systems, Man, and Cybernetics, Part B: Cybernetics, IEEE Transactions on
DOI :
10.1109/3477.623234
