Title :
Intelligent twisting sliding mode controller using neural network for pneumatic artificial muscles robot arm
Author :
Boudoua, S. ; Hamerlain, M. ; Hamerlain, F.
Author_Institution :
Centre de Dev. des Technol. Av. (CDTA), Algiers, Algeria
Abstract :
In this note we present a novel intelligent twisting sliding mode controller using neural network, achieving chatter reduction for the control of pneumatic artificial muscles robot arm. The system is highly non-linear and somehow difficult to model therefore resorting to robust control is required. Thanks to their property as universal approximators, in this work a two layer NN with on line adaptive learning law is used to reconstruct unknown and unmodeled robot dynamics, and the realisation of a two sliding mode is achieved through the design of a nonlinear sliding surface. The stability of the overall system is guaranteed by lyapunov method. Experimental results are presented and discussed.
Keywords :
Lyapunov methods; adaptive control; approximation theory; learning systems; manipulator dynamics; neurocontrollers; nonlinear control systems; pneumatic systems; robust control; variable structure systems; Lyapunov method; chatter reduction; intelligent twisting sliding mode controller; neural network; nonlinear sliding surface design; online adaptive learning law; pneumatic artificial muscles robot arm; robot dynamics; robust control; universal approximators; Artificial neural networks; Performance evaluation; Robots; Tin;
Conference_Titel :
Recent Advances in Sliding Modes (RASM), 2015 International Workshop on
Conference_Location :
Istanbul
DOI :
10.1109/RASM.2015.7154592