الفهرس 
Off-line tuning of adaptive sliding mode Controllers using particle swarm Optimization
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Abstract
In the presented work, a modified adaptive sliding mode control (ASMC) for nonlinear systems is presented. The proposed scheme combines the capabilities of the conventional sliding mode controllers (SMC) and those of the adaptive controllers in dealing with uncertainties. At the same time, it overcomes the main problems of them such as the problems of chattering and the required priori knowledge of the bounds of uncertainties that exist in (SMC) controllers as well as the problems that are common in adaptive controllers such as parameter drifting. Particle swarm optimization (PSO) algorithm is introduced to easily determine a large number of parameters and an adaptation gain to tune such a controller. The new scheme shows better accuracy, more stability and robustness and faster response as compared to other techniques applied on an inverted pendulum and a two-degrees-of-freedom (DOF) robot manipulator