Two different approaches have been actively studied to maintain performance in the presence of parametric uncertainties: adaptive control and robust control. The basic philosophy of adaptive controller is that incorporates some sort of parameter estimation and adaptive controller can learn from experiences in the sense that parameters are changed. Some of the adaptive control laws introduced by...

In this paper, an optimal adaptive sliding mode controller is proposed for anti-synchronization of two identical hyperchaotic systems. We use hyperchaotic complex T-system for master and slave systems with unknown parameters in the slave system. To construct the optimal adaptive sliding mode controller, first a simple sliding surface is designed. Then, the optimal adaptive sliding mode controll...

In this article, a new combined adaptive method is used for a two-link robot. One of the advantages of proposed controller is that it does not depend on the exact parameters such as joints weight. Also the controller can reach itself to real parameters. In many applications of robots in industry the weight and moment of inertia are changed intentionally and it would not be an easy task for the ...

The “Adaptive Slotine-Li Robot Controller (ASLRC)” of the nineties of the past century was designed by a sophisticated process based on the use of Lyapunov’s 2nd method. In the possession of the exact analytical form of the system model it generally can achieve global asymptotic stability by learning the system’s exact dynamic parameters. However, it is not robust to friction effects and unknow...

model predictive controller is widely used in industrial plants. uncertainty is one of the critical issues in real systems. in this paper, the direct adaptive simplified model predictive control (smpc) is proposed for unknown or time varying plants with uncertainties. by estimating the plant step response in each sample, the controller is designed and the controller coefficients are directly ca...

The problem of designing a robust adaptive control for nonlinear systems with uncertain time-varying parameters is addressed. The upper bound of uncertain parameters, considered even in control coefficients, are not required to be known. An adaptive tracking controller is presented and, using the Lyapunov theory, the closed-loop stability and tracking error convergence is shown. In order to imp...