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In this paper, a multi-model based hybrid sliding mode control (HSMC) system is proposed for trajectory tracking control problem of robotic systems. The idea of introducing multi-model/controller based HSMC design is to reduce the level of parametric uncertainty in order to reduce the controller gains that reduces the control effort. The key idea is to allow the parameter estimate of classical sliding mode control (SMC)design to be reset into a model that best approximates the plant among a finite set of candidate models. For this purpose, we uniformly distribute the compact set of unknown parameters into a finite number of smaller compact subsets. Then we design a family of candidate controllers for each of these smaller subsets. The derivative of the Lyapunov function candidate is used as a resetting criterion to identify a candidate model that closely approximates the plant at each instant of time. The proposed method is evaluated on a 2-DOF robot manipulator to demonstrate the effectiveness of the theoretical development.