Adaptive nonsingular terminal sliding mode controller for micro/nanopositioning systems driven by linear piezoelectric ceramic motors

In the field of nanotechnology, there is a growing demand to provide precision control and manipulation of devices with the ability to interact with complex and unstructured environments at micro/nano-scale. As a result, ultrahigh-precision positioning stages have been turned into a key requirement of nanotechnology. In this paper, linear piezoelectric ceramic motors (LPCMs) are adopted to drive micro/nanopositioning stages since they have the ability to achieve high precision in addition to being versatile to be implemented over a wide range of applications. In the establishment of a control scheme for such manipulation systems, the presence of friction, parameter uncertainties, and external disturbances prevent the systems from providing the desired positioning accuracy. The work in this paper focuses on the development of a control framework that addresses these issues as it uses the nonsingular terminal sliding mode technique for the precise position tracking problem of an LPCM-driven positioning stage with friction, uncertain parameters, and external disturbances. The developed control algorithm exhibits the following two attractive features. First, upper bounds of system uncertainties/perturbations are adaptively estimated in the proposed controller; thus, prior knowledge about uncertainty/disturbance bounds is not necessary. Second, the discontinuous signum function is transferred to the time derivative of the control input and the continuous control signal is obtained after integration; consequently, the chattering phenomenon, which presents a major handicap to the implementation of conventional sliding mode control in real applications, is alleviated without deteriorating the robustness of the system. The stability of the controlled system is analyzed, and the convergence of the position tracking error to zero is analytically proven. The proposed control strategy is experimentally validated and compared to the existing control approaches.