Adaptation of the Switching Hyperplanes in Cautious Sliding Control with Application to Mechanical Systems

Abstract

Sliding control is known to have excellent robustness properties against parametric uncertainty and non-linearities. However, if parameter changes are bigger than some limits, the sliding mode is destroyed and a bad transient behaviour is obtained.In this paper, a new adaptive sliding control is proposed. The switching hyperplane is adapted in order to ensure the existence of sliding mode in the presence of large parameter changes of the plant characteristics. A real-time identification is used to estimate the system parameters. The uncertainty given by ellipsoids is used to design a “cautious” switching law. The uncertainty is large in the beginning of identification or during fast parameter changes. In this case the control is made cautious and the system response is slow. The parametric uncertainty decreases with time and the control becomes performant and fast. This concept can be applied to any learning process.The method is applied to the position control of a DC motor. A fast response without overshoot is obtained. This performance is achieved in the presence of large changes of the moment of inertia of load. Simulation results are given in the paper. The application of the method to robotics is discussed.