Intelligent Switching Surface for Variable Structure Adaptive Model Following Control

This paper presents the application of genetic algorithms (GAs) to the design of an intelligent switching surface for variable structure adaptive model following controller for higher order systems with unmodelled dynamics/parameter variations. The conventional approach for the design of switching surface by pole placement method often lead to large value of control signals. A method for obtaining an intelligent switching surface in a computationally efficient manner is proposed in this paper. The proposed method make use of GAs to evolve a switching surface which ensures minimum disruption of the poles when variations/uncertainties act on the system. If minimum disruption of the poles is not ensured, higher control signal will be required to maintain sliding mode motion. The proposed methodology is applied to a practical system namely a flexible one-link manipulator and the results obtained are compared to the results obtained by applying the conventional design. The comparison reveals the efficacy of the proposed method