Nonlinear Robust Control Design For System Of IPMC Artificial Muscles

The ionic polymer metal composite(IPMC), also called artificial muscle, belongs to the category electroactive polymers(EAP). Because IPMCs have the following characteristics: large strain and stress induced electrically, light in weight, small and simple mechanisms, small electric consumption, and low drive voltage, which have been widely used in the developments of miniature robots and biomedical devices as a Driver. In order to achieve precise action in the control process, we can control the offset of artificial muscle to achieve this requirement. Therefor, we design the control system which can control the exact position of artificial muscle. In the process of the modeling, there exist model uncertainties, external disturbances and control input constraints under low voltage condition, these will affect the control accuracy. For the above reasons, it is difficult to obtain the accurate position control with the common control strategy. So the traditional methods are hardly applied into the control of IPMC. Therefor, it’s a key point that choose a suitable method to guarantee the robust stability of control system of IPMC with uncertainties, which will make IPMC more useful.In this paper, a robust nonlinear tracking control design for an ionic polymer metal composite(IPMC) is proposed. In order to control the IPMCs’ position precisely, first, the system with uncertainties and without uncertainties is designed based operator theory and the robust of system is guaranteed. Second, PI control is proposed to track the stabilized system, the parameters of tracking controller are optimized by two methods. The first optimal control parameters(Kp, Ki) is investigated by using MATLAB System Identification toolbox and and Response Optimization toolbox. This method is simply, but its tracking control is not perfect. Therefore, artificial bee algorithm is proposed to obtain the suitable parameters(Kp, Ki). Finally, the effectiveness of the second proposed method system is better by simulation results.