Hybrid control method for hysteresis non-linearity of magnetically controlled shape memory actuator

In order to eliminate the hysteresis non-linearity between the input and output of the magnetically controlled shape memory alloy (MSMA) actuator and improve the control accuracy, a hybrid control method is proposed. The proposed hybrid control method consists of two parts: a hysteresis inverse model feedforward controller and a neural network feedback controller. According to the hysteresis non-linearity between the input and output of MSMA actuator, a double sigmoid function (double S function) and a four layer feedforward neural network are used to establish the hysteresis model of MSMA actuator. With the same method, the hysteresis inverse model is established. A three layer feedforward neural network is used in the feedback controller. The experimental results show that the proposed control method can effectively improve the output accuracy of the MSMA actuator.