Sliding mode control of intramuscular functional electrical stimulation using fuzzy neural network with terminal sliding mode learning

In this paper, we propose a robust control strategy for control of ankle joint angle using intramuscular functional electrical stimulation (FES). Although, several robust control strategies were proposed for FES utilizing surface electrodes. However, developing a robust control strategy for FES utilizing the intramuscular electrodes is an open problem. The method is based on sliding mode control (SMC) with exponential reaching law and fuzzy neural network (FNN). A learning algorithm based on terminal sliding mode is proposed for estimation of the FNN parameter. The experiments were conducted on three rats. Experimental results show that the proposed strategy provides excellent tracking control with fast convergence. The average of tracking error over all trials of experiments and all rats is 3.6°±0.16.