Indirect Adaptive Neural Network Dynamic Surface Control for Uncertain Time-delay Electrostatic Micro-actuator with State Constraint

This study presents tracking control problem for a class of uncertain time-delay electrostatic micro-actuator systems which can be actively driven bidirectionally. By introducing indirect adaptive neural network (NN) algorithm into dynamic surface control (DSC) framework, some assumptions, which the uncertain time-delays must be satisfied in previous works, are removed. Also, by using the tangent barrier function, the proposed controller can ensure the system state tracks a reference trajectory and keeps in a desired region to prevent contact between the movable and fixed electrodes, while not violating the constraint during the whole dynamic response process. In addition, simulation results show that the effectiveness of the proposed results.