Identification and adaptive neural network control of a DC motor system with dead-zone characteristics

► A Wiener-type neural network is proposed to identify the DC motor with dead-zone characteristics. ► A PID-type neural network is then used to control and compensate for the dead-zone characteristics. ► An adaptive control approach based on the neural networks is presented to control a DC motor system with DZC. ► The stability and convergence analysis are conducted using the Lyapunov theorem. ► Experiments on the DC motor system demonstrated accurate identification and good compensation for dead-zone characteristics.