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Characteristic model–based adaptive controller with discrete extended state observer for servo systems

Inertia variations and torque disturbances, most often considered as two of the major uncertainties in servo systems, highly affect the control performance. This article presents a characteristic model–based adaptive controller in the presence of large-range load inertia variations. A discrete-time characteristic model of the servo system, which has more advantages in describing time-varying dynamics, is established. The parameters of characteristic model are identified by a recursive least squares algorithm. To restrain the identification error and load torque disturbances, a discrete extended state observer is newly designed for the discrete-time system. Both the convergence of discrete extended state observer and the stability of closed-loop system are verified by the Lyapunov theory. Finally, simulation and experimental results demonstrate that the proposed controller provides better performance than the fuzzy proportional integral controller in terms of adaptability and robustness.