To overcome the problems of structural parametric uncertainty and cable transmission model complexity, a nonlinear controller based on time-delay estimation and fuzzy self-tuning is proposed. The unknown dynamics and disturbances are estimated by time delaying the state of motion immediately before. The control gains are self-tuned by a fuzzy controller, which can reduce the errors caused by system’s uncertainties and external disturbances. Compared with the conventional Proportional-derivative (PD) and time-delay control, the result shows that the proposed control scheme based on time-delay estimation can improve the joint trajectory tracking accuracy of cable-driven robot by significantly reducing the control gains. With the PD gains self-tuned by fuzzy strategy, the mean square errors of trajectory tracking are decreased approximately by 5–20% more than the conventional time-delay control with constant gains. In addition, the experimental result shows that the proposed method has an effective inhibitory effect on dead zone in cable-driven joints. Experiment performed on position tracking control of a 2-degree-of-freedom cable-driven robot is presented to illustrate that the controller has the advantages of simple and reliable structure, model-free, strong robustness, and high tracking accuracy.
3D Space Trajectory Tracking of Underactuated AUVs using Back-Stepping Control and Time Delay Estimation
