A new fuzzy time-delay control for cable-driven robot

Abstract

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 timedelay 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.

Tracking control of an uncertain heavy load robot based on super twisting sliding mode control and fuzzy compensator

“…Many control schemes have been developed for various robot systems, including proportional-integral-derivative (PID) control [1], dynamic decoupling computed torque controller (CTC) [2], sliding mode (SM) control [2,3], and adaptive control [4]. To improve flexibility and adaptability, the research and application of intelligent control methods such as fuzzy control and neural network control are emerging in large numbers [5][6][7]. Due to the noise pollution of the measured value of system state variables and the existence of parameter perturbation and external disturbance, the performance of PID and CTC controllers is seriously affected [8,9].…”

Time Delay Estimation Control of Permanent Magnet Spherical Actuator Based on Gradient Compensation

“…However, the implementation of the sliding mode control algorithm needs to know the upper bound of disturbance, and it is easy to cause the chattering of the position tracking response and output torque, which will affect the motor body. In [23], a method combining time delay estimation control with fuzzy logic was put forward, which uses fuzzy logic to eliminate nonlinear terms, but fuzzy control will make the system complicated and increase the amount of calculation. Although the above methods can effectively suppress the time delay estimation errors, more control gain will make the system complicated, and the control gain adjustment is time-consuming, which will increase the burden of actual controller design.…”

Velocity-Free Adaptive Time Delay Control of Robotic System

“…e controller has a synergy effect coming from the complementary use of TDC and internal model. In [15], a fuzzy logic TDC was designed for a cable-driven robot. e TDC was used to estimate and cancel the soft nonlinearity while the fuzzy logic was used to cancel the hard nonlinearity.…”

“…e fuzzy logic TDC not only has a simple structure but also can effectively track the desired trajectory. Although the TDE error can be offset effectively by the control methods in [9][10][11][12][13][14][15], several gains need to be adjusted and the velocity and acceleration need to be measured additionally. Since it is a time-consuming task to adjust gains, a TDC method based on gradient estimator was designed for robot manipulator in [16].…”