Adaptive Fuzzy Dynamic Surface Control of Flexible-Joint Robot Systems With Input Saturation

In this paper, we propose an adaptive fuzzy dynamic surface control(DSC) scheme for single-link flexible-joint robotic systems with input saturation. A smooth function is utilized with the mean-value theorem to deal with the difficulties associated with input saturation. An adaptive DSC design with an auxiliary first-order filter is used to solve the "explosion of complexity"problem. It is proved that all the signals in the closed-loop system are semi-globally uniformly ultimately bounded, and the tracking error eventually converges to a small neighborhood around zero. The main advantage of the proposed method is that only one adaptation parameter needs to be updated,which reduces the computational burden significantly. Simulation results demonstrate the feasibility of the proposed scheme and the comparison results show that the improved DSC method can reduce the computational burden by almost two thirds in comparison with the standard DSC method.

Interval Type-2 Fuzzy PD Tracking Control of Flexible-Joint Robots

This paper develops a novel interval type-2 fuzzy Proportional-Derivative (PD) control scheme for electrically driven flexible-joint robots using the direct method of Lyapunov. The controller has a simple design in a decentralized structure. Compared to the previous controllers reported for the flexible-joint robots which use two control loops, it has a simpler structure using only one control loop. It guarantees stability and provides a good tracking performance. The controller considers the whole robotic system including the manipulator and motors by applying the voltage control strategy. Stability analysis is presented and the effectiveness of the proposed control approach is demonstrated by simulations using a three link flexible-joint robot driven by permanent magnet DC motors. Simulation results show that the interval type-2 fuzzy PD controller can handle external disturbance better than the type-1 fuzzy PD controller. In addition, it spends less control effort than the type-1 in order to deal with disturbance.

Type-2 Fuzzy Control for a Flexible-joint Robot Using Voltage Control Strategy

ype-1 fuzzy sets cannot fully handle the uncertainties. To overcome the problem, type2 fuzzy sets have been proposed. The novelty of this paper is using interval type-2 fuzzy logic controller （IT2FLC） to control a flexible-joint robot with voltage control strategy. In order to take into account the whole robotic system including the dynamics of actuators and the robot manipulator, the voltages of motors are used as inputs of the system. To highlight the capabilities of the control system, a flexible joint robot which is highly nonlinear, heavily coupled and uncertain is used. In addition, to improve the control performance, the parameters of the primary membership functions of IT2FLC are optimized using particle swarm optimization （PSO）. A comparative study between the proposed IT2FLC and type-1 fuzzy logic controller （T1FLC） is presented to better assess their respective performance in presence of external disturbance and unmodelled dynamics. Stability analysis is presented and the effectiveness of the proposed control approach is demonstrated by simulations using a two-link flexible-joint robot driven by permanent magnet direct current motors. Simulation results show the superiority of the IT2FLC over the T1FLC in terms of accuracy, robustness and interpretability.