Position control for haptic device based on discrete-time proportional integral derivative controller

Haptic devices had known as advanced technology with the goal is creating the experiences of touch by applying forces and motions to the operator based on force feedback. Especially in unmanned aerial vehicle (UAV) applications, the position of the end-effector Falcon haptic sets the velocity command for the UAV. And the operator can feel the experience vibration of the vehicle as to the acceleration or collision with other objects through a forces feedback to the haptic device. In some emergency cases, the haptic can report to the user the dangerous situation of the UAV by changing the position of the end-effector which is be obtained by changing the angle of the motor using the inverse kinematic equation. But this solution may not accurate due to the disturbance of the system. Therefore, we proposed a position controller for the haptic based on a discrete-time proportional integral derivative (PID) controller. A Novint Falcon haptic is used to demonstrate our proposal. From hardware parameters, a Jacobian matrix is calculated, which combines with the force output from the PID controller to make the torque for the motors of the haptic. The experiment was shown that the PID has high accuracy and a small error position.

Robust Control of Robot Manipulator based on QFT and H∞

Robust controllers have been developed by both control techniques QFT and H∞ applied in the waist, shoulder and elbow of a manipulator of 6 degrees of freedom. The design is based on the identification of a linear model of the robot dynamics which represents the non-linearity of the system using parametric uncertainty. QFT control methodology is used to tune the robust PID-controller and pre-filters of the system, and H∞ controllers are obtained by designing the weighting functions and using the MATLAB hinfopt tool. Finally the performance of robust controllers is compared designed based on the calculation and analysis of some behavioral indices.

Design and robustness analysis of fuzzy PID controller for automatic voltage regulator system using genetic algorithm

In this paper, a Fuzzy proportional–integral–derivative (Fuzzy PID) controller design is presented to improve the automatic voltage regulator (AVR) transient characteristics and increase the robustness of the AVR. Fuzzy PID controller parameters are determined by a genetic algorithm (GA)-based optimization method using a novel multi-objective function. The multi-objective function, which is important for tuning the controller parameters, obtains the optimal solution using the Integrated Time multiplied Absolute Error (ITAE) criterion and the peak value of the output response. The proposed method is tested on two AVR models with different parameters and compared with studies in the literature. It is observed that the proposed method improves the AVR transient response properties and is also robust to parameter changes.