Obstacle Avoidance Using CTC and Virtual Structure for Leader-Follower Formation on Mobile Robot

This research examined the development of the combination of virtual structure and leader-follower as an obstacle avoidance method in the formation control of a mobile robot. The formation of the robots are designed with the Separation Bearing Control (SBC) approach between the leader robot (RL) and the virtual robot (RV). The virtual robot is used as a virtual follower and a reference trajectory for the follower robot (RF). When the follower robot detects an obstacle, the follower robot trajectory is adjusted using a trajectory planner for obstacle avoidance. After passing the obstacle, the follower robot will track its position back in formation using virtual robot position and heading as reference. Leader robot and follower are perturbed by disturbances. In order to ensure the achievement of small error tracking, a controller is designed using the integration of kinematic and dynamics controllers with disturbance observer. The kinematic and dynamics controllers are designed using input-output linearisation (IOL) method and computed torque control (CTC). The effectiveness of the proposed method is verified by the simulation result.Keywords: CTC, leader follower, obstacle avoidance, SBC, virtual structure.

Robust Computed Torque Control for Uncertain Robotic Manipulatorss

This paper presents a robust control method for the trajectory control of the robotic manipulator. The standard Computed Torque Control (CTC) is an important method in the robotic control systems but its not robust to system uncertainty and external disturbance. The proposed method overcome the system uncertainty and external disturbance problems. In this paper, a robustification term has been added to the standard CTC. The stability of the proposed control method is approved by the Lyapunov stability theorem. The performance of the presented controller is tested by MATLAB-Simulink environment and is compared with different control methods to illustrate its robustness and performance.

Optimal adaptive computed torque control for haptic-teleoperation system with uncertain dynamics

This study aimed to eliminate dynamic uncertainty, one of the main problems of haptic teleoperation robotic systems. The optimal adaptive computed torque control method was used to overcome this problem. As is known, excellent stability and transparency are required in teleoperation systems. However, dynamic uncertainty that causes stability problems in the control of these systems also causes poor performance. In conventional adaptive computed torque control methods, updating the parameters of the system is generally discussed, but updating the control coefficients of vital importance in the control of the system is not considered. In the proposed method, an adaptation rule has been created to update uncertain parameters. In addition, the gray wolf optimization algorithm, one of the current optimization algorithms, has been proposed and applied to obtain the control coefficients of the system. The position tracking stability of the system was examined by using Lyapunov stability analysis method. As a result, both simulation and real-time optimal adaptive computational torque control method were used and bilateral position and force control was performed and the performance results of the system are obtained graphically and examined. Optimal adaptive computed torque control method obtained using the gray wolf optimization algorithm was used first in the literature search and success results have been obtained. In this regard, the authors have the idea that this work is an innovative aspect of both simulation and real time with the optimal adaptive computed torque control method.

A PD Computed Torque Control Method with Online Self-gain Tuning for a 3UPS-PS Parallel Robot

SUMMARY In this paper, an online self-gain tuning method of a PD computed torque control (CTC) is used for a 3UPS-PS parallel robot. The CTC is applied to the 3UPS-PS parallel robot based on the robot dynamic model which is established via a virtual work principle. The control system of the robot comprises a nonlinear feed-forward loop and a PD control feedback loop. To implement real-time online self-gain tuning, an adjustment method based on the genetic algorithm (GA) is proposed. Compared with the traditional CTC, the simulation results indicate that the control algorithm proposed in this study can not only enhance the anti-interference ability of the system but also improve the trajectory tracking speed and the accuracy of the 3UPS-PS parallel robot.