Abstract
Tracking control has been an important research topic in robotics. It is critical to design controllers that make robotic systems with smooth velocity commands. In addition, the robustness of the robotic system in the presence of system and measurement noises is an important consideration as well. This paper presents a novel tracking control strategy that integrates a biologically inspired backstepping controller and a torque controller with unscented Kalman filter (UKF) and Kalman filter (KF). The bioinspired backstepping controller and torque controller are capable of avoiding and reducing the velocity jumps and overshoots that occur in conventional backstepping control and provide smooth velocity commands. The integration of KF and UKF enables the proposed control strategy capable of providing accurate state estimates. The stability and convergence of tracking errors are guaranteed by Lyapunov stability analysis. The novelty of the proposed bioinspired tracking control strategy is to take the system and measurement noises and robot dynamic constraints into the consideration. The results show that the proposed control strategy provides accurate state estimates and avoids large velocity jumps and overshoot that occurs in conventional backstepping control. This tracking control strategy is suitable for autonomous mobile robots under hard conditions with system and measurement noises.
Highlights
Real-time tracking control has always been an essential research area in robotics [1], [2]
This paper developed a novel tracking control method that can generate smooth velocity commands and provide accurate state estimates by integrating the biologically inspired backstepping control and the torque control with Kalman filter (KF) and unscented Kalman filter (UKF)
The feedbacks for torque control and bioinspired backstepping control are respectively propagated through KF and UKF to generate accurate state estimates for the better performance of the control strategy in order for a mobile robot operating in hard conditions
Summary
Real-time tracking control has always been an essential research area in robotics [1], [2]. It is important to have the robotic system reach a certain speed that drives the robot to track its desired trajectory. Accurately tracking the desired trajectory is an important task in real-life applications as well. It is necessary to make the robot accurately track its desired trajectory and robust to these noises. The tracking control method should be practically applicable for a mobile robot and easy to implement. The mobile robot is subjected to a nonholonomic kinematic constraint which is given as yc cos θc − xc sin θc = 0
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