RESUMEN
This paper proposes an event-based adaptive tracking control scheme for the n-link robotic systems in the presence of unknown backlash-like hysteresis (BLH) and deferred position constraints. By combining a transformation error with an asymmetric Lyapunov function, the devised control tactic achieves that the position constraints of robotic systems are not violated after user pre-specified time. In contrast to the results of robotic systems with position constraints, this paper removes a common assumption condition generated by the conventional barrier Lyapunov function method. Then, the adverse effect of unknown BLH can be offset by the Nussbaum function. Meanwhile, an event-triggered mechanism is designed to economize on the network bandwidth resources. Finally, based on the Lyapunov theory, an event-based adaptive tracking control tactic is proposed to ensure that all the signals of robotic systems are bounded under unknown BLH and deferred position constraints. Some simulation results proof that the devised control scheme is valid.
RESUMEN
This paper focuses on the tracking control problem for the two-wheeled mobile robot (TWMR) with unknown parameters. The robot collects its own states from the networked positioning system, which is subject to Denial-of-Service (DoS) attacks. To handle the uncertainties in the robot model and mitigate the attack effects on the system performance, parameter estimators with the projection operator technique are introduced. Then, an adaptive tracking controller is designed by adopting the backstepping technique. Correspondingly, a stability condition is derived, which guarantees that all the closed-loop signals are semi-globally uniformly bounded and tracking errors can converge to an adjustable compact set. The stability condition also reveals the relationships among the attack durations, design parameters and tracking errors, which can be utilized to guide the choice of design parameters. Experimental results are provided to validate the effectiveness of the proposed control scheme.
RESUMEN
The core idea of traditional adaptive control is to reconstruct parameter estimation errors with known signals and damping injection based on tracking error, while the formulation of desired damping in controller designs is usually a nontrivial task. The main contribution of this paper lies in the development of the classic RISE result and a constructive damping injection procedure for the adaptive tracking control of Euler-Lagrange mechanical systems. By utilizing generalized dynamic scaling function, scalar filtering, the improved RISE method and analyzing the existence of finite escape time of the closed-loop system, a globally asymptotically stable result is obtained with facilitative damping injection, significant order reduction and improved design efficiency when compared with the existing results. Simulations on a fully actuated 2-DOF planar robot manipulator model demonstrate the effectiveness of the proposed methods.
RESUMEN
This paper proposes a novel constraint adaptive backstepping based tracking controller for nonlinear active suspension system with parameter uncertainties and safety constraints. By introducing the virtual control input and reference trajectories, the adaptive control law is developed to stabilize both of the vertical and pitch motions of vehicle body using backstepping technique and Lyapunov stability theory, and further to track the predefined reference trajectories within a finite time, which not only ensure the safety performance requirements, but also achieve improvements in riding comfort and handling stability of vehicle active suspension system. Next, the stability analysis on zero dynamics error system is conducted to ensure that all the safety performance indicators are all bounded and the corresponding upper bounds are estimable. Finally, a numerical simulation is provided to verify the effectiveness of the proposed controller and to address the comparability between the classical Barrier-Lyapunov Function based adaptive tracking controller and the proposed controller.