Yana Yang

Adaptive Fuzzy Finite-Time Coordination Control for Networked Nonlinear Bilateral Teleoperation System

The master-slave control design problem is considered for the networked teleoperation system with friction and external disturbances. A new finite-time synchronization control method is proposed with the help of adaptive fuzzy approximation. We develop a new nonsingular fast terminal sliding mode (NFTSM) to provide faster convergence and higher precision than the linear hyperplane-sliding mode and the classic terminal-sliding mode (TSM). Then, the adaptive fuzzy-logic system is employed to approximate the system uncertainties, and the corresponding adaptive fuzzy NFTSM controller is designed. By constructing Lyapunov function, the stability and finite-time synchronization performance are proved with the new controller in the presence of system uncertainties and external disturbances. Compared with the traditional teleoperation design method, the new control scheme achieves better transient-state performance and steady-state performance. Finally, the simulations are performed and the comparisons are shown among the proposed method, the P+d method, the PD+d method, the DFF method, and the classic TSM FTSM. The simulation results further demonstrate the effectiveness of the proposed method.

Output-Feedback Adaptive Control of Networked Teleoperation System With Time-Varying Delay and Bounded Inputs

The output-feedback based controller design problem is investigated for the networked teleoperation system in this paper. A new control scheme is proposed to guarantee the global asymptotic stability of the bilateral teleoperation system with time-varying delays and bounded inputs. First, a new fast terminal sliding-mode velocity observer is proposed to estimate the unknown velocity signals for the teleoperation system. Then, by considering the unknown gravity term, an adaptive SP+Sd-type (saturated proportion plus saturated damping) controller is designed based on the estimated velocity. In the new controllers, the specific sigmoidal function is not used, and any one on a set of saturation functions can be applied. Furthermore, by choosing Lypunov-Krasovskii functional, we show that the master-slave teleoperation system is stable under specific linear matrix inequality conditions. With the given controller design parameters and the upper bound of the input, the allowable maximal transmission delay can be computed by using the proposed stability criteria. Finally, both simulations and experiments are performed to show the effectiveness of the proposed methods.

Neural network-based adaptive position tracking control for bilateral teleoperation under constant time delay

The trajectory tracking problem for the teleoperation systems is addressed in this paper. Two neural network-based controllers are designed for the teleoperation system in free motion. First, with the defined synchronization variables containing the velocity error and the position error between master and slaver, a new adaptive controller using the acceleration signal is designed to guarantee the position and velocity tracking performance between the master and the slave manipulators. Second, with the acceleration signal unavailable, a controller with the new synchronization variables is proposed such that the trajectory tracking error between the master and the slave robots asymptotically converges to zero. By choosing proper Lyapunov functions, the asymptotic tracking performance with these two controllers is proved without the knowledge of the upper bound of the neural network approximation error and the external disturbance. Finally, the simulations are performed to show the effectiveness of the proposed methods.

Adaptive neural network based prescribed performance control for teleoperation system under input saturation

Abstract This paper addresses the stability and position synchronization problems for bilateral nonlinear teleoperation system with asymmetric constant time delays under input saturation. Compared with previous work, not only the steady-state performance but also the transient-state performance is considered. In the presence of system uncertainties and external disturbances, the corresponding adaptive neural network (ANN) based prescribed performance control (PPC) scheme is designed. Moreover, the time-dependent stability conditions are derived by applying the linear matrix inequality (LMI). Finally, in simulation comparisons with P+d (proportion plus differential) controller are conducted, simulation results are presented to demonstrate the effectiveness of the proposed PPC approach.

Bilateral Teleoperation Design With/Without Gravity Measurement

The networked teleoperation design problem is considered. The communication delays are assumed to be both time varying and asymmetrical, which is the case for network-based teleoperation systems. Two cases are considered, i.e., that gravity functions are available and not available. To avoid the heavy collision between the slave robot and the environment, a new torque design scheme is proposed. A designed force is added to the master robot to make the human operator feel the environment before touching the object. The master velocity signal and the distance signal between the slave robot and the object are all embedded in the designed force function. By constructing Lyapunov functional, the stability of the closed-loop system is proved. For the case that the gravity function is not available, an adaptive compensator design method is proposed on both sides. The stability of the closed-loop system is also proven with the new master-slave adaptive controllers. Finally, the simulations are performed, and the results show the effectiveness of the proposed method.

Adaptive fuzzy synchronization control for networked teleoperation system with input and multi-state constraints

Abstract Constraints are ubiquitous in physical systems, and manifest themselves as physical stoppages, saturation, as well as performance and safety specifications, among others. Violation of the constraints during operation may result in performance degradation, hazards or system damage. In this paper, the synchronization control problem for teleoperation system is investigated with input saturation and multi-state constraints in the presence of system uncertainties and asymmetric time delays. For the multi-state constraints, two types of barriers are considered: constant symmetric barriers and time-varying asymmetric barriers. An auxiliary system is designed to deal with the input saturation problem and the Fuzzy Logic system (FLs) is employed to approximate the system uncertainties. Then, new adaptive fuzzy control algorithms are designed by applying the backstepping method to provide some high performances: faster synchronization speed and higher precision. By constructing the barrier Lyapunov functions (BLF), the stability and synchronization performances are proved with the new control algorithms. Moreover, the system input and system states are prevented from transgressing the constrained region during the transient stages. Therefore, both the steady-state and transient-state performances can be guaranteed. Finally, experiment on two Phantom Premium 1.5A robots is performed to demonstrate the effectiveness of the proposed methods.

Finite-time output-feedback synchronization control for bilateral teleoperation system via neural networks

The finite-time control problem is considered for bilateral teleoperation system via output feedback approach. A new observer is designed for the velocity estimation and the resulting velocity error system is proved to be semi-globally stable. The observer based output feedback finite-time controller is developed by employing a novel nonsingular fast integral terminal sliding mode. The closed-loop system is proved to be stable based on Lyapunov stability theory. It is shown that the master-slave synchronization error converges to zero in finite time. The merit of the proposed method is that the designed controller only uses the position information which renders that the master-slave synchronization error reaches zero in the prescribed time. Simulation and experiment are performed and the results demonstrate the effectiveness of the proposed method.

Finite-time coordination control for networked bilateral teleoperation

Robotica / Volume 33 / Issue 02 / February 2015, pp 451 462 DOI: 10.1017/S026357471400037X, Published online: 05 March 2014 Link to this article: http://journals.cambridge.org/abstract_S026357471400037X How to cite this article: Yana Yang, Changchun Hua, Huafeng Ding and Xinping Guan (2015). Finite-time coordination control for networked bilateral teleoperation. Robotica, 33, pp 451-462 doi:10.1017/S026357471400037X Request Permissions : Click here

Fixed-time Coordination Control for Bilateral Telerobotics System with Asymmetric Time-varying Delays

Fixed-time coordination in dynamical systems means system trajectories converge to the desired trajectories in determined time which is independent of the system initial states. In this paper, a novel fixed-time coordination control approach for nonlinear telerobotics system with asymmetric time-varying delays is proposed to provide faster convergence rate and higher convergence precision. The neural networks (NNs) and the parameter adaptive method are combined to approximate the uncertain model of the teleoperator, the upper bound of the NNs estimation errors and the external disturbances. Then the corresponding adaptive NNs fixed-time controller is designed without using the derivatives of the time-varying delays. Dynamic surface control (DSC) is employed to avoid the singularity. Moreover, considering the nonpassive human operator and remote environment insert forces, the stability criterion for the closed-loop system is also developed. Then by choosing proper Lyapunov functions, the master-slave coordination errors converging into a deterministic domain in fixed-time with the new controller is proved in the presence of the exogenous forces from human operator and remote environment. Furthermore, the exact convergence time is presented only with the designed parameters. Some comparisons are conducted in simulation to show the superior performance of the proposed control approach. Finally, experimental results are also given to demonstrate the effectiveness of the new control method.

Robust adaptive uniform exact tracking control for uncertain Euler–Lagrange system

ABSTRACT This paper offers a solution to the robust adaptive uniform exact tracking control for uncertain nonlinear Euler–Lagrange (EL) system. An adaptive finite-time tracking control algorithm is designed by proposing a novel nonsingular integral terminal sliding-mode surface. Moreover, a new adaptive parameter tuning law is also developed by making good use of the system tracking errors and the adaptive parameter estimation errors. Thus, both the trajectory tracking and the parameter estimation can be achieved in a guaranteed time adjusted arbitrarily based on practical demands, simultaneously. Additionally, the control result for the EL system proposed in this paper can be extended to high-order nonlinear systems easily. Finally, a test-bed 2-DOF robot arm is set-up to demonstrate the performance of the new control algorithm.