Synchronous Control Protocol Research Articles

Optimal synchronization with [formula omitted]-gain performance: An adaptive dynamic programming approach

This paper studies an optimal synchronous control protocol design for nonlinear multi-agent systems under partially known dynamics and uncertain external disturbance. Under some mild assumptions, Hamilton–Jacobi–Isaacs equation is derived by the performance index function and system dynamics, which serves as an equivalent formulation. Distributed policy iteration adaptive dynamic programming is developed to obtain the numerical solution to the Hamilton–Jacobi–Isaacs equation. Three theoretical results are given about the proposed algorithm. First, the iterative variables is proved to converge to the solution to Hamilton–Jacobi–Isaacs equation. Second, the L2-gain performance of the closed loop system is achieved. As a special case, the origin of the nominal system is asymptotically stable. Third, the obtained control protocol constitutes an Nash equilibrium solution. Neural network-based implementation is designed following the main results. Finally, two numerical examples are provided to verify the effectiveness of the proposed method.

Control Synchronization Design of a Multiple Electrohydraulic Actuator System with Linearization Dynamics and an External Disturbance Observer

The control synchronization of multiple electrohydraulic actuators (MEHAs) is initially discussed to ensure the consensus of every electrohydraulic actuator (EHA) with three-order isomorphic dynamics. First, the EHA model is linearized using the Lie derivative method to obtain the state-space model of MEHAs. Then, the disturbance observer is used to estimate and compensate for the unknown external load caused by the driving force of a motion plant. Via the Lyapunov technique, this protocol asymptotically achieves consensus to a zero neighborhood with the ultimate boundaries of the MEHAs’ state errors. The effectiveness of the synchronous control protocol is verified by both simulation and experimental benches with two-node EHAs.

Uncertainty and disturbance estimator-based distributed synchronization control for multiple marine surface vehicles with prescribed performance

The accuracy is of great significance to the synchronization motion of the marine surface vehicles (MSVs). However, the accuracy is highly affected by the uncertain hydrodynamic damping dynamics and the unknown environmental disturbances. This paper aims to address the coordinated synchronization motion control problem for a group of uncertain MSVs subject to exogenous time-varying disturbances under prescribed performance constraints. To improve the accuracy of synchronization motion, the uncertainty and disturbance estimator (UDE) is employed to completely compensate for the modeling uncertainties, the external time-varying disturbances, and the accelerations of the neighboring MSVs. Based on error transformation, backstepping procedure, and control Lyapunov synthesis, a distributed UDE-based synchronization control protocol is developed. The proposed UDE-based synchronization control algorithm could achieve fast and accurate synchronization motion in the sense that the neighborhood error converges asymptotically to zero with convergence rate no less than a given value. Simulation results verify the effectiveness of the proposed synchronization control algorithm.

Optimal synchronization control for heterogeneous multi‐agent systems: Online adaptive learning solutions

AbstractThis paper presents an online adaptive learning solution to the optimal synchronization control problem of heterogeneous multi‐agent systems via a novel distributed policy iteration approach. For the leader‐follower multi‐agents, the dynamics of all the followers are heterogeneous with leader disturbance. To make the output of each follower synchronize with the leader's output, we propose a synchronization control protocol where the stability conditions for selecting the feedback gains are given. Next, with a minimization of the output tracking errors, we optimize the feedback gains for the synchronization control protocol, and the unique solutions for those feedback gains are learned via a novel distributed policy iteration approach. We prove that the proposed online adaptive learning solution will converge to the optimal control solution under some mild conditions. Finally, an illustrative numerical example is provided to show the effectiveness of the approach.

A hybrid adaptive synchronization protocol for nondeterministic perturbed fractional-order chaotic nonlinear systems

In this paper, we investigate hybrid adaptive synchronization issue for a class of perturbed fractional-order chaotic systems with nondeterministic nonlinear terms. On the basis of fractional-order extended version of Lyapunov stability criterion, a novel fuzzy adaptive synchronization control protocol coupled with backstepping-based method is constructed, ensuring that the synchronization errors converge to a sufficiently small region of the origin. In order to avert the occurrence of “explosion of complexity”, we take advantage of a fuzzy logic system to estimate the unknown systematic term approximately in every backstepping step. Finally, some numerical simulations are given to exemplify the effectiveness of the proposed approach.

Distributed adaptive sliding mode control for attitudes synchronization of multiple autonomous underwater vehicles

This article is concerned with attitudes synchronization of networked autonomous underwater vehicles, which aims to enable all the autonomous underwater vehicles tracking the desired attitude coordinately, when the desired attitude information can only be achieved by one or one subset autonomous underwater vehicles. A Lyapunov technique is presented for designing an adaptive synchronization control protocol using sliding mode and consensus theory. The uncertainty of the autonomous underwater vehicle dynamics, and the unknown external disturbance and input saturation were both considered in our controller proposed; moreover, only the neighbors’ information were used by the controller, so it is totally distributed. Simulations were performed to validate the theoretical results.

A Synchronous Motor Imagery Based Neural Physiological Paradigm for Brain Computer Interface Speller.

Brain Computer Interface (BCI) speller is a typical BCI-based application to help paralyzed patients express their thoughts. This paper proposed a novel motor imagery based BCI speller with Oct-o-spell paradigm for word input. Furthermore, an intelligent input method was used for improving the performance of the BCI speller. For the English word spelling experiment, we compared synchronous control with previous asynchronous control under the same experimental condition. There were no significant differences between these two control methods in the classification accuracy, information transmission rate (ITR) or letters per minute (LPM). And the accuracy rates of over 70% validated the feasibility for these two control strategies. It was indicated that MI-based synchronous control protocol was feasible for BCI speller. And the efficiency of the predictive text entry (PTE) mode was superior to that of the Non-PTE mode.

Distributed adaptive control for synchronization of unknown nonlinear networked systems

This paper is concerned with synchronization of distributed node dynamics to a prescribed target or control node dynamics. A design method is presented for adaptive synchronization controllers for distributed systems having non-identical unknown nonlinear dynamics, and for a target dynamics to be tracked that is also nonlinear and unknown. The development is for strongly connected digraph communication structures. A Lyapunov technique is presented for designing a robust adaptive synchronization control protocol. The proper selection of the Lyapunov function is the key to ensuring that the resulting control laws thus found are implementable in a distributed fashion. Lyapunov functions are defined in terms of a local neighborhood tracking synchronization error and the Frobenius norm. The resulting protocol consists of a linear protocol and a nonlinear control term with adaptive update law at each node. Singular value analysis is used. It is shown that the singular values of certain key matrices are intimately related to structural properties of the graph.