Zhi Feng

Robust connectivity preserving rendezvous of multi-robot systems under unknown dynamics and disturbances

This paper studies a robust connectivity preserving rendezvous problem for a leader-following multi-robot system. Only a small group of mobile robots are informed to have access to the leaders information. A distributed control law is proposed such that connectivity preserving rendezvous is achieved regardless of the unknown nonlinear dynamics and disturbances. Although the multi-robot network has a dynamic network topology, the developed controller is able to maintain the connectivity of an initially connected communication network. Using the tools from algebraic graph theory, Lyapunov method, and nonsmooth analysis, sufficient conditions on the convergence of the closed-loop error systems are derived.

Distributed Coordination of Multiple Unknown Euler-Lagrange Systems

A robust consensus tracking problem is addressed for multiple unknown Euler-Lagrange systems where only a subset of the agents is informed of the desired time-varying trajectory. Challenging unstructured uncertainties, including unknown nonlinear dynamics and disturbances, are considered in the agent dynamics. A model-free, identifier-based, continuous, distributed robust control method is designed to solve this problem under both undirected and directed graphs. The control inputs and coupling gains depend only on local information and the consensus tracking errors are proven to converge to zero asymptotically. Under an undirected graph, a distributed nonlinear identifier is developed for each agent to compensate for the unknown nonlinear dynamics and disturbances. Based on this identifier, a continuous distributed control law is designed to enable asymptotic robust consensus tracking. By selecting the gains of the designed controller according to the derived conditions, closed-loop stability is proven using graph theory and Lyapunov analysis. Furthermore, the directed graph case is investigated via a distributed two-layer coordination scheme in which a model-free continuous distributed controller is designed by using information obtained from a distributed leader estimator. Numerical simulation results are given to illustrate the effectiveness of the proposed methods.

Distributed Secure Coordinated Control for Multiagent Systems Under Strategic Attacks

This paper studies a distributed secure consensus tracking control problem for multiagent systems subject to strategic cyber attacks modeled by a random Markov process. A hybrid stochastic secure control framework is established for designing a distributed secure control law such that mean-square exponential consensus tracking is achieved. A connectivity restoration mechanism is considered and the properties on attack frequency and attack length rate are investigated, respectively. Based on the solutions of an algebraic Riccati equation and an algebraic Riccati inequality, a procedure to select the control gains is provided and stability analysis is studied by using Lyapunov’s method.. The effect of strategic attacks on discrete-time systems is also investigated. Finally, numerical examples are provided to illustrate the effectiveness of theoretical analysis.

Robust Connectivity Preserving Rendezvous of Multirobot Systems Under Unknown Dynamics and Disturbances

This paper studies a robust connectivity preserving rendezvous problem for a leader-following multirobot system. Only a small group of mobile robots is informed to have access to the leaders information. A distributed, robust, dynamic, control law is proposed such that connectivity-preserving rendezvous is achieved regardless of the unknown nonlinear dynamics and disturbances. Although the multirobot network has a dynamic network topology, the developed controller is able to maintain the connectivity of an initially connected communication network. Using the tools from algebraic graph theory, Lyapunov method, and nonsmooth analysis, sufficient conditions on the asymptotic convergence of the closed-loop multirobot systems are derived. A numerical example and simulation results are presented to show the effectiveness of the proposed approach.

Distributed secure average consensus for linear multi-agent systems under DoS attacks

This paper studies event-triggered secure cooperative control of linear multi-agent systems under Denial-of-Service (DoS) attacks. The DoS attacks refer to interruptions of communication on the control channels carried out by an intelligent adversary. We consider time-sequence-based DoS attacks allowed to occur aperiodically in an unknown attack strategy. The frequency and duration of DoS attacks are analyzed and investigated for a secure average consensus problem. A distributed event-triggered control law is developed and scheduling of controller updating times is determined in the presence of DoS attacks. It is shown that under the proposed distributed control scheme, the agents can achieve secure consensus exponentially. The effectiveness of the developed methods is illustrated through example and numerical simulations on multi-robot coordination.

Distributed Tracking Control for Multi-Agent Systems Under Two Types of Attacks ⋆

This paper studies a distributed consensus tracking control problem for a class of stochastic linear multi-agent systems subject to two types of attacks. The problem boils down to how to achieve robust consensus tracking of multi-agent systems with switching connected and disconnected directed topologies under attacks. The attacks on the edges instead of nodes lead to the loss of consensus tracking security. Based on a multi-step design procedure for designing a distributed secure algorithm, sufficient conditions on robust mean-square exponential consensus tracking are derived via the idea of average dwell time switching between some stable and unstable subsystems obtained from graph theory analysis. An applicaton to a practical power system is considered. It is proved that each distributed generator (DG) modeled as an agent in a microgrid can successfully synchronize their terminal voltage amplitude to a prespecified reference value under these two types of attacks.

Passivity-based consensus and passification for a class of stochastic multi-agent systems with switching topology

This paper studies the passivity-based consensus analysis and the consensus synthesis problem (called passification) for a class of stochastic multi-agent systems subject to external disturbances. Based on Lyapunov methods, graph theory, and slack matrix methods such as the free-weighting matrix and Jensens integral inequality, a new storage Lyapunov functional is proposed to derive delay-dependent sufficient conditions on mean-square exponential consensus and stochastic passivity for the stochastic multi-agent systems. By proposing passive time-varying stochastic consensus protocols, the solvability conditions for the passification problem are derived based on linearization techniques. A numerical example is provided to illustrate the effectiveness of the theoretical results.

Distributed fault-tolerant control for a large-scale power generator network

This paper studies a distributed fault-tolerant control (DFTC) problem for a multi-agent system modeling a large-scale power generator network. The objective is to enable all the agents to achieve the control goal of asymptotic stability without losing the system tracking performance while coordinately identifying the unknown input including nonlinear interconnections and coupling fault functions. A model-based distributed state estimator (DSE) is firstly designed to obtain the residual and a proportional-integral-like nonlinear distributed identifier (DI) is then developed to identify the unknown input. By exploiting the redundancies from the estimated information, a novel continuous DFTC scheme is designed to enable all the agents to achieve the control goal. A power system example and numerical simulation are provided to illustrate the effectiveness.

Multi-robot formation control using distributed null space behavioral approach

This paper presents a distributed formation control method for a group of robots. The global objective of achieving a desired formation is obtained by dividing it into a set of local objectives which are achieved in a distributed manner. A basic repetitive pattern in the desired formation is identified and a corresponding unique differentiable task function is defined based on the position coordinates of the robots forming the pattern. Neighbor selection rules are designed for the robots in such a way that each robot is part of one or more such patterns. A singularity-robust task-priority inverse kinematics method is used to design velocity controllers to achieve these patterns. Since a robot can receive multiple control actions being part of multiple task functions or patterns, a distributed null space behavioral (NSB) approach is designed to combine such multiple control actions in a prioritized way. A comprehensive stability analysis of the proposed approach based on Lyapunov methods is presented. Simulation results are provided to verify the effectiveness of the proposed approach.

Distributed coordinated tracking control for multiple unknown nonlinear Euler-Lagrange systems

This paper studies a robust distributed consensus tracking problem for a class of multiple unknown nonlinear Euler-Lagrange systems where only a subset of the agents has access to the desired trajectory. A nonlinear identifier is first developed for each agent to estimate the unknown nonlinear dynamics and disturbances. Based on the identifier, a continuous distributed consensus tracking algorithm is developed to enable robust consensus tracking under an undirected graph. The closed-loop stability is proven by graph theory and Lyapunov analysis. By selecting the identifier and controller parameters according to the derived sufficient conditions, robust asymptotic consensus tracking can be enabled through local information exchange. An example is provided to illustrate the effectiveness of the proposed method.