Non-identical Unknown Nonlinear Dynamics Research Articles

Linear-Extended-State-Observer Based Pinning Control of Nonlinear Multi-Robots System

In this paper, the pinning control problem of nonlinear multi-robots system (MRS) is investigated. By introducing Linear-Extended-State-Observer (LESO) approach, a LESO based pinning control algorithm is proposed for the multi-robots system with non-identical unknown nonlinear dynamics. By pinning one robot with small coupling strength, a LESO based control algorithm has been developed to guarantee the nonlinear multi-robots system to reach synchronisation when the nonlinear function is given. Furthermore, the tracking errors of the following robots are bounded when the nonlinear function is unknown. Finally, numerical simulations with different scenarios are presented to illustrate the effectiveness of the theoretical results.

Robust Adaptive Fault-tolerant Control of Multi-agent Systems with Uncertain Non-identical Dynamics and Undetectable Actuation Failures

This paper studies the distributed consensus problem of multiagent systems (MASs) in the presence of nonidentical unknown nonlinear dynamics and undetectable actuation failures. Of particular interest is the development of a robust adaptive fault-tolerant consensus protocol capable of compensating uncertain dynamics/disturbances and time-varying yet unpredictable actuation failures simultaneously. By introducing the virtual parameter estimation error into the artfully chosen Lyapunov function, the consensus problem is solved with a robust adaptive fault-tolerant control scheme based upon local (neighboring) agent state information. It is shown that the proposed method is user friendly in that there is no need for detail dynamic information of the agent or costly detection/diagnosis of the actuation faults in control design and implementation, resulting in a structurally simple and computationally inexpensive solution for the leaderless consensus problem of MAS. Simulation results illustrate and verify the benefits and effectiveness of the proposed scheme.

Cooperative Adaptive Fuzzy Tracking Control for Networked Unknown Nonlinear Multiagent Systems With Time-Varying Actuator Faults

In this paper, the cooperative adaptive fault tolerant fuzzy tracking control (CAFTFTC) problem of networked high-order multiagent with time-varying actuator faults is studied, and a novel CAFTFTC scheme is proposed to guarantee that all follower nodes asymptotically synchronize a leader node with tracking errors converging to a small adjustable neighborhood of the origin in spite of actuator faults. The leader node is modeled as a higher order nonautonomous nonlinear system. It acts as a command generator giving commands only to a small portion of the networked group. Each follower is assumed to have nonidentical unknown nonlinear dynamics, and the communication network is also assumed to be a weighted directed graph with a fixed topology. A distributed robust adaptive fuzzy controller is designed for each follower node such that the tracking errors are cooperative uniform ultimate boundedness (CUUB). Moreover, these controllers are distributed in the sense that the controller designed for each follower node only requires relative state information between itself and its neighbors. The adaptive compensation term of the optimal approximation errors and external disturbances is adopted to reduce the effects of the errors and disturbances, which removes the assumption that the upper bounds of unknown function approximation errors and disturbances should be known. Analysis of stability and parameter convergence of the proposed algorithm are conducted that are based on algebraic graph theory and Lyapunov theory. Comparing with results in the literature, the CAFTFTC scheme can minimize the time delay between fault occurrence and accommodation and reduce its adverse effect on system performance. In addition, the FTC scheme requires no additional fault isolation model, which is necessary in the traditional active FTC scheme. Finally, an example is provided to validate the theoretical results.

Extended-state-observer-based adaptive control for synchronisation of multi-agent systems with unknown nonlinearities

This paper studies the problem of synchronisation to a desired trajectory for non-linear multi-agent systems. By introducing extended state observer approach, decentralised adaptive controllers are designed for distributed systems which have non-identical unknown non-linear dynamics. The non-identical unknown non-linear dynamics allows for a tracked command dynamics which is also non-linear and unknown. State variables of agents can be obtained only in the case where leader agent and the network communication topology for multi-agent systems is strongly connected digraph network structures. A Lyapunov-function-based approach is given to show that the tracking error is ultimately bounded. Some simulation results are given to demonstrate the effectiveness of the developed techniques in this paper.

Adaptive finite-time consensus in multi-agent networks

This paper is concerned with the finite-time consensus problem of distributed agents having non-identical unknown nonlinear dynamics, to a leader agent that also has unknown nonlinear control input signal. By parameterization of unknown nonlinear dynamics, a Lyapunov technique in conjunction with homogeneity technique is presented for designing a decentralized adaptive finite-time consensus control protocol in undirected networks. Homogeneous Lyapunov functions and homogeneous vector fields are introduced in the stability analysis although the whole system is not homogeneous. Theoretical analysis shows that leader-following consensus can be achieved in finite-time, meanwhile, finite-time parameter convergence can be also guaranteed under the proposed control scheme. An example is given to validate the theoretical results.

Adaptive Consensus of High Order Multi-Agent Systems with Unknown Nonlinear Dynamics

In this paper, high order consensus problem of multi-agent systems with non-identical unknown nonlinear dynamics following an unknown and nonlinear leader is investigated in networks with fixed and switching topologies. By parameterizations of unknown nonlinear dynamics of agents in the system, neighbor-based adaptive consensus algorithms are proposed by incorporating consensus errors in addition to relative position feedback. Base on algebraic graph theory, Lyapunov theory, Riccati inequalities and PE condition, analysis of stability and parameter convergence of the proposed algorithm are conducted. Finally, a simulation in switching networks is worked out to illustrate the effectiveness of the theoretical results.

Adaptive consensus of multi-agents in networks with jointly connected topologies

In this paper, the consensus problem of multi-agent following a leader is studied. An adaptive design method is presented for multi-agent systems with non-identical unknown nonlinear dynamics, and for a leader to be followed that is also nonlinear and unknown. By parameterizations of unknown nonlinear dynamics of all agents, a decentralized adaptive consensus algorithm is proposed in networks with jointly connected topologies by incorporating local consensus errors in addition to relative position feedback. Analysis of stability and parameter convergence of the proposed algorithm are conducted based on algebraic graph theory and Lyapunov theory. Finally, examples are provided to validate the theoretical results.

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.