Distributed-observer-based cooperative control for synchronization of linear discrete-time multi-agent systems

This paper considers output synchronization of discrete-time multi-agent systems with directed communication topologies. The directed communication graph contains a spanning tree and the exosystem as its root. Distributed observer-based consensus protocols are proposed, based on the relative outputs of neighboring agents. A multi-step algorithm is presented to construct the observer-based protocols. In light of the discrete-time algebraic Riccati equation and internal model principle, synchronization problem is completed. At last, numerical simulation is provided to verify the effectiveness of the theoretical results.     

Distributed optimal coordination control for nonlinear multi-agent systems using event-triggered adaptive dynamic programming method

This paper is concerned with the design of distributed optimal coordination control for nonlinear multi-agent systems (NMASs) based on event-triggered adaptive dynamic programming (ETADP) method. The method is firstly introduced to design the distributed coordination controllers for NMASs, which not only avoids the transmission of redundant data compared with traditional time-triggered adaptive dynamic programming (TTADP) strategy and minimizes the performance function of each agent. The event-triggered conditions are proposed based on Lyapunov functional method, which is deduced by guaranteeing the stability of NMASs. Then a new adaptive policy iteration algorithm is presented to obtain the online solutions of the Hamiton–Jocabi–Bellman (HJB) equations. In order to implement the proposed ETADP method, the fuzzy hyperbolic model based critic neural networks (NN) are utilized to approximate the value functions and help calculate the control policies. In critic NNs, the NN weight estimations are updated at the event-triggered instants leading to aperiodic weight tuning laws so that computation cost is reduced. It is proved that the weight estimation errors and the local neighborhood coordination errors is uniformly ultimately bounded (UUB). Finally, two simulation examples are provided to show the effectiveness of the proposed ETADP method.     

Distributed adaptive containment control of uncertain QUAV multiagents with time-varying payloads and multiple variable constraints

This paper considers the containment control problem for uncertain QUAV (Quadrotor Unmanned Aerial Vehicle) multiagents with time-varying payloads under a fixed topology graph, and a distributed adaptive containment control protocol with multiple variable constraints is proposed. Generally, the control framework is classified into two layers. In the first layer, the desired trajectories are determined for followers by the communication topology and initial values of leaders. For the second layer, the ith QUAV follower is required to track the desired trajectory by employing the information of itself and neighbors. Under the second layer, the system of the ith agent is decoupled into two subsystems: the translational subsystem and the rotational subsystem. For the translational subsystem, the distributed adaptive containment controller is designed via dynamic surface control method to track the desired position trajectory. With such method, the information requirement of ith agent for its neighbors can be reduced significantly. For the rotational subsystem, the adaptive tracking controller is constructed to track the desired attitudes derived from translational subsystem through commonly used attitudes extraction algorithms. In the end, the resulting closed-loop system is proved to be stable in the sense of uniformly ultimate boundness, and the effectiveness of the proposed approach is illustrated by numerical simulations.     

神经网络模型参考自适应控制在污水处理中的仿真研究

污水处理厂目前广泛使用序批式活性污泥法处理污水.该方法是一种复杂动态生物反应过程,难以建立准确的数学模型,同时采用常规的PID控制难以达到较好的控制品质.针对以上问题,该文提出了RBF神经网络模型参考自适应控制策略,利用神经网络辨识器对污水处理模型进行辨识,使神经网络控制器不依赖被控对象精确的数学模型.仿真结果表明,该...     

基于模型参考自适应控制的直线电机位置控制

针对直线电机的强非线性和时变特性,采用模型参考自适应控制(MRAC)方法对SISO直线电机闭环位置控制器进行了研究。利用偶极子对消建立了简化的永磁直线电机二阶数学模型,提出了基于局部参数最优化MIT(梯度)方案和全局稳定性理论的Lyapunov方案下的二阶直线电机位置模型参考自适应控制器,并对自适应控制器下的直线电机闭环系统稳定性进行了分析研究。在相同的前馈加反馈的控制器下,对这两种方案下的实验结果进行了对比分析。研究结果表明,基于Lyapunov第二方法设计的二阶控制器比MIT方法下的二阶控制器更能实现对三阶点到点轨迹输入信号的快速响应和跟踪,证实了直线电机位置自适应控制的有效性。     

Robust adaptive fault-tolerant control for leader-follower flocking of uncertain multi-agent systems with actuator failure

In this work, we study the flocking problem of multi-agent systems with uncertain dynamics subject to actuator failure and external disturbances. By considering some standard assumptions, we propose a robust adaptive fault tolerant protocol for compensating of the actuator bias fault, the partial loss of actuator effectiveness fault, the model uncertainties, and external disturbances. Under the designed protocol, velocity convergence of agents to that of virtual leader is guaranteed while the connectivity preservation of network and collision avoidance among agents are ensured as well.     

基于BP神经网络的模型参考自适应PID控制器的研究

基于BP神经网络误差的传播机制,探讨建立在BP神经网络基础上的模型参考自适应控制与传统的PID控制相结合的控制方法,控制器通过在线的自学习不断进行适应性控制,以保证系统的输出符合期望的性能要求。用MATLAB软件仿真后表明,该方法具有方法简单,实时跟踪误差,易于实现等优点。     

Multi-formation control of nonlinear leader-following multi-agent systems

This paper deals with the multi-formation control problem for nonlinear leader-following multi-agent systems. Both the fixed topology case and the switching topology case are considered. The neighbor-based multi-formation control protocols are proposed under the assumption that for one subgroup, the total information received from other subgroups is zero. Then, based on the Lyapunov stability theory combined with the algebraic graph theory, sufficient conditions are established to ensure that the leader-following multi-agent systems with nonlinear dynamics can reach and maintain the desired multi-formation control. Finally, simulation examples are provided to illustrate the effectiveness of the theoretical results.     

Event-triggered decentralized adaptive fault-tolerant control of uncertain interconnected nonlinear systems with actuator failures

This paper investigates the event-triggered decentralized adaptive tracking problem of a class of uncertain interconnected nonlinear systems with unexpected actuator failures. It is assumed that local control signals are transmitted to local actuators with time-varying faults whenever predefined conditions for triggering events are satisfied. Compared with the existing control-input-based event-triggering strategy for adaptive control of uncertain nonlinear systems, the aim of this paper is to propose a tracking-error-based event-triggering strategy in the decentralized adaptive fault-tolerant tracking framework. The proposed approach can relax drastic changes in control inputs caused by actuator faults in the existing triggering strategy. The stability of the proposed event-triggering control system is analyzed in the Lyapunov sense. Finally, simulation comparisons of the proposed and existing approaches are provided to show the effectiveness of the proposed theoretical result in the presence of actuator faults.     

Distributed MPC based consensus for single-integrator multi-agent systems

This paper addresses model predictive control schemes for consensus in multi-agent systems (MASs) with discrete-time single-integrator dynamics under switching directed interaction graphs. The control horizon is extended to be greater than one which endows the closed-loop system with extra degree of freedom. We derive sufficient conditions on the sampling period and the interaction graph to achieve consensus by using the property of infinite products of stochastic matrices. Consensus can be achieved asymptotically if the sampling period is selected such that the interaction graph among agents has a directed spanning tree jointly. Significantly, if the interaction graph always has a spanning tree, one can select an arbitrary large sampling period to guarantee consensus. Finally, several simulations are conducted to illustrate the effectiveness of the theoretical results.     

分数阶模型参考自适应控制的Matlab设计

介绍了分数阶模型参考自适应控制算法的Matlab实现。利用Oustaloup算法设计了simulink仿真结构图,并进行了仿真研究。通过参数选择可以取得比用传统控制更好的控制效果,仿真实例也验证了该控制的有效性。该控制系统具有较快的响应时间,较小的超调量以及很好的鲁棒性。     

Global adaptive control for uncertain nonaffine nonlinear hysteretic systems

In this paper, the global output tracking is investigated for a class of uncertain nonlinear hysteretic systems with nonaffine structures. By combining the solution properties of the hysteresis model with the novel backstepping approach, a robust adaptive control algorithm is developed without constructing a hysteresis inverse. The proposed control scheme is further modified to tackle the bounded disturbances by adaptively estimating their bounds. It is rigorously proven that the designed adaptive controllers can guarantee global stability of the closed-loop system. Two numerical examples are provided to show the effectiveness of the proposed control schemes.     

Stabilizing model predictive control for constrained nonlinear distributed delay systems

In this paper, a model predictive control scheme with guaranteed closed-loop asymptotic stability is proposed for a class of constrained nonlinear time-delay systems with discrete and distributed delays. A suitable terminal cost functional and also an appropriate terminal region are utilized to achieve asymptotic stability. To determine the terminal cost, a locally asymptotically stabilizing controller is designed and an appropriate Lyapunov-Krasoskii functional of the locally stabilized system is employed as the terminal cost. Furthermore, an invariant set for locally stabilized system which is established by using the Razumikhin Theorem is used as the terminal region. Simple conditions are derived to obtain terminal cost and terminal region in terms of Bilinear Matrix Inequalities. The method is illustrated by a numerical example.     

Model reference adaptive control of air-lubricated capstan drive for precision positioning

Because friction-induced nonlinearities in positioning systems are generally range of motion-dependent, dual-model or dual-stage strategies are often adopted to deal with the inconsistencies encountered when a system moves from submicrometer steps (micro mode) to larger scale strokes (macro mode). Although good performance is usually obtained when each model/stage operates in its designed range of motion, a system frequently performs less satisfactorally when operating near the switching point between models or stages. An air-lubricated capstan drive was used in this study to minimize the discrepancy between macro and micro modes, and a single-mode MRAC was developed to control the capstan drive system for precision positioning. Accuracy better than ±15 nm with no overshooting was achieved in all conditions tested (including 50 nm, 500 nm and 10 μm steps). Disturbance resistance of the system also proved to be satisfactory.     

Distributed output-feedback consensus control of multi-agent systems with dynamically changing directed interaction topologies

This paper considers the distributed output-feedback consensus control problem for a multi-agent system with higher order linear dynamics and subject to external disturbance, under dynamically changing directed topologies and weighting factors. An extended state observer (ESO) is first designed to estimate not only the unmeasurable agent states but also the external disturbance. Based on the output of the ESO, a novel distributed control protocol is proposed. We show that, with the application of the proposed control protocol, the consensus can be achieved asymptotically by the group of agents if the union of the directed interaction graphs contains a spanning tree frequently enough. A numerical example is given to verify the effectiveness of the theoretical results.     

Speed sensorless model predictive current control of doubly-fed induction machine drive using model reference adaptive system

This paper presents a speed sensorless control scheme named as finite control set-model predictive current control (FCS-MPCC) using a modified fictitious ohmic quantity (R) based model reference adaptive system (MRAS) for grid-connected doubly-fed induction machine (DFIM) drive. The variables of the reference model of this speed sensorless scheme (R-MRAS) are represented in stationary reference frame while those for the adaptive model are denoted in synchronously rotating reference frame. The sensorless formulation thus obtained is completely independent of any stator/rotor resistance terms. The scheme is also devoid of any stator/rotor flux estimation. Moreover, the intuitiveness of FCS-MPCC brings in additional flexibility in comparison to the conventional control techniques like field oriented control (FOC) and direct torque control (DTC). The overall scheme demonstrates faster execution time than FOC/DTC based control of DFIM drive. The proposed control algorithm is simulated and tested for limited speed range application in MATLAB/Simulink. The validation of simulation results are further done by experimentation on a dSPACE-1103 based DFIM laboratory setup.     

A new discrete-time robust adaptive time-delay control for a class of uncertain nonlinear strict-feedback systems using sliding mode

This paper presents a new discrete-time adaptive second-order sliding mode control with time delay estimation (TDE) for a class of uncertain nonlinear time-varying strict-feedback systems. The existing researches on time delay control (TDC) are conventionally established based on a stability criterion that is subject to the infinitesimal time delay assumption. Recently, this criterion was rejected and a new criterion was proposed for the development of a controller for systems with fully known dynamics. In this study, this approach is extended to uncertain systems. Specifically, a new criterion is developed for the stability of the TDE-error within an adaptive robust controller design without the infinitesimal time delay assumption. With the proposed adaptive robust control, there is no need for determination of uncertainties upper-bounds. Simulation results illustrate the efficacy of the proposed controller.