基于状态空间模型的网络化广义预测控制

针对网络化控制系统中存在的网络诱导时延和数据包丢失,考虑了基于状态空间模型的网络化广义预测控制问题,提出一种采用最小预测步长和预测控制向量分别补偿网络诱导时延和数据包丢失对系统性能影响的新方法.分别给出了存在数据包丢失、网络诱导时延以及两者同时存在情况下的控制器设计方法.仿真实验结果验证了所提出算法的有效性.     

面向网络诱导时延和数据包丢失补偿的网络化广义预测控制

针对网络化控制系统中存在的网络诱导时延和数据包丢失, 考虑了网络化广义预测控制问题. 基于多个数据打包传送的通讯方式以及网络诱导时延和数据包丢失预先可知的假设, 提出了一种采用最小预测步长和预测控制增量向量分别补偿网络诱导时延和数据包丢失对系统性能影响的新方法, 给出了相应的网络化模型预测算法和网络化滚动优化算法, 对于被控对象参数未知或缓慢变化的情况, 给出了基于递推最小二乘辨识改进算法的网络化反馈修正算法, 通过仿真验证了所提出网络化算法的有效性.     

网络化最优预测状态估计

当网络诱导时延和数据包丢失确定可知时,提出了一种网络化最优预测状态估计器设计方法,能够补偿网络诱导时延和数据包丢失对估计性能的影响,理论分析表明了随着网络诱导时延或数据包丢失的增加,该估计器在获得明显补偿效果的同时预测估计偏差略微递增,并给出了估计系统的稳定性条件,最后通过仿真和实验验证了所提出方法的有效性和理论分析的正确性.     

面向数据包丢失补偿的网络化广义预测控制

针对网络化控制系统中存在的数据包丢失,考虑了基于状态空间模型的网络化广义预测控制问题;在假设反馈通道和控制通道的数据包丢失过程确定可知的情况下,提出了一种采用预测器和预测控制器分别补偿反馈通道和控制通道的数据包丢失对系统性能影响的方法,通过把广义预测控制问题转化为滚动线性二次型最优跟踪问题,基于动态规划给出了网络化广义预测控制器的设计方法,并基于Ricoati差分方程非负定解的单调性,给出了末端加权矩阵保证系统稳定性的充分条件,最后通过仿真验证了所提出方法的有效性.     

网路化双线性系统的预测控制优化算法研究

本文对一类离散时间双线性系统进行网络化预测控制研究.针对控制系统网络信道传输引起的前向通道和反馈通道时延问题,基于双线性系统结构特性提出2种逐步优化算法对非凸优化问题进行求解,进而得到未来时刻的预测控制序列.仿真实例说明所求预测控制序列可以主动补偿网络引起的时延问题,从而说明所提出预测控制算法的有效性.     

基于GPC算法的网络控制系统研究

针对具有随机时延的一类网络控制系统(NCS),文章设计了一种基于时延补偿和广义预测控制(GPC)算法的控制器。该控制器根据数据包的时间戳计算传感器-控制器时延,通过时延补偿得到被控对象当前的状态和输出,采用GPC算法计算控制量。仿真结果证实了该控制器的有效性。     

具有随机时延和丢包补偿的NCS的H∞控制

给出一个存在随机时延和数据包丢失的网络控制系统（Networked Control System, NCS）模型，并分析了其渐近稳定的LMI条件．为了降低数据包丢失对系统稳定性的影响，在系统中增加了补偿器，并建立了具有丢包补偿器和随机网络诱导时延的NCS模型．在此模型的基础上，给出了系统渐近稳定和γ次优、最优的充分条件，并且获得了系统最优H∞控制的输出反馈控制律．对同一算例进行Matlab仿真，结果表明具有丢包补偿器的NCS趋于稳定的速度更快．     

具有传感器增益退化、传输时延和丢包的离线状态估计器

研究了具有传感器增益退化、数据传输时延和丢包的网络化状态估计问题,传感器增益退化现象通过统计特性已知的随机变量来描述,数据包时延和丢失发生于传感器量测输出向远程处理中心传送过程中,将各时延的发生描述为随机过程,在远程处理中心端建立只存储最新时刻数据包的时延-丢包模型,考虑到利用每一时刻实时的时延值和丢包情况,设计了一种离线的无偏估计器,推导出最小方差原则下的离线最优估计器增益.最后,通过算例仿真验证所设计离线状态估计器的有效性.     

基于双观测器的网络控制系统稳定性分析

网络控制系统存在网络诱导时延和数据包丢失等问题,使网络控制系统控制性能下降甚至导致系统不稳定,同时在实际应用中存在双闭环的情况,并且一些系统的状态不可测量。针对上述问题,设计2个状态观测器,利用测量输出进行状态重构,并采用状态观测器对丢包进行补偿,应用指数稳定定理分析整个系统的闭环稳定性,给出状态控制率的求解方法。仿真结果证明,该方法能有效补偿网络控制系统的性能,保证在时延和有数据包丢失情况下的网络控制品质。     

网络化多智能体主从式预测编队控制

为解决通讯延时对编队控制造成的不利影响,研究网络化多智能体在通讯延时情形下的主从式预测编队控制问题,提出一种主从式预测编队控制架构.在该架构中,所有智能体都基于延时状态预测自身当前时刻状态,用于主动补偿反馈通道延时.主智能体将自身未来预测状态发送给各从智能体,从而主动补偿主从智能体间的通讯延时.仿真结果验证了所提出主从式预测编队控制架构的可行性和灵活性.     

Dynamic output feedback control for uncertain networked control systems with random network-induced delays

This paper investigates the stabilization problem for a class of uncertain networked control systems (NCSs) with random communication network-induced delays. A dynamic output feedback controller is designed for the uncertain NCSs in the presence of network effects, i.e., network-induced delays and packet dropouts in both the sensor-controller and controller-actuator channels. Based on the Lyapunov-Razumikhin method, the existence of such controller is given in terms of the solvability of bilinear matrix inequalities. An iterative algorithm is proposed to change this non-convex problem into quasi-convex optimization problems, which can be solved effectively by available mathematical tools. The effectiveness of the proposed design methodology is verified by a numerical example.     

Improved synthesis method for network-based control

A less conservative stability analysis condition for closed-loop delayed linear systems subjected to uncertain, bounded, non-differentiable, additive time delays is presented. The obtained stability condition is applied to the problem of networked control system robust design in the presence of network-induced delays and data packet dropouts. Illustrative examples are provided to show the advantage and applicability of the developed results in this case.     

Tracking Control of Multi-Agent Systems Using a Networked Predictive PID Tracking Scheme

With the rapid development of network technology and control technology, a networked multi-agent control system is a key direction of modern industrial control systems, such as industrial Internet systems. This paper studies the tracking control problem of networked multi-agent systems with communication constraints, where each agent has no information on the dynamics of other agents except their outputs. A networked predictive proportional integral derivative(PPID) tracking scheme is proposed t...     

Stability analysis of model-based networked distributed control systems

Networked distributed control systems (NDCSs) face serious challenges such as delays and packet dropouts induced by the communication network employed to connect local controllers of interacting subsystems. These two network-induced shortcomings may degrade the performance or even destabilize NDCSs. This paper is concerned with the problem of stability analysis and stabilization of the NDCSs, featuring both random delay and random packet loss in their communication networks. A model-based networked distributed control framework is proposed to stabilize the NDCS consisting of discrete-time subsystems interconnected through their states. In this control framework, to compensate for the adverse effects of these two network-induced shortcomings, an interaction estimator is provided in each local controller; in addition to a main control unit. This estimator uses the explicit model of the subsystems to estimate the evolution of the states of interacting subsystems, when information about their actual values is not available. A model for the NDCS subject to both random packet loss and random delay is developed. By providing a 3-step interaction estimating algorithm, the closed-loop model-based networked distributed control system (MB-NDCS) is formulated as a time-dependent impulsive system. Then, a quadratic Lyapunov function is constructed to derive a linear matrix inequality (LMI) based sufficient condition for stability analysis of the overall impulsive system. Finally, an illustrative example of a network of interconnected chemical reactors with recycle is presented to show the effectiveness of the proposed approach.     

An output formation consensus control for leader–follower networked multi-agent systems under communication constraints and switching topologies

In this paper, the formation consensus problem for a class of leader–follower networked multi-agent systems under communication constraints and switching topologies is investigated. A networked predictive control scheme is proposed to achieve stability and output formation consensus with the switching topology, capable of compensating for data loss and time delays in the network. By equating the whole closed-loop networked multi-agent system with the proposed control scheme to the corresponding switched system, the sufficient and necessary condition of output formation consensus and stability for agents is given. Finally, using three-degree-of-freedom air-bearing spacecraft simulators as the control objects, the proposed scheme is demonstrated to be able to actively compensate for the communication constraints through numerical simulations, and it is also verified to have a good control performance by further realizing the formation task of the simulators through practical experiments.     

Robust <Emphasis Type="Italic">H</Emphasis><Subscript>∞</Subscript> state feedback control of NCSs with Poisson noise and successive packet dropouts

This paper examines various constraints of networked control systems (NCSs) such as network-induced random delays, successive packet dropouts and Poisson noise. Time delays are represented as modes of Markov chain and successive packet dropouts are modeled using Poisson probability distribution. For each delay-mode, a separate Poisson distribution is used with the help of an indicator function. Poisson noise is incorporated in the design to cater sudden network link failures and power shutdowns. After modeling these constraints, a stability criterion is proposed by using Lyapunov-Krasovskii functional. On the basis of the stability criteria, sufficient conditions for the existence of a robust H _∞ state feedback controller are given in terms of bilinear matrix inequalities (BMIs). Later, BMIs are converted into quasi-convex linear matrix inequalities (LMIs) and are solved by using a cone complementarity linearizing algorithm. The effectiveness of the proposed scheme is elaborated with the help of two simulation examples. Moreover, the effects of successive packet dropouts and Poisson noise on H _∞ performance are analyzed.     

Admissible consensus for networked singular multi-agent systems with communication delays

This study concerns the admissible consensus problem for networked singular multi-agent systems with communication delays and agents described by general singular systems. Only the information of outputs is available through the network. An observer-based networked predictive control scheme (NPCS) is employed to compensate for the communication delays actively. Based on NPCS and dynamic compensator (dynamic output feedback), a novel protocol is proposed. Based on graph, algebra and singular system theory, the necessary and sufficient conditions are given to guarantee existence of the proposed protocol. The conditions depend on the topologies of singular multi-agent systems and the structure properties of each agent dynamics. Moreover, a consensus algorithm is provided to design the predictive protocol. A numerical example demonstrates the effectiveness of compensation for networked delays.     

An Optimal Hybrid Learning Approach for Attack Detection in Linear Networked Control Systems

A novel learning-based attack detection and estimation scheme is proposed for linear networked control systems (NCS), wherein the attacks on the communication network in the feedback loop are expected to increase network induced delays and packet losses, thus changing the physical system dynamics. First, the network traffic flow is modeled as a linear system with uncertain state matrix and an optimal Q-learning based control scheme over finite-horizon is utilized to stabilize the flow. Next, an adaptive observer is proposed to generate the detection residual, which is subsequently used to determine the onset of an attack when it exceeds a predefined threshold, followed by an estimation scheme for the signal injected by the attacker. A stochastic linear system after incorporating network-induced random delays and packet losses is considered as the uncertain physical system dynamics. The attack detection scheme at the physical system uses the magnitude of the state vector to detect attacks both on the sensor and the actuator. The maximum tolerable delay that the physical system can tolerate due to networked induced delays and packet losses is also derived. Simulations have been performed to demonstrate the effectiveness of the proposed schemes.      

Markov-chain-based output feedback control for stabilization of networked control systems with random time delays and packet losses

This paper proposes an output feedback method to stabilize and control networked control systems (NCSs). Random time delays and packet losses are treated separately when an NCS is modeled. The random time delays in the controller-to-actuator and sensor-to-controller links are modeled with two time-homogeneous Markov chains, while the packet losses are treated by the Dirac delta functions. An asymptotic mean-square stability criterion is established to compensate for the network-induced random time delays and packet losses in both the controller-to-actuator and sensor-to-controller links simultaneously. An algorithm to implement the asymptotic mean-square stability criterion is also proposed. Further, a DC-motor speed-control test bed with Ethernet using User Datagram Protocol (UDP) is constructed and employed for experimental verification. Two sets of experiments, with and without 10% packet losses in the links, are conducted on this NCS. Experimental results illustrate the effectiveness of the proposed output feedback method compared to conventional controllers. This method could compensate for the effects of the random time delays and packet losses and guarantee the system performance and stability. The integral time and absolute error (ITAE) of the experiments without packet losses is reduced by 13% with the proposed method, and the ITAE of experiments with 10% packet losses, by 30%. The NCS can track the reference command faithfully with the proposed method when random time delays and packet losses exist in the links, whereas the NCS fails to track the reference command with the conventional control algorithms.     

Event‐triggered predictive control for networked control systems with network‐induced delays and packet dropouts

This paper presents an event‐triggered predictive control approach to stabilize a networked control system subject to network‐induced delays and packet dropouts, for which the states are not measurable. An observer‐based event generator is first designed according to the deviation between the state estimation at the current time and the one at the last trigger time. A predictive control scheme with a selector is then proposed to compensate the effect of network‐induced delays and packet dropouts. Sufficient conditions for stabilization of the networked control system are derived by solving linear matrix inequalities and the corresponding gains of the controller and the observer are obtained. It is shown that the event‐triggered implementation is able to realize reduction in communication and save bandwidth resources of feedback channel networks. A simulation example of an inverted pendulum model illustrates the efficacy of the proposed scheme.