不可靠WSN时钟同步网络化输出反馈MPC量化分析

在Cyber-Physical环境下,时钟同步双向信息交换过程中,包含时钟信息的数据包丢失将对时钟同步性能产生影响。讨论了现代控制理论状态空间模型的输出反馈Tubes-MPC时钟同步方法。由分离原理,设计了本地化的状态估计器与控制器,实现了输出反馈Tubes-MPC时钟同步的指数稳定。以不完全量测下的观测模型为基础,定量分析了统计意义下的同步误差方差上界与下界,并采用MPC中Set-Theory-in-Control方法,将完全量测下的干扰误差集合运算于由丢包所引入的附加的估计误差集合,建立了集合约束下的模型预测优化模型。已构建的统一框架下的输出反馈Tubes-MPC时钟同步系统化方法,综合考量了控制理论在线计算复杂度与网络控制观点应用的可行性,对无线网络的不可靠性、网络规模、收敛性能具有鲁棒性,进一步容易扩展为网络级绝对时钟状态空间模型。     

Robust output feedback distributed model predictive control of networked systems with communication delays in the presence of disturbance

In this work, an output feedback cooperative distributed model predictive control is developed for a class of networked systems composed of interacting subsystems interconnected through their states, in which it handles bounded disturbances and time varying communication delays. A distributed buffer based prediction strategy is used to compensate bounded delays and predict those states, which are coupled between subsystems that their actual values may not available due to delays. In the design of robust distributed model predictive control, distributed moving horizon estimation is employed so that convergence and boundedness of the estimation error are ensured. Furthermore, robust exponential stability of the closed loop system is established. The effectiveness of the proposed method is illustrated using two interconnected continuous stirred tank reactors.     

Output feedback model predictive control of hydraulic systems with disturbances compensation

Enhancing the robustness of output feedback control has always been an important issue in hydraulic servo systems. In this paper, an output feedback model predictive controller (MPC) with the integration of an extended state observer (ESO) is proposed for hydraulic systems. The ESO was designed to estimate not only the unmeasured system states but also the disturbances, which will be synthesized into the design of the output prediction equation. Based on the mechanism of receding horizon and repeating optimization of MPC, the output prediction equation will be updated in real time and the future behavior of the system will be accurately predicted since the disturbances are compensated effectively. Hence, the ability of the traditional MPC to suppress disturbances will be improved evidently. The experiment results show that the proposed controller has high-performance nature and strong robustness against various model uncertainties, which verifies the effectiveness of the proposed control strategy.     

Constrained off-line synthesis approach of model predictive control for networked control systems with network-induced delays

This paper investigates the off-line synthesis approach of model predictive control (MPC) for a class of networked control systems (NCSs) with network-induced delays. A new augmented model which can be readily applied to time-varying control law, is proposed to describe the NCS where bounded deterministic network-induced delays may occur in both sensor to controller (S–A) and controller to actuator (C–A) links. Based on this augmented model, a sufficient condition of the closed-loop stability is derived by applying the Lyapunov method. The off-line synthesis approach of model predictive control is addressed using the stability results of the system, which explicitly considers the satisfaction of input and state constraints. Numerical example is given to illustrate the effectiveness of the proposed method.     

Iterated non-linear model predictive control based on tubes and contractive constraints

This paper presents a predictive control algorithm for non-linear systems based on successive linearizations of the non-linear dynamic around a given trajectory. A linear time varying model is obtained and the non-convex constrained optimization problem is transformed into a sequence of locally convex ones. The robustness of the proposed algorithm is addressed adding a convex contractive constraint. To account for linearization errors and to obtain more accurate results an inner iteration loop is added to the algorithm. A simple methodology to obtain an outer bounding-tube for state trajectories is also presented. The convergence of the iterative process and the stability of the closed-loop system are analyzed. The simulation results show the effectiveness of the proposed algorithm in controlling a quadcopter type unmanned aerial vehicle.     

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.     

基于隐马尔可夫的网络控制系统稳定性分析

讨论了一类具有随机通信时延的网络控制系统的建模及稳定性分析,其中网络诱导时延受控于一概率分布未知的马尔可夫链,其概率分布可通过Baum-Welch算法计算.基于隐马尔町夫模型理论,将采用状态反馈的闭环网络控制系统建模成跳变线性系统,给出了这类网络控制系统随机稳定的允分条件,并将状态反馈控制器的求解问题转化为线性矩阵不等式的解的问题.最后,通过一个仿真算例说明了上述判定系统稳定性条件的有效性.     

一种克服模型参数失配的广义预测控制算法

针对模型参数失配对广义预测控制输出的影响,提出了一种输出增量反馈的广义预测控制简化算法.该算法通过引入一个输出增量速度函数,设计了输出增量参考序列,以控制输出增量的方式间接控制系统输出;同时利用阶梯控制方式,对输入增量引入柔化系数矩阵进行约束,既避免了传统预测控制律中逆矩阵的求解,减少了计算量,又防止了控制量的剧烈变化;最后引入控制增量增益,利用这个自由度提高了系统的鲁棒稳定性.仿真结果表明:该预测控制简化算法能有效克服模型参数失配带来的影响,抑制系统输出调整过程中的输出波动,缩短调整时间,提高系统的动态特性,并抑制系统控制输入的剧烈变化.     

Robust model predictive control for switched linear systems

Developed is a robust model predictive control scheme for a class of discrete-time switched linear systems. The system is described in linear fractional transformation form in the presence of model uncertainty and induced norm bounded disturbances. The objective is to minimize the upper bound of an infinite horizon cost function subject to a terminal inequality. A Lyapunov function analysis for the switched system shows guaranteed closed-loop stability. Taking into account the switching structure of the system, the predictive control design problem along with sufficient conditions for the existence of a solution is expressed in terms of Riccati–Metzler inequalities. Then, these inequalities are turned into a linear matrix inequality feasibility problem. Three cases are analyzed to demonstrate the performance and effectiveness of the proposed robust model predictive controller for switched discrete-time linear systems.     

Distributed model predictive control for constrained nonlinear systems with decoupled local dynamics

This paper considers the distributed model predictive control (MPC) of nonlinear large-scale systems with dynamically decoupled subsystems. According to the coupled state in the overall cost function of centralized MPC, the neighbors are confirmed and fixed for each subsystem, and the overall objective function is disassembled into each local optimization. In order to guarantee the closed-loop stability of distributed MPC algorithm, the overall compatibility constraint for centralized MPC algorithm is decomposed into each local controller. The communication between each subsystem and its neighbors is relatively low, only the current states before optimization and the optimized input variables after optimization are being transferred. For each local controller, the quasi-infinite horizon MPC algorithm is adopted, and the global closed-loop system is proven to be exponentially stable.     

A new approach to event-triggered static output feedback control of networked control systems

This paper is concerned with the event-triggered static output feedback control of networked control systems. The event-triggered mechanism is represented by a time-delay model and some latest techniques are employed to deal with the induced time-delay. Furthermore, a novel strategy is developed to eliminate the coupling among control gain, input matrix and output matrix. With these techniques, a new sufficient condition for system stability is established in the framework of linear matrix inequalities. The effectiveness of the proposed method is shown by two numerical examples.     

基于T-S模糊模型的非线性系统广义预测控制

针对离散非线性系统,提出一种基于T-S模糊模型的广义预测控制方法。该方法将采样点的T-S模糊模型转化为采样点线性模型与非线性误差叠加的线性形式,通过迭代修正非线性误差,使具有非线性误差的线性模型预测控制律逐渐逼近采样点T-S模糊模型预测控制律。同时,该预测控制方法也能适用于当系统受输入输出约束时的控制。仿真结果验证了所提出的TS模糊模型广义预测方法有效。     

网络控制系统传输模型和服务质量的研究与仿真

在网络控制系统中,传输网络的服务质量对整个控制系统的稳定和性能的提高至关重要。总结了当前普通网络中的服务质量技术特性,详细地研究了网络的传输协议、传输模型及传输处理过程,并对服务质量的影响进行了仿真,给出了结论。     

Decentralized adaptive control of interconnected nonlinear systems with unknown control directions

In this paper, we propose a decentralized adaptive control scheme for a class of interconnected strict-feedback nonlinear systems without a priori knowledge of subsystems' control directions. To address this problem, a novel Nussbaum-type function is proposed and a key theorem is drawn which involves quantifying the interconnections of multiple Nussbaum-type functions of the subsystems with different control directions in a single inequality. Global stability of the closed-loop system and asymptotic stabilization of subsystems' output are proved and a simulation example is given to illustrate the effectiveness of the proposed control scheme.     

Disturbance-observer-based fuzzy model predictive control for nonlinear processes with disturbances and input constraints

This paper proposes a disturbance-observer-based fuzzy model predictive control (DOBFMPC) scheme for the nonlinear process subject to disturbances and input constraints. The proposed control scheme is composed of the baseline fuzzy model predictive control (FMPC) law designed on the Takagi–Sugeno fuzzy model and the disturbance compensation law. To build a fuzzy model of appropriate complexity and accuracy for the nonlinear process model, a systematic approach is developed via the gap metric to determine the linearization points. With FMPC, the asymptotic stability is theoretically proved, and the input constraints are satisfied by both the free control variables and the future control inputs in the form of the state feedback law. The disturbance compensation gain is designed such that the influence of the disturbance is removed from the output channels by the composite DOBFMPC law at the steady state. The application to a subcritical boiler–turbine system demonstrate the effectiveness of the proposed control scheme.     

一类网络控制系统的稳定性分析

在基于多包传输的网络控制系统中,传感器采用时间驱动,控制器和执行器采用事件驱动.假定传输时延可以忽略,则整个网络控制系统可以描述为一个具有N个事件的异步动态系统.该文针对受控对象状态均可测,控制律采用输出反馈的情况,利用双线性矩阵不等式方法,讨论了网络控制系统指数稳定的问题,并给出了稳定性的充分条件,最后通过仿真实验加以验证.     

基于神经网络的非线性系统约束预测控制

利用非线性激励函数的局部线性表示,提出一种可用于非线性过程的基于神经网络模型的约束广义预测控制算法。该算法将非线性搜索转化为只对当前控制增量的约束,避免了非线性优化求解,并不需要很多的计算量。文中给出了仿真结果。     

Robust fault-tolerant control for networked control systems subject to random delays via static-output feedback

This paper focuses on the problem of fault-tolerant controller (FTC) design for uncertain networked control systems (NCSs) with random delays and actuator faults. A new fault model is proposed to represent more class of actuator faults. More precisely, the NCSs with random delays and the possible actuator faults are modeled as a Markovian jump system (MJS) with incomplete transition probabilities (TPs) and then LMI-based sufficient conditions are derived to ensure the stochastic stability of the closed-loop system. The sufficient conditions are constructed to synthesize the mode-dependent static-output feedback (SOF) control laws. Feasibility and reliability of the proposed FTC against actuator faults are indicated through simulation results.     

A distributed model predictive control based load frequency control scheme for multi-area interconnected power system using discrete-time Laguerre functions

This paper proposes a distributed model predictive control based load frequency control (MPC-LFC) scheme to improve control performances in the frequency regulation of power system. In order to reduce the computational burden in the rolling optimization with a sufficiently large prediction horizon, the orthonormal Laguerre functions are utilized to approximate the predicted control trajectory. The closed-loop stability of the proposed MPC scheme is achieved by adding a terminal equality constraint to the online quadratic optimization and taking the cost function as the Lyapunov function. Furthermore, the treatments of some typical constraints in load frequency control have been studied based on the specific Laguerre-based formulations. Simulations have been conducted in two different interconnected power systems to validate the effectiveness of the proposed distributed MPC-LFC as well as its superiority over the comparative methods.