Predictive Event-Triggered Control for Disturbanced Wireless Networked Control Systems

The control and scheduling for wireless networked control system with packet dropout and disturbance are investigated. A prediction based event triggered control is proposed to reduce data transmissions while preserving the robustness against external disturbance. First, a trigger threshold is especially designed to maintain the difference of the estimated and actual states below a proper boundary when system suffers from packet dropout. Then a predictive controller is designed to compensate for packet dropouts by utilizing the packet-based control approach. The sufficient conditions to ensure the closed-loop system being uniformly ultimately bounded are derived, with consequently the controller gain method. Numerical examples illustrate the effectiveness of the proposed approach.     

一类多输入多输出系统的预测PID控制算法仿真

研究了一类参教未知的多变量系统的广义预测PID参数整定问题。基于广义预测控制(GPC)的思想和γGPC与PID的相互关系，提出了一种新的离散多变量系统PID参数整定方法，其中性能指标包含了稳态误差加权项。PID参数通过γGPC与PID的相互关系递推计算得到。仿真例子说明了该方法的有效性和可行性。     

一类MIMO网络控制系统的时滞相关鲁棒控制器设计

针对一类多输入多输出(MIMO)网络控制系统,提出一种时滞相关鲁棒控制器的设计方法.首先经过等价推导,将系统转化成具有多输入时滞的连续系统,利用李雅普诺夫函数,通过求解若干线性矩阵不等式,获得系统时滞相关鲁棒控制器.算法递推简单,避免了进行系统变换和处理交叉项,减少了计算负荷.仿真结果表明:在网络具有一定传输时延的情况下,该方法可以获得满足系统稳定性的控制器.     

一类非线性时滞系统的模糊预测控制

利用模糊T-S模型对一类输入受限的非线性时滞系统进行建模;在此基础上,提出了模糊预测控制,推导了预测性能指标上界,将稳定性约束,输入约束变换成容易求解的线性矩阵不等式形式。采用了并行分布补偿预测控制器,基于李雅普诺夫函数和线性矩阵不等式方法给出滚动时域优化的充分条件,证明了闭环系统的稳定性,仿真结果验证了所提方法的有效性。     

Coordination Control for a Class of Multi-Agent Systems Under Asynchronous Switching

This paper studies the coordination control of nonlinear multi-agent systems under asynchronous switching, including consensus, tracking control, and containment. The asynchronous switching considered here means that the switching of the controller lags behind the mode's switching for each agent. So the matched controller is interrupted by the delayed switching. For the situation, the authors give some new results by applying the conventional distributed control protocol. The authors show that all agents can achieve consensus. Secondly, the authors show that all followers can track the actual leader. Thirdly, the authors show that all followers will converge to the convex hull spanned by the dynamic leaders as time goes on. Numerical simulations are also provided and the results show highly consistent with the theoretical results.     

A Novel Networked Predictive Control Method for Systems with Random Communication Constraints

This paper presents a novel observer-based predictive control method for networked systems where random network-induced delays, packet disorders and packet dropouts in both feedback and forward channels are considered. The proposed method has three significant features: i) A concept of destination-based lumped(DBL) delay is introduced to represent the combined effects of random communication constraints in each channel; ii) in view of different natures of the random DBL delays in the feedback and forward channels, different compensation schemes are designed; and iii) it is actual control inputs rather than predicted ones that are employed to generate future control signals based on the latest system state estimate available in the controller. For the resulting closed-loop system, a necessary and sufficient stability condition is derived, which is less conservative and also independent of random communication constraints in both channels. Simulation results are provided to demonstrate the effectiveness of the proposed method.     

移动机器人网络运动协调的控制与仿真

研究移动机器人网络运动协调的仿真框架与分散控制律的设计。建立了传感范围有限、差速驱动移动机器人网络的数学模型:单个机器人的运动由运动学与动力学方程描述,且驱动力矩和速度有限;有向图和proximity图分别描述机器人间的通信网络和互感网络。设计了基于MATLAB/SIMULINK的运动协调仿真框架,并在此基础上设计了带速度约束的平行运动与自组织编队生成协调控制律。仿真结果证明控制器设计的有效性和仿真框架对不同分散控制律的适用性。     

网络化制造环境下离散供应链系统预测控制策略

针对离散供应链系统中客户需求的高度不确定性，提出最小方差控制方法。该方法相对于传统的预测控制策略，更适合于追踪需求变化减少或消除“牛鞭效应”。首先，将具有z变换的各单元传递函数整合成一个闭环传递函数，以此为整个供应链网络建模，采用白回归移动平均模型描述客户需求趋势，并通过客户需求预测确定两种库存目标水平。其次，建立基于订单策略的目标函数，利用最小方差预测器处理客户需求，提出了供应链的性能指标函数和“牛鞭效应”的分析方程，并通过设定最小方差控制器参数调节超额库存和未交付订货。最后，仿真结果表明最小方差控制在预测市场变化、追踪客户动态需求和保持合理库存水平上是可行和有效的。     

模型预测控制在网络化制造环境下SCM中的应用

针对网络化制造环境下供应链需求不确定的特点,采用模型预测控制技术解决供应链管理中库存的动态优化问题。首先,阐述了模型预测控制的机理及其在供应链动态控制方面的适应性;其次,建立了成本目标优化模型,提出控制法则并给出控制算法;最后,仿真结果表明,模型预测控制技术在预测合理库存水平以及控制动态、不确定的供应链系统是可行的。     

分布式MPC在网络化制造环境下SCM中的应用

针对网络化制造环境下动态供应链管理特点,利用分布式模型预测控制技术解决供应链中动态优化控制问题。首先,阐述动态供应链运行机理,并以此提出完整的随机动态优化控制模型及其控制约束;其次,给出分布式模型预测控制算法,并构建了优化控制序列模型;最后,仿真实例结果表明,利用分布式模型预测控制技术计算供应链中各阶段订货率,可以预测企业各阶段理想库存,从而快速响应市场动态变化,有效控制供应链管理中的不确定性。     

波浪干扰下的AUV纵向运动建模与模型预测控制

针对近水面航行的AUV,研究了其波浪影响下定深控制问题。基于弗劳德—克雷洛夫假设(Froude-Krylov Hypothesis),采用切片理论计算AUV近水面运动中受到的随机波浪干扰力和力矩,并以此作为扰动项建立随机波浪作用下AUV纵向运动的线性化数学模型。采用模型预测控制方法进行仿真研究,使AUV的航行深度和俯仰角达到期望值。仿真结果表明:该方法能够有效提高AUV近水面航行过程中的抗波浪干扰能力,系统具有良好的动态性能。     

Tracking Synchronization of Networked Lagrangian Systems via Impulsive Control and Its Applications

An impulsive control scheme is proposed to investigate the tracking synchronization of ring and inline networked Lagrangian systems. Given a time-varying target trajectory, some algebraic synchronization criteria are derived to make the networked Lagrangian systems synchronize to the target trajectory. A distinctive feature of the proposed work is that the impulsive control scheme is used to investigate the highly nonlinear Lagrangian systems. By the impulsive control, each agent described by the Lagrangian system instantaneously interacts with its neighbors only at some discrete moments. Furthermore, the proposed control strategy requires only local coupling feedback for global convergence. As a direct application of the obtained theoretical results, the tracking synchronization of multiple 3-DOF mobile robots is discussed in detail and simulated. Simulation results verify the effectiveness of the proposed control strategy.     

网络控制系统随机鲁棒控制律设计方法

研究了具有随机网络诱导时延及数据包丢失的网络控制系统的随机鲁棒控制律设计方法.利用有限状态markov链来描述控制网络中固有的随机传输延迟和丢包过程,建立网络系统的多结构markov跳变模型.基于由蒙特卡罗估计和优化算法构成的随机鲁棒设计方法,结合保证系统均方稳定的充要条件,得到网络控制系统的随机鲁棒控制律.最后,某型无人飞行器纵向俯仰通道的网络控制仿真实例验证了该方法的有效性.     

Learning-Based Predictive Control of Switched Nonlinear Systems via Koopman Modeling Approach

This paper proposes a data-driven learning-based approach to predictive control for switched nonlinear systems subject to state and control constraints and external stochastic disturbances. A switched Koopman modeling framework is developed, where a multi-mode neural network for state lifting is trained simultaneously with Koopman operators and state reconstruction matrices for all modes.This framework facilitates the construction of the switched linear Koopman model in a transformed space and effectively captures the dynamics of the original nonlinear system. A switched predictive control strategy is then designed to regulate the switched Koopman model with constrained states and control inputs against both the stochastic disturbances and the uncertainties introduced by the lifting neural network. The proposed control scheme ensures mean-square stability and guarantees boundedness during the online phase. Furthermore, boundedness analysis is performed to determine the bounded set of the original system state across all admissible switching sequences. The effectiveness of the proposed methodology is demonstrated through a case study of a gene regulatory network.     

具有数据包丢失的网络控制系统的估计问题

主要考虑了具有数据包丢失的网络控制系统(NCSs)的估计问题。首先,给出经典的卡尔曼滤波估计器和协方差矩阵。当量测方程带有噪声时,通过递推的方法严格推导出最优估计(条件期望)。另外,根据系统丢包行为能否被观测到的估计问题,分情况进行讨论。最后,在实际应用中开发了一个次优的近似估计器。这对在大的有限域下研究具有数据包丢失的网络控制系统有所帮助,也为进一步分析网络控制系统的问题提供了研究方向。     

一类模型模糊系统的模型参考自适应控制

针对一类模型可用一组模糊规则来描述的系统,提出了一种模型参考自适应控制律。根据 Ｌｙａｐｕｎｏｖ理论证明了闭环系统是稳定收敛的。仿真例子证实了该方法的有效性。     

一类非线性系统的鲁棒自适应控制

针对一类含有不确定参数和未知扰动的非线性系统，提出一种鲁棒自适应控制方法以确保系统输出稳定地精确跟踪给定的参考信号。控制器的设计分两步进行：首先，在不考虑扰动的情况下，采用一种基于参数映射的Lyapunov设计方法设计系统参数自适应控制器；然后，在该自适应控制器的基础上，采用衰减控制策略设计鲁棒补偿器，实现对扰动的抑制。最后通过数字仿真验证了设计方案的有效性。     

不确定网络化控制系统的保性能鲁棒容错控制

研究了一类含有不确定性的网络化控制系统的完整性和保性能容错控制问题.基于Lyapunov稳定性理论和LMI方法,采用状态反馈控制策略,针对含有不确定性的网络化控制系统当执行器发生失效故障时分别推证出了系统仍渐近稳定和能够满足一定控制指标的充分条件,进而通过将矩阵不等式转化为线性矩阵不等式得到了求取两种容错控制器的方法.最后用仿真算例验证了该方法的有效性和可行性.     

多变量系统预测函数解耦控制

提出一种新的多变量系统预测函数解耦控制(PFC)算法。该算法将多变量系统的PFC分散为若干单变量系统的PFC,使参数设计和算法求解大为简化。此外,利用该算法可得到一个解析的控制量计算方程,控制器参数均可离线计算,因此在线时算法简单、计算量小,可用于解决复杂的耦合控制问题。仿真结果表明了该算法的有效性和可行性。     

非最小相位系统预测函数控制

针对开环稳定非最小相位系统(NMPS),提出了一种参考轨迹自调整预测函数控制(PFC策略。由于开环稳定NMPS可以方便地用有限脉冲响应(FIR)模型来描述,因此采用基于FIR模型的PFC对其实施控制,并推广到多变量情形,实现对多变量NMPS的有效控制。为了在减小负调缩短调节时间和减小超调之间达到合理的折中,提出了参考轨迹自调整方案,在系统响应初始阶段采用较大的期望闭环性能特性系数,以减小负调;当系统克服负调进入正常响应阶段,采用适当的期望闭环性能特性系数,以缩短调节时间和减小超调。将该策略应用到水轮机调速系统中,仿真结果表明,系统具有良好的动态性能和较强的鲁棒性。