Asynchronous update based networked predictive control system using a novel proactive compensation strategy

Networked predictive control system (NPCS) has been proposed to address random delays and data dropouts in networked control systems (NCSs). A remaining challenge of this approach is that the controller has uncertain information about the actual control inputs, which leads to the predicted control input errors. The main contribution of this paper is to develop an explicit mechanism running in the distributed network nodes asynchronously, which enables the controller node to keep informed of the states of the actuator node without a priori knowledge about the network. Based on this mechanism, a novel proactive compensation strategy is proposed to develop asynchronous update based networked predictive control system (AUBNPCS). The stability criterion of AUBNPCS is derived analytically. A simulation experiment based on Truetime demonstrates the effectiveness of the scheme.     

Delay-tolerant distributed voltage control for multiple smart loads in AC microgrids

With increasing penetration of variable loads and intermittent distributed energy resources (DERs) with uncertainty and variability in distribution systems, the power system gradually inherits some features (e.g., lack of rotating inertia), which leads to the voltage instability in microgrids. As a means to provide stability support for smart grid against high penetration of intermittent DERs, inverter-based smart loads across the distribution grid has been suggested recently. Accordingly, this paper presents a delay-tolerant distributed voltage control scheme based on consensus protocol for multiple-cooperative smart loads through effective demand-side management in ac microgrids, in which the time-delay effect on transmission communication occurred in information exchanges is considered. The proposed distributed voltage control scheme always enables the output voltage of each smart load to be synchronized to their reference value, which improves the robustness of system stability against transmission communication delays. The Lyapunov–Krasovskii functions are employed to analyze the stability of our proposed distributed control scheme, then the delay-independent stability conditions are derived, which allows some large communication delays. Moreover, the sensitivity analysis is developed to show how the time delay affects system dynamics in order to validate the robustness of proposed delay-independent stability conditions. Furthermore, a sparse communication network is employed to implement the proposed distributed control protocols, which thus satisfies the plug-and-play requirement of smart microgrids. Finally, the simulation results of an ac microgrid in MATLAB/SimPowerSystems are presented to demonstrate the effectiveness of the proposed control methodology.     

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.     

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.     

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.     

云制造环境下基于离散Markov跳变系统的机床装备资源动态优选方法

针对云制造环境下加工任务执行过程中机床装备资源易受紧急插单、加工质量异常、设备运行故障等高频随机扰动影响,致使产品加工服务质量(QoS)不能满足客户个性化需求的问题,提出一种基于离散Markov跳变系统的机床装备资源动态优化选择方法.首先,结合云制造服务运行特点,构建了云制造环境下面向加工任务执行过程的服务质量动态演化...     

基于神经网络的直线电磁阀式怠速系统预测控制方法研究

基于汽油发动机怠速系统的非线性、时变性和不确定性等特点,构建了神经网络与预测算法相结合的控制系统。利用预测控制算法的滚动优化和反馈校正的特性,采用神经网络建立系统的动态模型作为预测控制器的预测模型;提供怠速系统的开环输入输出数据离线训练神经网络,再在线对神经网络模型的权值和阀值进行调整,获得精确的预测模型,实现了对怠速系统的自适应控制。仿真结果表明,这种方法有效地提高了发动机怠速系统的控制精度、可靠性和转速的稳定性。     

Guaranteed cost control of mobile sensor networks with Markov switching topologies

This paper investigates the consensus seeking problem of mobile sensor networks (MSNs) with random switching topologies. The network communication topologies are composed of a set of directed graphs (or digraph) with a spanning tree. The switching of topologies is governed by a Markov chain. The consensus seeking problem is addressed by introducing a global topology-aware linear quadratic (LQ) cost as the performance measure. By state transformation, the consensus problem is transformed to the stabilization of a Markovian jump system with guaranteed cost. A sufficient condition for global mean-square consensus is derived in the context of stochastic stability analysis of Markovian jump systems. A computational algorithm is given to synchronously calculate both the sub-optimal consensus controller gains and the sub-minimum upper bound of the cost. The effectiveness of the proposed design method is illustrated by three numerical examples.     

Passivity-based control framework for task-space bilateral teleoperation with parametric uncertainty over unreliable networks

Bilateral teleoperation systems developed in joint-space or in task-space without taking into account parameter uncertainties and unreliable communication have limited practical applications. In order to ensure stability, improve tracking performance, and enhance applicability, a novel task-space control framework for bilateral teleoperation with kinematic/dynamic uncertainties and time delays/packet losses is studied. In this paper, we have demonstrated that with the proposed control algorithms, the teleoperation system is stable and position tracking is guaranteed when the system is subjected to parametric uncertainties and communication delays. With the transformation of scattering variables, a packet modulation, called Passivity-Based Packet Modulation (PBPM), is proposed to cope with data losses, incurred in transmission of data over unreliable network. Moreover, numerical simulations and experiments are also presented to validate the efficiency of the developed control framework for task-space bilateral teleoperation.     

Deep learning-based smith predictor design for a remote grasping control system

In this study, a robotic hand control system was designed based on data gloves, aiming to provide more intuitive control and improved operational performance for a remote robotic hand. Compensation measures were proposed for the time lag effect on the remote-control system to address the input and feedback time delays of the remote robot system. A Smith predictor structure was modified by replacing the linear estimator with a recurrent neural network. A convolutional neural network was applied to the long short-term memory (LSTM) model, as it had a better convergence time and learning performance than the multi-layer perceptron model during training. The experimental results demonstrate that the control effect of this scheme is approximately 0.5 s faster than the normal Smith predictive control, proving its effectiveness.

     

An approach to predictive control of multivariable time-delayed plant: stability and design issues

In this paper, a new method of multivariable predictive control is presented. The main advantage of a predictive approach is that multivariable plants with time delays can be easily handled. The proposed control algorithm also introduces a compact and simple design in the case of higher-order and nonminimal phase plants, but it is limited to open-loop stable plants. The algorithm of the proposed multivariable predictive control is developed, designed, and implemented on an air-conditioned system. The stability of the proposed control law is discussed.     

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.     

H2 consensus control of time-delayed multi-agent systems: A frequency-domain method

An analytical H2 controller design approach of homogeneous multi-agent systems with time delays is presented to improve consensus performance. Firstly, a closed-loop multi-input multi-output framework in frequency domain is introduced, and a consensus tracking condition is given. Secondly, the decomposition method is utilized to simplify the analysis of internal stability and H2 performance index of the whole system to a set of independent optimization problems. Finally, the H2 optimal controller can be computed from all the stabilizing controllers. The contributions of the new approach are that the design procedure is conducted analytically for arbitrary delayed multi-agent systems, and a simple quantitative tuning way is developed to trade off the nominal performance and robustness. The simulation examples show the effectiveness of the proposed control strategy.     

Real-time mobile robot teleoperation via Internet based on predictive control

A remote control system that can control a mobile robot in real time via the internet is proposed. To compensate for the network delay and counteract its impact on the teleoperation system, a predictive control scheme based on the modified Smith predictor proposed is selected. To ensure the stability and transparency of the system, a dynamic model manager is designed based on the information exchange between the sensors at the master and slave sides. To precisely predict the time delay, a new timer synchronization algorithm is proposed. To decrease delay- jitter, a new data buffer scheme is performed. Force feedback and a virtual predictive display are introduced to enhance the real-time efficiency of teleoperation. The usefulness and effectiveness of the proposed method and system are proven by teleoperation experiments via the internet over a long distance.     

Model-free adaptive integral terminal sliding mode predictive control for a class of discrete-time nonlinear systems

In this paper, a new model-free adaptive digital integral terminal sliding mode predictive control scheme is proposed for a class of nonlinear discrete-time systems with disturbances. The characteristic of the proposed control approach is easy to be implemented because it merely adopts the input and output data model of the system based on compact form dynamic linearization (CFDL) data-driven technique, while the technique of perturbation estimation is applied to estimate the disturbance term of the system. Moreover, by means of combining model predictive control and CFDL digital integral terminal sliding mode control (CFDL-DITSMC), the CFDL digital integral terminal sliding mode predictive control (CFDL-DITSMPC) method is proposed, which can further improve the tracking accuracy and disturbance rejection performance in comparison with the CFDL model-free adaptive control, neural network quasi-sliding mode control and the CFDL-DITSMC scheme. Meanwhile, the stability of the proposed approach is guaranteed by theoretical analysis, and the effectiveness of the proposed method is also illustrated by numerical simulations and the experiment on the two-tank water level control system.     

Adaptive fuzzy wavelet network control of second order multi-agent systems with unknown nonlinear dynamics

In this paper, consensus problem is considered for second order multi-agent systems with unknown nonlinear dynamics under undirected graphs. A novel distributed control strategy is suggested for leaderless systems based on adaptive fuzzy wavelet networks. Adaptive fuzzy wavelet networks are employed to compensate for the effect of unknown nonlinear dynamics. Moreover, the proposed method is developed for leader following systems and leader following systems with state time delays. Lyapunov functions are applied to prove uniformly ultimately bounded stability of closed loop systems and to obtain adaptive laws. Three simulation examples are presented to illustrate the effectiveness of the proposed control algorithms.     

Synchronization of complex dynamical networks with random coupling delay and actuator faults

This paper addresses the issue of passivity-based synchronization problem for a family of Markovian jump neutral complex dynamical networks (NCDNs) with coupling delay and actuator faults. Also, by considering the effect of random fluctuation in complex dynamical network systems, the occurrence of coupling delay are taken in terms of a stochastic distribution, which obeys the Bernoulli distribution. To handle the fault effects in actuators of proposed complex network systems, an actuator fault model is considered. The main objective of this paper is to develop a robust state feedback controller such that for all possible actuator failures and random coupling delays, all nodes of the proposed Markovian jump NCDNs is globally asymptotically synchronized to the reference node in mean square sense and guarantee the output strict passivity performance. By developing a suitable Lyapunov–Krasovskii functional and utilizing the Wirtinger-based integral inequality, the required a set of sufficient conditions for the synchronization of proposed system is established in form of linear matrix inequalities. Finally, three numerical examples including a 3-dimensional Lorenz chaotic model are provided to demonstrate the correctness and superiority of the proposed control scheme.     

Real-time mobile robot teleoperation via Internet based on predictive control

A remote control system that can control a mobile robot in real time via the internet is proposed. To compensate for the network delay and counteract its impact on the teleoperation system, a predictive control scheme based on the modified Smith predictor proposed is selected. To ensure the stability and transparency of the system, a dynamic model manager is designed based on the information exchange between the sensors at the master and slave sides. To precisely predict the time delay, a new timer synchronization algorithm is proposed. To decrease delay-jitter, a new data buffer scheme is performed. Force feedback and a virtual predictive display are introduced to enhance the real-time efficiency of teleoperation. The usefulness and effectiveness of the proposed method and system are proven by teleoperation experiments via the internet over a long distance. __________ Translated from Robot, 2007, 29(4): 305–312 [译自: 机器人]     

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.     

Robustly stable bilateral teleoperation under time-varying delays and data losses: an energy-bounding approach

This paper presents an energy-bounding approach for robustly stable bilateral teleoperation over a communication channel with severe variable time delays and packet drops. We extend the energy-bounding algorithm (EBA) for haptic interaction with virtual environments to bilateral teleoperation with remote environments by using an analogy between haptic interaction and teleoperation controls. Robust stability is achieved by both restricting the extra energy that is generated by the sample-and-hold to within the consumable energy in the master device or slave robot and passifying the communication network. Theoretical analyses of transparency are performed for both position and force tracking aspects. Comprehensive test results for various free and contact motions subsequently show that the proposed bilateral EBA can ensure robust stability against fairy large constant/variable round trip time delays (tested for up to 5 sec for free motion and 600 msec for contact motion within the device workspace) as well as for packet losses of up to 90 % during data transmission.