基于DoS攻击能量分级的ICPS综合安全控制与通信协同设计

针对一类有限能量拒绝服务（denial of service,DoS）攻击与执行器故障共存的工业信息物理系统（industry cyber-physical system,ICPS）,研究了综合安全控制与通信协同设计问题。首先,考虑单侧网络遭受DoS攻击的情形,构建了ICPS综合安全控制架构,并从防御者的视角通过分析不...     

Resilient control for wireless networked control systems under DoS attack via a hierarchical game

In this paper, the resilient control problem is investigated for a wireless networked control system (WNCS) under denial‐of‐service (DoS) attack via a hierarchical game approach. In the presence of a wireless network, a DoS attacker leads to extra packet dropout in the cyber layer of WNCS by launching interference power. A zero‐sum Markov game is exploited to model the interaction between the transmitter and the DoS attacker under dynamic network environment. Additionally, with the attack‐induced packet loss, an H_∞ minimax controller is designed in the physical layer by using a delta operator approach. Both value iteration and Q‐learning methods are used to solve the hierarchical game problem for the WNCS. The proposed method is applied to a load frequency control system to illustrate the effectiveness.     

DoS攻击下多智能体系统无模型自适应迭代学习跟踪控制EI北大核心CSCD

针对周期性拒绝服务(DoS)攻击下多智能体系统有限时间趋同跟踪控制问题,本文提出了一种无模型自适应迭代学习控制(MFAILC)算法.假设多智能体系统具有固定拓扑结构,并且仅有部分智能体可获取到期望轨迹信息.在多智能体系统数据传输过程中,需要经由对数量化器进行量化处理.首先,使用伪偏导数将智能体系统动态线性化,处理过程中考虑符合伯努利分布的周期性DoS攻击现象,在此基础上设计了MFAILC控制算法,其次,采用压缩映射方法给出了一个在期望意义下保证跟踪误差收敛的充分条件,并在理论上证明了所提算法的收敛性.所提算法只需利用系统的输入输出数据就可完成趋同跟踪任务.最后,仿真结果验证了所提算法的有效性.     

基于LQG控制的EPS系统最优控制研究

电动助力转向系统存在着路面随机激励、转矩传感器测量噪声、模型参数不确定所引起的干扰等复杂因素,通过建立电动助力转向系统的数学模型以及加入随机干扰信号的系统状态空间表达式,设计了线性二次型高斯状态反馈控制器和Kalman滤波器。并以能耗及电机的实际助力电流与目标助力电流之间的误差最小为目标函数对EPS系统进行仿真分析,仿真结果表明:采用该最优控制方法能有效的抑制系统的外部干扰,提高系统的鲁棒性,使能耗及电机的实际助力电流与目标助力电流之间的误差达到最小。     

Speed tracking control for the gimbal system with harmonic drive

This paper presents a composite controller based on a disturbance observer for the gimbal system of double-gimbal magnetically suspended control moment gyro (DGMSCMG) with harmonic drives. The controller removes the influence by coupling moments and nonlinear transmission torques. The disturbances are estimated by the designed disturbance observer. By introducing a state feedback controller, the disturbances can be eliminated from the output channel of the system. The gain selection principle of the disturbance observer is also analyzed. Both the simulation and experimental results indicate that the proposed control method can reject mismatched disturbances and improve system performance.     

工业机器人遥操作系统的空间映射与控制策略

针对工业机器人遥操作系统中存在的主从机器人工作空间差异以及运动控制精度与安全问题,提出了一种工作空间映射算法与位置—速度混合控制策略。首先,将遥操作划分为自由运动和交互两个阶段,在自由运动阶段采用映射算法使主从机器人的工作空间高度覆盖,使主机器人可操控的从机器人运动范围最大化。进一步,在交互阶段设计了一种位置—速度混合控制策略对工业机器人的运动进行准确的控制,使主从机器人的实际位置轨迹准确的跟随,并进一步引入反馈引导力以实现安全的控制。最后在Touch-ABB IRB120主从机器人遥操作实验平台上对所提控制方法进行验证,实验结果表明该方法使得主从机器人运动范围在高度覆盖的同时可以保证遥操作控制的精度。     

Virtual control strategy and conditioning technique for tracking and learning controls under input restrictions

The virtual control strategy for mechanical systems has been recently proposed (Gnucci and Marino, 2021) in the context of under-actuated mechanical systems. Such a strategy views and represents an under-actuated mechanical system as a fully actuated system with virtually added inputs and outputs having to satisfy, through a suitable choice of the virtual output reference signals, the virtual input zero-equality constraint: the related adaptive tracking control problem is then solved through standard design techniques. This paper exhibits a twofold aim. The first one is: to enlarge the concept of zero-input constraint and thus naturally adapt the virtual control approach to the case in which an actuator fault can occur. The second aim is: to show how the application and transposition of such an adaptation to two well-known classes of nonlinear systems (special systems in multi-variable tracking form with two inputs and outputs under actuator faults; one-relative-degree, single-input, single-output systems in output feedback form under input saturation) not only own strong connections with the conditioning technique, originally conceived in the context of anti-windup problems under input constraints, but they also gain original results.     

拒绝服务攻击下的多输入多输出非线性系统无模型自适应控制

针对多输入多输出(MIMO)非线性离散时间系统,研究系统遭受拒绝服务(DoS)攻击和随机发生数据包丢失下的控制问题.首先采用两个独立的伯努利分布对周期性DoS攻击和随机发生的数据包丢失进行建模.其次结合DoS攻击设计无模型自适应控制(MFAC)算法,进而通过理论分析和数学推导证明所提算法的收敛性.并且通过结合先前时刻数...     

雨雾天气下公路可变限速控制策略研究

针对雨雾天气下公路交通事故上升与通行能力下降的问题,综合考虑交通安全和通行效率两个因素,提出一种雨雾天气下可变限速控制策略;首先,考虑雨雾天气下道路线形对车辆速度和道路通行能力的影响,建立雨雾天气下动态交通流模型;然后,根据驾驶员可视距离、路面附着系数和道路曲线等因素确定雨雾天气下车辆最大安全速度;最后,采用自适应遗传算法对包含总行程时间和总行驶里程的目标函数进行求解,得到雨雾天气下各路段的限速值;仿真结果表明,所提出的可变限速控制策略有效降低了雨雾天气下公路的行车风险,并缓解了交通拥堵。     

循环球电动助力转向系统控制及补偿策略

考虑循环球式转向系统内多因素的影响,设计循环球式电动助力系统的控制及补偿策略,建立循环球式电动助力转向系统模型,设计电流助力曲线,采用模糊PID控制方法,实现电机的实时控制;为了获得更好的助力力矩,补偿系统内损失,基于LuGre摩擦模型,通过观测到的系统参数,建立摩擦状态观测器,得到摩擦补偿叠加电流。使用Matlab/Simulink与CarSim的联合仿真验证控制系统;通过对增加摩擦补偿策略前后的对比分析,可知所设计的电动助力转向电流控制系统能综合车辆行驶时的摩擦、车速和转向盘转角等信息,由助力执行电机产生适当的助力,更准确地实现驾驶员的驾驶意图,使得回正过程更加平稳。     

A two-level control strategy with fuzzy logic for large-scale photovoltaic farms to support grid frequency regulation

This study proposes a two-level coordinated control strategy with fuzzy logic for appropriately adjusting the total active power supplied to a grid by large-scale photovoltaic (PV) farms in order to regulate grid frequency. For a solar farm, the strategy includes a central coordinating controller and many local controllers at PV power assemblies, treated as agents. In detail, the central controller uses a frequency regulation module based on a new automatic-tuning fuzzy-logic controller scheme to compute the appropriate reference values according to the total power needed. Then, the individual reference value for each local controller is determined. Each local controller governs all power-electronic converters installed at the PV agent to inject power into the grid according to the individual reference value received. Additionally, each local controller uses an algorithm to manage the state-of-charge of the battery bank installed at the agent so that it remains in the safe range of 20–80% while operating and close to the desired idle value of 50% at the steady state. Besides, a special control mode is developed and integrated into the overall strategy to aid rapid recovery of the grid frequency under emergency conditions. Numerical simulations demonstrate that the suggested strategy has the good response in terms of injecting an appropriate amount of power into the grid to regulate the frequency deviation into acceptable ranges of ±0.2 (Hz) in the transient state and ±0.05 (Hz) at the steady state, even when the weather conditions (solar radiation, air temperature), AC system load, and important control parameters of the grid suddenly change. Furthermore, the effectiveness in improving the grid-frequency stabilization by using the proposed strategy is validated within a four-area power system, where four PV farms are connected and the operating parameters of the grids at the areas are fairly different.     

Distributed event‐triggered tracking control with a dynamic leader for multiple Euler‐Lagrange systems under directed networks

The distributed tracking control for multiple Euler‐Lagrange systems with a dynamic leader is investigated in this article via the event‐triggered approach. Only a portion of followers have access to the leader, and the communication topology among all agents is directed that contains a directed spanning tree rooted at the leader. The case that the leader's generalized velocity is constant is first considered, and a distributed event‐based control law is developed by using a velocity estimator. When the leader's generalized velocity is time‐varying, novel distributed continuous estimators are proposed to avoid the undesirable chattering effect while guaranteeing that the estimate errors converge to zeros. With the designed distributed estimators, another distributed event‐based control protocol is provided. Controller update frequency and resource consumption in our work can be reduced by applying the aforementioned two distributed control laws, and the tracking errors can converge to zeros. In addition, it is rigorously proved that no agent exhibits Zeno behavior. Finally, the effectiveness of the proposed distributed event‐based control laws is elucidated by a number of simulation examples.     

Optimal trajectory planning for robots under the consideration of stochastic parameters and disturbances

Efficient control strategies of robots should cause only low on-line correction expenses. Hence, the mostly available statistical and a priori informations about the random parameters and disturbances of the underlying mechanical system and its environment should be considered already for off-line programming of robots. Measuring the violations of the basic mechanical conditions by means of expected penalty costs, a stochastic optimization problem is obtained for the computation of an optimal open-loop control. The stochastic optimization problem can be solved — after discretization — by parameter optimization.     

Bounded consensus for multiagent systems by event‐triggered data transmission,time delay,and predictor‐based control

This paper investigates the consensus issue of multiagent systems with data transmission time delay. The state measurement of each local agent is directly sent to a private event‐trigger and further authorized to be broadcasted to its neighbors via communication network only when the threshold of the event‐trigger is violated. Since the controller always receives discrete‐time neighbor information with data transmission time delay, a predictor is employed to estimate the continuous‐time neighbor state. Based on the estimated state, a novel consensus protocol is mainly proposed for achieving the bounded consensus of the multiagent systems. By the proposed method, the asynchronous neighbor information is allowed and the margin of data transmission time delay is also given. Furthermore, it has been proved that the unwanted Zeno phenomena can be naturally excluded. Numerical example is provided to demonstrate the effectiveness of the proposed method.     

Finite‐time attitude‐tracking control for rigid spacecraft with actuator failures and saturation constraints

In this article, the problem of finite‐time attitude‐tracking control for rigid spacecraft is addressed. Uncertainties caused by external disturbances, unknown inertial matrix, actuator failures, and saturation constraints are tackled simultaneously. First, a smooth function that is more qualified to approximate the standard saturation characteristics is presented to deal with the actuator saturation constraints. Second, a fast nonsingular terminal sliding mode (FNTSM) manifold is constructed as a foundation of controllers design. By incorporating the fuzzy logic system into FNTSM technique, a less demanding solution of coping with model uncertainties is provided because the requirement of a prior knowledge of unknown inertial parameters and external disturbances in many existing achievements is removed. To reduce the number of parameters to be estimated, the norm approximation approach is exploited. Subsequently, an antichattering attitude controller is presented such that all the tracking errors converge into arbitrary small domains around the origin in finite time. The result is further extended to obtain a fault‐tolerant controller against completely failed actuators. Finally, numerical simulation is conducted to verify the effectiveness of the proposed control scheme and comparison with relevant literature demonstrates its high performance. Furthermore, an experiment for the large satellite Hubble Space Telescope is carried out to validate the practical feasibility.     

A control energy approach for the stabilization of the rigid beam balanced by the cart

In this paper we present a control strategy for the stabilization of a rigid beam balanced by a cart. The control problem consists of horizontally balancing the beam by moving the cart backwards and forwards along the beam. The cart movement is restricted to always remain over the beam. The control strategy is based on the interconnection and damping assignment passivity based controller. The stability analysis is carried out using LaSalles's theorem. Copyright © 2008 John Wiley & Sons, Ltd.     

Dual mode control strategy for the energy efficiency of complex and flexible manufacturing systems

The manufacturing industry is shifting towards smart manufacturing, in which both energy efficiency and flexibility are some of the main objectives of this digital transformation. In this regard, the control strategies for manufacturing systems should be able to support the requirements of this transformation with a low computational burden towards their implementation in real time. To this end, in this paper, a dual mode control strategy based on two control approaches is proposed to minimise the energy consumption of manufacturing systems without affecting their productivity, even when scenarios of flexible manufacturing are considered. The first control mode is based on model predictive control to determine an optimisation-based strategy for the constrained behaviour of the system. Then, the second mode builds on the assumption that the system exhibits a periodic behaviour and, thus, it will be able to switch to an autonomous control mode that avoids the resolution of an optimisation problem online. The proposed control strategy is tested in a manufacturing process line in which changes in the production programs are considered with the aim to test the performance in flexible manufacturing scenarios. The obtained results show that the computational burden could be significantly reduced while reducing global energy consumption without affecting the system productivity.     

超大型天线馈源舱柔索支撑结构动力学分析与跟踪控制

根据悬链线解析表达式推导出柔索两端固定时索端拉力与索长之间的关系,用于求解特定长度的驱动柔索对处于某一位姿的馈源舱作用力,在此基础上应用Newton-Euler法建立了超大型射电望远镜馈源舱柔索支撑系统的简化动力学模型.采用具有二次收敛性的Newton-Raphson迭代法进行求解,得到较快的求解速度以满足实时控制要求.针对该系统的非线性、慢时变、多变量耦合等特点,提出了一种自适应双模糊控制器来实现馈源舱轨迹跟踪.该控制器采用模糊推理完成两组控制器的平稳过渡.最后,通过仿真计算结果验证了该控制策略的有效性.     

Pattern recognition and control by adaptive methods for an intelligent mobile vehicle

This paper describes adaptive methods for both pattern recognition and control in an experimental mobile vehicle (MV). An adaptive resonance theory (ART) neural network is used as the character recognizer. It can self-organize and self-stabilize in response to complex binary input vectors. New input patterns can be saved in such a fashion that the stored patterns are not forgotten or destroyed. By merging the advantages of the feed-forward neural network, adaptive algorithm, and fuzzy control, a neuro-fuzzy system also is proposed. This can deal with a large amount of training data in the neural network, from these data produce more reasonable fuzzy rules with the adaptive algorithm, and then control the object by fuzzy control. This is not a simple combination of the three methods, but a merger into one intelligent control system. Finally, the experimental results and some conclusions are given. This work was presented in part at the 7th International Symposium on Artificial Life and Robotics, Oita, Japan, January 16–18, 2002     

Stabilisation and state trajectory tracking problem for nonlinear control systems in the presence of disturbances

In this paper, we consider the problem of stabilisation and tracking of desired state trajectory for a wide range of nonlinear control problems with disturbances. We present the sufficient conditions for the existence of C ^k state-feedback controllers and the process of their mathematical designing is described.