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Fixed-time prescribed performance control method for nonlinear systems with unknown time-varying parameters 具有未知时变参数的非线性系统的固定时间规定性能控制方法
IF 2.2 4区 计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS Pub Date : 2024-07-10 DOI: 10.1049/cth2.12723
Wei Sun, Junhao Yuan, Xiaoqin Yang

In this study, it is considered that the question of adaptive tracking control of nonlinear systems containing unknown time-varying parameters. To optimize the control effect, a fixed-time control strategy is adopted, in which the upper bound of the settling time is connected with the designed parameters, but not to the initial conditions. In the design, the unknown time-varying parameters are treated as the multiplication of known and unknown vectors, and the adaptive laws are constructed to estimate the mean value of the components in the unknown ones, which availably solve the difficulty of unknown control gains. Besides, the application of command filtered technique, which combined with the compensation signals containing the adaptive parameters, effectively avoids the “complexity explosion” problem. Further, Lyapunov stability theory verifies that the tracking error can always be kept within the boundaries of the performance functions, and converges to a designated neighbourhood of the origin within a fixed time, beyond that all signals of the closed-loop system are bounded. Finally, the simulation results prove the effectiveness of the proposed control scheme.

本研究考虑的是包含未知时变参数的非线性系统的自适应跟踪控制问题。为了优化控制效果,采用了固定时间控制策略,其中沉降时间的上限与设计参数有关,而与初始条件无关。在设计中,未知时变参数被视为已知矢量与未知矢量的乘积,通过构建自适应法则来估计未知矢量中各分量的平均值,从而解决了控制增益未知的难题。此外,指令滤波技术的应用与包含自适应参数的补偿信号相结合,有效避免了 "复杂性爆炸 "问题。此外,Lyapunov 稳定性理论验证了跟踪误差可始终保持在性能函数的边界内,并在固定时间内收敛到原点的指定邻域,在此邻域之外,闭环系统的所有信号都是有界的。最后,仿真结果证明了所提控制方案的有效性。
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引用次数: 0
An edge-based event-triggered delayed distributed algorithm for economic dispatch in smart grids 智能电网中基于边缘事件触发的延迟分布式经济调度算法
IF 2.2 4区 计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS Pub Date : 2024-07-09 DOI: 10.1049/cth2.12720
Chengze Ren, Xuguang Hu, Haoran Zhao, Qiuye Sun

This paper presents an edge-based event-triggered delay distributed algorithm for solving the economic dispatch problem (EDP) in smart grids. The objective of the EDP is to minimize the total generation cost by allocating power to individual generators, each with its local generation constraint. To save the overhead of communication resources between agents, an edge-based event-triggered mechanism is suggested. By setting distinct triggering thresholds for each communication edge, the agent may efficiently regulate the communication frequency among all neighbors. However, in practice, owing to the instability of the network, the agent may receive information regarding its neighbors, leading to communication lags for every communication link. The virtual agent technique and double-stochastic matrix augmentation technique provide an equivalent delay-free EDP. It is demonstrated that the proposed algorithm can asymptotically converge to the global optimal solution as long as the communication delay is arbitrary, time-varying, and random, but bounded. Objective and clear evidence is provided through a case study in smart grids to verify the algorithm's feasibility.

本文提出了一种基于边缘的事件触发延迟分布式算法,用于解决智能电网中的经济调度问题(EDP)。经济调度问题的目标是通过向各个发电机分配电力,使总发电成本最小化,而每个发电机都有其本地发电约束。为了节省代理之间的通信资源开销,建议采用基于边缘的事件触发机制。通过为每个通信边缘设置不同的触发阈值,代理可以有效地调节所有邻居之间的通信频率。然而,在实际应用中,由于网络的不稳定性,代理可能会收到有关其邻居的信息,从而导致每个通信链路的通信滞后。虚拟代理技术和双随机矩阵增强技术提供了等效的无延迟 EDP。研究表明,只要通信延迟是任意的、时变的、随机的,但又是有界的,所提出的算法就能逐渐收敛到全局最优解。通过对智能电网的案例研究,为验证算法的可行性提供了客观、清晰的证据。
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引用次数: 0
Complex-step derivative-based extended Kalman filter for state estimation in twin rotor MIMO system 基于复步导数的扩展卡尔曼滤波器用于双转子多输入多输出系统的状态估计
IF 2.2 4区 计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS Pub Date : 2024-07-09 DOI: 10.1049/cth2.12715
İbrahim Mucuk, Ayhan Özdemir

This paper presents the design of a complex-step extended Kalman filter (CS-EKF) to estimate the states of the twin-rotor MIMO system (TRMS) which is a non-linear system. Since the model of TRMS is quite complex and contains discontinuous functions, it is very difficult to calculate the Jacobian matrix in the TRMS analytically by hand. This makes it difficult to implement control methods that require Jacobian matrix calculation for TRMS. Herein, to calculate the Jacobian matrix, the CS-EKF uses the complex-step derivative approach, which is a numerical technique and offers near-analytical accuracy in a single function evaluation. The effectiveness of the CS-EKF is demonstrated through simulation and real-time experiments. Also, The CS-EKF is compared to the finite-difference extended Kalman filter (FD-EKF) and the unscented Kalman filter (UKF) in terms of estimation accuracy, computational load, and ease of implementation.

本文介绍了复杂步长扩展卡尔曼滤波器(CS-EKF)的设计,用于估计非线性系统双旋翼多输入多输出系统(TRMS)的状态。由于 TRMS 的模型相当复杂,且包含不连续函数,因此很难通过手工分析计算 TRMS 中的雅各布矩阵。这就给需要计算 TRMS 雅各矩阵的控制方法的实施带来了困难。在此,为了计算雅各矩阵,CS-EKF 采用了复步导数法,这是一种数值技术,可在单次函数评估中提供接近分析的精度。CS-EKF 的有效性通过模拟和实时实验得到了证明。此外,CS-EKF 还与有限差分扩展卡尔曼滤波器(FD-EKF)和无符号卡尔曼滤波器(UKF)在估计精度、计算负荷和易实施性方面进行了比较。
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引用次数: 0
Observer-based finite-time time-varying elliptical formation control of a group mobile mecanum-wheeled omnidirectional vehicles for collaborative wildfire monitoring 基于观测器的有限时时变椭圆编队控制,用于协同野火监测的移动式机械轮全向车辆群
IF 2.2 4区 计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS Pub Date : 2024-07-08 DOI: 10.1049/cth2.12713
Joewell Mawanza

This article addresses the issue of collaborative wildfire monitoring using a group mobile mecanum-wheeled omnidirectional vehicles (MWOVs) affected by nonlinear uncertainties and external disturbances. By integrating finite-time extended state observers (FTESO) and backstepping nonsingular fast terminal sliding mode (BNFTSM) control method, an observer-based finite-time time-varying elliptical formation control scheme is proposed for a group of MWOVs tasked with monitoring the propagation of wildfires in an elliptical pattern. First, the FTESO is employed to estimate the unavailable velocity system states and the lumped disturbances. Then, a novel nonsingular fast terminal sliding surface, enhanced with an exponential term, is introduced to improve the convergence rate. Through the Lyapunov theorem, the convergence of position and velocity cooperative tracking errors to zero in fast finite-time is demonstrated. To showcase the effectiveness of the proposed control scheme, comparative simulation results are presented.

本文探讨了使用受非线性不确定性和外部干扰影响的移动式机械轮式全向车辆(MWOVs)进行野火协同监测的问题。通过集成有限时间扩展状态观测器(FTESO)和反步非奇异快速终端滑动模态(BNFTSM)控制方法,提出了一种基于观测器的有限时间时变椭圆编队控制方案,用于监测野火以椭圆模式传播的一组 MWOV。首先,采用 FTESO 估算不可用的速度系统状态和叠加干扰。然后,引入一个新颖的非奇异快速终端滑动面,并用指数项进行增强,以提高收敛速度。通过 Lyapunov 定理,证明了位置和速度协同跟踪误差在快速有限时间内收敛为零。为了展示所提控制方案的有效性,还给出了比较仿真结果。
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引用次数: 0
A hybrid energy storage array group control strategy for wind power smoothing 用于风电平滑的混合储能阵列群控制策略
IF 2.2 4区 计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS Pub Date : 2024-07-06 DOI: 10.1049/cth2.12698
Tong Tong, Le Wei, Yuanye Chen, Fang Fang

With the increase of wind power generation, the safety and economy of power system operations are greatly influenced by the intermittency and fluctuation of wind power. To take the advantage of the complementary characteristics between different energy storage devices, a Hybrid Energy Storage System (HESS) consisting of Battery Energy Storage System (BESS) and Flywheel Energy Storage System (FESS) can alleviate the uncertainty of wind power. This article has proposed a coordinated control strategy through group consensus algorithm based on Model Predictive Control (MPC) for Hybrid Energy Storage Array (HESA) to smooth wind power fluctuations. To allocate power commands to the FESS and BESS, the fluctuation of wind power output is extracted with different frequency domain characteristics as instructions by Empirical Mode Decomposition (EMD) technology. Moreover, a group consensus algorithm based on MPC is proposed to complete the adaptive power allocation of energy storage units. Eventually, the actual wind farm data is used for the simulation to verify the effect of control strategy proposed in this paper. It can be seen that the developed group consensus algorithm based on MPC can cope with different frequency power commands, avoid overcharging and discharging of energy storage media, and smooth wind power effectively.

随着风力发电量的增加,电力系统运行的安全性和经济性受到风力发电间歇性和波动性的极大影响。为了利用不同储能设备之间的互补性,由电池储能系统(BESS)和飞轮储能系统(FESS)组成的混合储能系统(HESS)可以缓解风力发电的不确定性。本文提出了一种基于模型预测控制(MPC)的混合储能阵列(HESA)群组共识算法协调控制策略,以平滑风电波动。为了将功率指令分配给 FESS 和 BESS,利用经验模式分解(EMD)技术提取了具有不同频域特征的风电输出波动。此外,还提出了一种基于 MPC 的群体共识算法,以完成储能单元的自适应功率分配。最后,利用实际风电场数据进行仿真,验证本文提出的控制策略的效果。可以看出,所开发的基于 MPC 的群组共识算法能够应对不同频率的功率指令,避免储能介质的过充和过放,并有效平滑风功率。
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引用次数: 0
Closed-loop stability analysis of deep reinforcement learning controlled systems with experimental validation 深度强化学习控制系统的闭环稳定性分析与实验验证
IF 2.2 4区 计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS Pub Date : 2024-06-27 DOI: 10.1049/cth2.12712
Mohammed Basheer Mohiuddin, Igor Boiko, Rana Azzam, Yahya Zweiri

Trained deep reinforcement learning (DRL) based controllers can effectively control dynamic systems where classical controllers can be ineffective and difficult to tune. However, the lack of closed-loop stability guarantees of systems controlled by trained DRL agents hinders their adoption in practical applications. This research study investigates the closed-loop stability of dynamic systems controlled by trained DRL agents using Lyapunov analysis based on a linear-quadratic polynomial approximation of the trained agent. In addition, this work develops an understanding of the system's stability margin to determine operational boundaries and critical thresholds of the system's physical parameters for effective operation. The proposed analysis is verified on a DRL-controlled system for several simulated and experimental scenarios. The DRL agent is trained using a detailed dynamic model of a non-linear system and then tested on the corresponding real-world hardware platform without any fine-tuning. Experiments are conducted on a wide range of system states and physical parameters and the results have confirmed the validity of the proposed stability analysis (https://youtu.be/QlpeD5sTlPU).

基于训练有素的深度强化学习(DRL)控制器可以有效地控制动态系统,而传统的控制器可能效果不佳且难以调整。然而,由训练有素的 DRL 代理控制的系统缺乏闭环稳定性保证,这阻碍了它们在实际应用中的采用。本研究基于训练有素的 DRL 代理的线性-二次多项式近似值,利用 Lyapunov 分析法研究了由训练有素的 DRL 代理控制的动态系统的闭环稳定性。此外,这项工作还有助于理解系统的稳定裕度,从而确定有效运行的操作边界和系统物理参数的临界阈值。所提出的分析方法在 DRL 控制系统上进行了多次模拟和实验验证。DRL 代理使用非线性系统的详细动态模型进行训练,然后在相应的真实世界硬件平台上进行测试,无需任何微调。实验在多种系统状态和物理参数下进行,结果证实了所建议的稳定性分析 (https://youtu.be/QlpeD5sTlPU) 的有效性。
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引用次数: 0
UAV cluster geometric information fusion cooperative positioning algorithm with LEO satellite system 无人机集群几何信息融合与LEO卫星系统协同定位算法
IF 2.2 4区 计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS Pub Date : 2024-06-24 DOI: 10.1049/cth2.12708
Chengkai Tang, Wenbo Wang, Lingling Zhang, Chen Wang

With the rapid development of unmanned aerial vehicle (UAV) clusters, they will become the main means in urban transportation, traffic monitoring and other fields. The positioning accuracy of UAV clusters is the core basis of the application, this paper proposes a UAV cluster information geometry fusion positioning method based on low-orbit satellite system, which uses the geometric relationship between UAV clusters to transform the low-orbit constellation navigation information of each UAV into an information geometry probability model, reducing the influence of the low-orbit satellite system time asynchrony, and through Kullback–Leibler average fusion to achieve UAV cluster real-time high-precision positioning. The method effectively solves the problem caused by the easy loss of GNSS signals in the obscured environment, and significantly improves the reliability and stability of UAV cluster positioning in urban environments. Comparing the method of this paper with the existing UAV fusion navigation methods in terms of positioning accuracy stability, positioning real-time and error mutation under the occlusion scenario, the experimental results show that the method of this paper has obvious superiority in the above indexes.

随着无人机(UAV)集群的快速发展,它们将成为城市交通、交通监控等领域的主要手段。无人机集群的定位精度是应用的核心基础,本文提出了一种基于低轨卫星系统的无人机集群信息几何融合定位方法,利用无人机集群之间的几何关系,将每架无人机的低轨星座导航信息转化为信息几何概率模型,减少了低轨卫星系统时间异步的影响。并通过Kullback-Leibler平均融合实现无人机集群实时高精度定位。该方法有效解决了GNSS信号在遮挡环境下容易丢失的问题,显著提高了无人机集群在城市环境下定位的可靠性和稳定性。将本文方法与现有无人机融合导航方法在遮挡场景下的定位精度稳定性、定位实时性和误差突变等方面进行了比较,实验结果表明,本文方法在上述指标上具有明显的优势。
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引用次数: 0
Robust distributed Nash equilibrium solution for multi-agent differential graphical games 多智能体差分图形博弈的鲁棒分布纳什均衡解
IF 2.2 4区 计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS Pub Date : 2024-06-24 DOI: 10.1049/cth2.12687
Shouxu Zhang, Zhuo Zhang, Rongxin Cui, Weisheng Yan

This paper studies the differential graphical games for linear multi-agent systems with modelling uncertainties. A robust optimal control policy that seeks the distributed Nash equilibrium solution and guarantees the leader-following consensus is designed. The weighting matrices rely on modelling uncertainties, leading to the Nash equilibrium solution, and the solution can be obtained by solving a decoupled algebraic Riccati equation. Simulation studies are finally reported to illustrate the effectiveness of proposed policy.

本文研究了具有建模不确定性的线性多代理系统的微分图形博弈。本文设计了一种稳健的最优控制策略,该策略寻求分布式纳什均衡解,并保证领导者与跟随者之间达成共识。权重矩阵依赖于建模不确定性,从而导致纳什均衡解,该解可通过求解解耦代数里卡提方程获得。最后报告了模拟研究,以说明建议政策的有效性。
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引用次数: 0
Event-triggered adaptive output feedback control of unmanned aerial vehicles under hybrid attacks 混合攻击下无人机的事件触发自适应输出反馈控制
IF 2.2 4区 计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS Pub Date : 2024-06-24 DOI: 10.1049/cth2.12688
Rui Li, Lei Zhang, Yufeng Lu, Chenying Yi, Liangyuan Chen, Yi Su

This study addresses the adaptive dynamic output feedback (DOF) control for unmanned aerial vehicle systems subjected to hybrid attacks. These attacks are delineated by two Bernoulli variables, signifying denial-of-service (DoS) and deception attacks, respectively. In an effort to enhance energy efficiency and reduce communication costs in the presence of network delays, the study introduces an innovative probability event-triggering mechanism (PETM). Subsequently, it crafts a DOF controller that operates based on the available measurement outputs. By harnessing Lyapunov stability theory, the study identifies sufficient conditions that guarantee the stability of the system's augmented dynamics. Finally, the efficacy and applicability of the proposed method are underscored through a case study on an unmanned aerial vehicle.

本研究针对遭受混合攻击的无人飞行器系统的自适应动态输出反馈(DOF)控制。这些攻击由两个伯努利变量划定,分别表示拒绝服务(DoS)攻击和欺骗攻击。为了在网络延迟的情况下提高能效并降低通信成本,研究引入了一种创新的概率事件触发机制(PETM)。随后,它根据可用的测量输出精心设计了一个 DOF 控制器。通过利用 Lyapunov 稳定性理论,研究确定了保证系统增强动态稳定性的充分条件。最后,通过对无人驾驶飞行器的案例研究,强调了所提方法的有效性和适用性。
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引用次数: 0
Finite-time control of DC–AC boost converter: The limit cycle approach 直流-交流升压转换器的有限时间控制:极限循环方法
IF 2.2 4区 计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS Pub Date : 2024-06-24 DOI: 10.1049/cth2.12705
Meysam Azhdari, Tahereh Binazadeh

This paper proposes a novel finite-time limit cycle controller for DC to AC conversion in power boost converters. The stable limit cycle is categorized as a positive limit set. Achieving the control law, based on the concepts of set stability and finite-time stability, is a challenging problem. To fulfill the control objective, a novel sliding manifold is suggested concerning the structure of the wanted limit cycle which facilitates conditions for the development of finite-time stability for the limit cycle. By utilizing the sliding mode control method, a control strategy is proposed that guarantees the desired stable limit cycle is created in the phase plane of the closed-loop system and the phase trajectories reach it in a finite time and remain on it for all future times. This ensures the finite-time generation of the biased sinusoidal oscillations in the output of the power boost converter from a DC input source. The simulation results of a practical boost converter have validated the effectiveness and feasibility of the presented algorithm.

本文针对升压转换器中的直流到交流转换,提出了一种新型有限时间极限周期控制器。稳定的极限循环被归类为正极限集。根据集合稳定性和有限时间稳定性的概念来实现控制法则是一个具有挑战性的问题。为了实现控制目标,就所需极限循环的结构提出了一种新的滑动流形,它为极限循环有限时间稳定性的发展提供了便利条件。通过利用滑模控制方法,提出了一种控制策略,确保在闭环系统的相位平面上创建所需的稳定极限周期,相位轨迹在有限时间内到达极限周期,并在未来所有时间内保持在极限周期上。这样就能确保在直流输入源的升压转换器输出端有限时间内产生偏置正弦振荡。实际升压转换器的仿真结果验证了所介绍算法的有效性和可行性。
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引用次数: 0
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IET Control Theory and Applications
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