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The optimal control theory——a scientific approach to fundamentally solving control problems

Science China(Information Sciences) 2025年第1期68卷 389-391页

作者： Huanshui ZHANG School of Electrical and Automation Engineering Shandong University of Science and Technology School of Control Science and Engineering Shandong University

The maximum principle has bridged mathematical optimization to optimal control,ushering in significant developments and refinements in optimal control theory,notably during the 1960s with the advent of linear quadratic (LQ)control and linear quadratic estimation (LQE).This progression propelled optimal control theory into further advancements,encompassing stochastic control,robust/H-infinity control,model predictive control (MPC),networked control,and reinforcement learning *** control,established upon a rigorous mathematical foundation,extends static optimization theory to dynamic systems,exhibiting scientific essence,unity,and ***,since its inception,optimal control theory has served as an indispensable core role across all control-related domains,including communication-constrained control in networked systems,consensus control,cooperative control,and reinforcement learning control.

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Event-triggered leader-follower bipartite consensus control for nonlinear multi-agent systems under DoS attacks

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Science China(Information Sciences) 2025年第3期68卷 286-301页

作者： Wei SU Chaoxu MU Song ZHU Ben NIU Changyin SUN School of Control Science and Engineering Tianjin University School of Mathematics China University of Mining and Technology School of Control Science and Engineering Dalian University of Technology School of Automation Southeast University

Aiming at the consensus control problem of nonlinear multi-agent systems(MASs) under directed topology, a leader-follower bipartite consensus control strategy is proposed. This strategy takes into account the potential for denial-of-service(DoS) attacks and completely unknown system dynamics. Specifically, the bipartite consensus dynamics describes the cooperation and competition relationship between followers and the leader, that is, the follower chooses to move in accordance with or opposite to the leader according to its trajectory. In order to optimize the communication bandwidth and mitigate the impact of DoS attacks, the proposed consensus control scheme integrates the DoS attack detection mechanism and event-triggered mechanism. In addition, neural networks(NNs) are used to solve the nonlinear problem, and a speed function is designed to achieve the desired tracking performance, ensuring that all agents' tracking errors converge to a predefined set in a finite time. With the help of backstepping, graph theory, and Lyapunov stability theory, sufficient conditions for achieving bipartite consensus without Zeno behavior are established. Finally, the accuracy and feasibility of the theoretical analysis are verified by simulation cases.

关键词： multi-agent systems neural networks bipartite consensus event-trigger denial-of-service attack

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Detection of Escherichia coli Using Loop-Mediated Isothermal Amplification for a Novel Air Sampling System

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Aerosol and Air Quality Research 2025年第1期25卷 1-13页

作者： Eraslan-Gültekin, Hülya Ergenc, Ali Fuat Department of Control and Automation Engineering Istanbul Technical University Istanbul34469 Turkey

Introduction: This paper presents an innovative air sampling and rapid detection system for airborne bacteria in the environment. Objective: The proposed system aims to enhance the efficiency and accuracy of airborne bacterial detection by integrating an improved air sampler with a rapid nucleic acid amplification method. Methods: The system incorporates an air sampler with a cutting-edge nucleic acid amplification method known as loop-mediated isothermal amplification to detect bacterial pathogens precisely and efficiently. The air sampling system comprises a specialized collection device capable of capturing airborne bacteria particles, and an automatic sample extraction system from this device. Subsequently, nucleic acid amplification is performed using the LAMP technique, which can amplify at a constant temperature (65 °C) without the need for thermal cycling as with polymerase chain reaction, providing a faster, less costly, isothermal, and highly sensitive method for detecting target bacterial DNA. In addition, a simple, easily portable, low-cost, high-efficiency heating device that can be operated at constant temperature for the desired time has been developed for the LAMP reactions. Results: The results demonstrate the capability of the system to detect a broad-spectrum bacteria concentration with high sensitivity and specificity, making it a valuable tool for real-time monitoring and surveillance. The limit of detection of the air sampling system is 65 CFU L-1, determined through a series of experiments. Conclusions: The proposed air sampling system, coupled with the LAMP technology, offers a promising solution for addressing the limitations associated with traditional bacterial detection methods in airborne environments, such as insufficient sensitivity, extended processing times, microbial drying, isolating target microorganisms from others, and challenges in detecting low concentrations, paving the way for enhanced public health and safety measures. © Th

关键词： Escherichia coli

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Stability and Stabilization of Sampled-Data Based LFC for Power Systems:A Data-Driven Method

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IEEE/CAA Journal of Automatica Sinica 2025年第1期12卷 291-293页

作者： Yu-Long Fan Chuan-Ke Zhang Yong He the School of Automation China University of Geosciences the Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems the Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education IEEE

Dear Editor,This letter is concerned with stability analysis and stabilization design for sampled-data based load frequency control(LFC) systems via a data-driven method. By describing the dynamic behavior of LFC systems based on a data-based representation, a stability criterion is derived to obtain the admissible maximum sampling interval(MSI) for a given controller and a design condition of the PI-type controller is further developed to meet the required MSI. Finally, the effectiveness of the proposed methods is verified by a case study.

关键词： Sampled data control systems

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Security control for air-sea heterogeneous multiagent systems with cooperative-antagonistic interactions:An intermittent privacy preservation mechanism

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Science China(Technological Sciences) 2025年第4期68卷 179-192页

作者： Shoufeng YANG Hongjing LIANG Yingnan PAN Tieshan LI College of Control Science and Engineering Bohai UniversityJinzhou121013China School of Automation Engineering University of Electronic Science and Technology of ChinaChengdu611731China Laboratory of Electromagnetic Space Cognition and Intelligent Control Beijing100089China

antagonistic interactions,data security and transient-steady state performance of the system are two key *** ensure data security,an intermittent privacy preservation(IPP)mechanism is proposed for the first time.A novel setting time initial mask function and a novel intermittent mask function are *** can implement intermittent preservation for the system according to actual requirements,which solves the irreversibility problem after conventional mask disappears and balances control accuracy and system *** ensure transient-steady state performance,a novel error transformation function(ETF)is proposed and integrated into the predefined-time prescribed performance control *** to conventional hyperbolic tangent type ETFs,the proposed ETF can improve the convergence accuracy of errors under the same ***,a unified model of the air-sea HMASs is established,which improves the model accuracy compared with the simplified ***,the proposed IPP security control strategy is applied to the air-sea delivery mission to verify its feasibility and effectiveness.

关键词： air-sea heterogeneous multiagent systems(HMASs) security control intermittent privacy preservation(IPP) error transformation function(ETF)

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controllability of heterogeneous networked sampled-data systems

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Science China(Information Sciences) 2025年第3期68卷 302-318页

作者： Zixuan YANG Lin WANG Xiaofan WANG Guanrong CHEN Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China School of Mechatronic Engineering and Automation Shanghai University School of Electrical and Electronic Engineering Shanghai Institute of Technology Department of Electrical Engineering City University of Hong Kong

This study investigates the controllability of a general heterogeneous networked sampled-data system(HNSS) consisting of nonidentical node systems, where the inner coupling between any pair of nodes can be described by a unique *** signals on control and transmission channels are sampled and held by zero-order holders, and the control sampling period of each node can be different. Necessary and sufficient controllability conditions are developed for the general HNSS, using the Smith normal form and matrix equations, respectively. The HNSS in specific topology or dynamic settings is discussed subsequently with easier-to-verify conditions derived. These heterogeneous factors have been determined to independently or jointly affect the controllability of networked sampled-data systems. Notably, heterogeneous sampling periods have the potential to enhance the overall controllability, but not for systems with some special dynamics. When the node dynamics are heterogeneous,the overall system can be controllable even if it is topologically uncontrollable. In addition, in several typical heterogeneous sampled-data multi-agent systems, pathological sampling of single-node systems will necessarily cause overall uncontrollability.

关键词： network controllability sampled-data system heterogeneous system inner coupling multi-agent system

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Predicting Temperatures Inside a Steel Slab Reheating Furnace Using Neural Networks

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IEEE Transactions on Industry Applications 2025年第3期61卷 5273-5282页

作者： De Souza Lima, Rodrigo Scardua, Leonardo Azevedo De Almeida, Gustavo Maia Federal Instituto of Espírito Santo Control Engineering and Automation Engineering ES Serra Brazil Federal Instituto of Espírito Santo Coordination of Industrial Automation Serra ES Serra Brazil

The steel industry, characterized by complex and costly production processes, stands to gain significantly from the integration of intelligent systems for automation. This study details the development of a data-driven computer system, leveraging artificial neural networks, specifically for predicting temperatures in slab reheating furnaces. Recurrent Artificial Neural Networks (RNNs) have been extensively studied for their ability to make predictions based on historical sequences with temporal dependencies, which is ideal for monitoring industrial process variables. This research evaluates the performance of several predictive neural models, including Recurrent Neural Network (RNN), Long Short-Term Memory (LSTM), Gated Recurrent Unit (GRU), and Temporal Convolutional Network (TCN). It also delves into data preprocessing and hyperparameter tuning to enhance model accuracy. Prediction accuracy was assessed using metrics such as Mean Absolute Error (MAE) and Root Mean Square Error (RMSE). The models were tested across various prediction horizons to determine their effectiveness in delivering accurate forecasts several steps ahead. © 1972-2012 IEEE.

关键词： Long short-term memory

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Enhanced Tube-Based Event-Triggered Stochastic Model Predictive control With Additive Uncertainties

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IEEE/CAA Journal of Automatica Sinica 2025年第3期12卷 596-605页

作者： Chenxi Gu Xinli Wang Kang Li Xiaohong Yin Shaoyuan Li Lei Wang the School of Control Science and Engineering Shandong University IEEE the School of Electronic and Electrical Engineering University of Leeds the Qingdao University of Science and Technology the Department of Automation Shanghai Jiao Tong University the Key Laboratory of System Control and Information Processing Ministry of Education of China

This paper proposes an event-triggered stochastic model predictive control for discrete-time linear time-invariant(LTI) systems under additive stochastic disturbances. It first constructs a probabilistic invariant set and a probabilistic reachable set based on the priori knowledge of system *** with enhanced robust tubes, the chance constraints are then formulated into a deterministic form. To alleviate the online computational burden, a novel event-triggered stochastic model predictive control is developed, where the triggering condition is designed based on the past and future optimal trajectory tracking errors in order to achieve a good trade-off between system resource utilization and control performance. Two triggering parameters σ and γ are used to adjust the frequency of solving the optimization problem. The probabilistic feasibility and stability of the system under the event-triggered mechanism are also examined. Finally, numerical studies on the control of a heating, ventilation, and air conditioning(HVAC) system confirm the efficacy of the proposed control.

关键词： Event-triggered mechanism heating, ventilation, and air conditioning (HVAC) control probabilistic reachable set stochastic model predictive control

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Interference Suppression and Jitter Elimination Ability-Based Adaption Tracking Guidance for Robotic Fishes

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IEEE/CAA Journal of Automatica Sinica 2025年第1期12卷 126-137页

作者： Dongfang Li Jie Huang Rob Law Xin Xu Limin Zhu Edmond Q.Wu IEEE the School of Electrical Engineering and Automation Fuzhou University the Key Laboratory of System Control and Information Processing Ministry of Education the School of Electrical Engineering and Automation Fuzhou University 5G+Industrial Internet Institute Fuzhou University the University of Macau the College of Mechatronics and Automation National University of Defense Technology the School of Mechanical Engineering Shanghai Jiao Tong University the Department of Computer Science and Engineering Shanghai Jiao Tong University

This work presents an adaptive tracking guidance method for robotic fishes. The scheme enables robots to suppress external interference and eliminate motion jitter. An adaptive integral surge line-of-sight guidance rule is designed to eliminate dynamics interference and sideslip issues. Limited-time yaw and surge speed observers are reported to fit disturbance variables in the model. The approximation values can compensate for the system's control input and improve the robots' tracking ***, this work develops a terminal sliding mode controller and third-order differential processor to determine the rotational torque and reduce the robots' run jitter. Then, Lyapunov's theory proves the uniform ultimate boundedness of the proposed method. Simulation and physical experiments confirm that the technology improves the tracking error convergence speed and stability of robotic fishes.

关键词： Adaptive integral surge line-of-sight approximation robotic fish speed observer

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Event-based non-fragile state estimation for time-varying systems under deception attacks

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Science China(Information Sciences) 2025年第4期68卷 349-362页

作者： Xiao-Meng LI Tao ZOU Renquan LU Zhijia ZHAO School of Mechanical and Electrical Engineering Guangzhou University School of Automation Guangdong Hong Kong Joint Laboratory for Intelligent Decision and Cooperative ControlGuangdong University of Technology

This paper addresses the challenge of dynamic event-based non-fragile state estimation for discrete time-varying systems under deception attacks. These attacks involve injecting deceptive signals into the communication channel, which can consume limited network resources and disrupt system estimation tasks. To tackle this issue, the study introduces a comprehensive and realistic deception attack model that accounts for the various hard physical constraints. To mitigate the influence of these attacks and reduce communication demands, a dynamic event-triggered scheme that uses dynamic threshold parameters is developed. The main purpose of the addressed problem is to design an event-based non-fragile estimator that ensures the estimation error systems meet the H∞performance constraint over a finite horizon. The paper provides two key criteria to ensure the existence of the proposed estimator, leveraging stochastic analysis techniques. The desired estimator gains are determined using a recursive process of solving matrix inequalities. Finally, a numerical example illustrates the effectiveness of the developed event-based non-fragile estimator design method.

关键词： discrete time-varying systems deception attacks dynamic event-triggered mechanism finite horizon non-fragile estimation

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