In the era of exponential growth of data availability, the architecture of systems has a trend toward high dimensionality, and directly exploiting holistic information for state inference is not always computationally affordable. This paper proposes a novel Bayesian filtering algorithm that considers algorithmic computational cost and estimation accuracy for high-dimensional linear systems. The high-dimensional state vector is divided into several blocks to save computation resources by avoiding the calculation of error covariance with immense dimensions. After that, two sequential states are estimated simultaneously by introducing an auxiliary variable in the new probability space, mitigating the performance degradation caused by state segmentation. Moreover, the computational cost and error covariance of the proposed algorithm are analyzed analytically to show its distinct features compared with several existing methods. Simulation results illustrate that the proposed Bayesian filtering can maintain a higher estimation accuracy with reasonable computational cost when applied to high-dimensional linear systems.
{"title":"Bayesian Filtering for High-Dimensional State-Space Models With State Partition and Error Compensation","authors":"Ke Li;Shunyi Zhao;Biao Huang;Fei Liu","doi":"10.1109/JAS.2023.124137","DOIUrl":"https://doi.org/10.1109/JAS.2023.124137","url":null,"abstract":"In the era of exponential growth of data availability, the architecture of systems has a trend toward high dimensionality, and directly exploiting holistic information for state inference is not always computationally affordable. This paper proposes a novel Bayesian filtering algorithm that considers algorithmic computational cost and estimation accuracy for high-dimensional linear systems. The high-dimensional state vector is divided into several blocks to save computation resources by avoiding the calculation of error covariance with immense dimensions. After that, two sequential states are estimated simultaneously by introducing an auxiliary variable in the new probability space, mitigating the performance degradation caused by state segmentation. Moreover, the computational cost and error covariance of the proposed algorithm are analyzed analytically to show its distinct features compared with several existing methods. Simulation results illustrate that the proposed Bayesian filtering can maintain a higher estimation accuracy with reasonable computational cost when applied to high-dimensional linear systems.","PeriodicalId":54230,"journal":{"name":"Ieee-Caa Journal of Automatica Sinica","volume":null,"pages":null},"PeriodicalIF":11.8,"publicationDate":"2024-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140556008","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This study addresses the problem of global asymptotic stability for uncertain complex cascade systems composed of multiple integrator systems and non-strict feedforward nonlinear systems. To tackle the complexity inherent in such structures, a novel nested saturated control design is proposed that incorporates both constant saturation levels and state-dependent saturation levels. Specifically, a modified differentiable saturation function is proposed to facilitate the saturation reduction analysis of the uncertain complex cascade systems under the presence of mixed saturation levels. In addition, the design of modified differentiable saturation function will help to construct a hierarchical global convergence strategy to improve the robustness of control design scheme. Through calculation of relevant inequalities, time derivative of boundary surface and simple Lyapunov function, saturation reduction analysis and convergence analysis are carried out, and then a set of explicit parameter conditions are provided to ensure global asymptotic stability in the closed-loop systems. Finally, a simplified system of the mechanical model is presented to validate the effectiveness of the proposed method.
{"title":"Nested Saturated Control of Uncertain Complex Cascade Systems Using Mixed Saturation Levels","authors":"Meng Li;Zhigang Zeng","doi":"10.1109/JAS.2023.124176","DOIUrl":"https://doi.org/10.1109/JAS.2023.124176","url":null,"abstract":"This study addresses the problem of global asymptotic stability for uncertain complex cascade systems composed of multiple integrator systems and non-strict feedforward nonlinear systems. To tackle the complexity inherent in such structures, a novel nested saturated control design is proposed that incorporates both constant saturation levels and state-dependent saturation levels. Specifically, a modified differentiable saturation function is proposed to facilitate the saturation reduction analysis of the uncertain complex cascade systems under the presence of mixed saturation levels. In addition, the design of modified differentiable saturation function will help to construct a hierarchical global convergence strategy to improve the robustness of control design scheme. Through calculation of relevant inequalities, time derivative of boundary surface and simple Lyapunov function, saturation reduction analysis and convergence analysis are carried out, and then a set of explicit parameter conditions are provided to ensure global asymptotic stability in the closed-loop systems. Finally, a simplified system of the mechanical model is presented to validate the effectiveness of the proposed method.","PeriodicalId":54230,"journal":{"name":"Ieee-Caa Journal of Automatica Sinica","volume":null,"pages":null},"PeriodicalIF":11.8,"publicationDate":"2024-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140555875","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Dear Editor, This letter focuses on the fixed-time (FXT) cluster optimization problem of first-order multi-agent systems (FOMASs) in an undirected network, in which the optimization objective is the sum of the objective functions of all clusters. A novel piecewise power-law control protocol with cooperative-competition relations is proposed. Furthermore, a sufficient condition is obtained to ensure that the FOMASs achieve the cluster consensus within an FXT. Then, on the basis of maintaining the cluster consensus, the agents in each cluster converge to the optimal solution of their objective functions in another FXT.
{"title":"Fixed-Time Cluster Optimization for Multi-Agent Systems Based on Piecewise Power-Law Design","authors":"Suna Duan;Xinchun Jia;Xiaobo Chi","doi":"10.1109/JAS.2024.124230","DOIUrl":"https://doi.org/10.1109/JAS.2024.124230","url":null,"abstract":"Dear Editor, This letter focuses on the fixed-time (FXT) cluster optimization problem of first-order multi-agent systems (FOMASs) in an undirected network, in which the optimization objective is the sum of the objective functions of all clusters. A novel piecewise power-law control protocol with cooperative-competition relations is proposed. Furthermore, a sufficient condition is obtained to ensure that the FOMASs achieve the cluster consensus within an FXT. Then, on the basis of maintaining the cluster consensus, the agents in each cluster converge to the optimal solution of their objective functions in another FXT.","PeriodicalId":54230,"journal":{"name":"Ieee-Caa Journal of Automatica Sinica","volume":null,"pages":null},"PeriodicalIF":11.8,"publicationDate":"2024-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10500722","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140555930","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A long history has passed since electromyography (EMG) signals have been explored in human-centered robots for intuitive interaction. However, it still has a gap between scientific research and real-life applications. Previous studies mainly focused on EMG decoding algorithms, leaving a dynamic relationship between the human, robot, and uncertain environment in real-life scenarios seldomly concerned. To fill this gap, this paper presents a comprehensive review of EMG-based techniques in human-robot-environment interaction (HREI) systems. The general processing framework is summarized, and three interaction paradigms, including direct control, sensory feedback, and partial autonomous control, are introduced. EMG-based intention decoding is treated as a module of the proposed paradigms. Five key issues involving precision, stability, user attention, compliance, and environmental awareness in this field are discussed. Several important directions, including EMG decomposition, robust algorithms, HREI dataset, proprioception feedback, reinforcement learning, and embodied intelligence, are proposed to pave the way for future research. To the best of what we know, this is the first time that a review of EMG-based methods in the HREI system is summarized. It provides a novel and broader perspective to improve the practicability of current myoelectric interaction systems, in which factors in human-robot interaction, robot-environment interaction, and state perception by human sensations are considered, which has never been done by previous studies.
{"title":"Intuitive Human-Robot-Environment Interaction with EMG Signals: A Review","authors":"Dezhen Xiong;Daohui Zhang;Yaqi Chu;Yiwen Zhao;Xingang Zhao","doi":"10.1109/JAS.2024.124329","DOIUrl":"https://doi.org/10.1109/JAS.2024.124329","url":null,"abstract":"A long history has passed since electromyography (EMG) signals have been explored in human-centered robots for intuitive interaction. However, it still has a gap between scientific research and real-life applications. Previous studies mainly focused on EMG decoding algorithms, leaving a dynamic relationship between the human, robot, and uncertain environment in real-life scenarios seldomly concerned. To fill this gap, this paper presents a comprehensive review of EMG-based techniques in human-robot-environment interaction (HREI) systems. The general processing framework is summarized, and three interaction paradigms, including direct control, sensory feedback, and partial autonomous control, are introduced. EMG-based intention decoding is treated as a module of the proposed paradigms. Five key issues involving precision, stability, user attention, compliance, and environmental awareness in this field are discussed. Several important directions, including EMG decomposition, robust algorithms, HREI dataset, proprioception feedback, reinforcement learning, and embodied intelligence, are proposed to pave the way for future research. To the best of what we know, this is the first time that a review of EMG-based methods in the HREI system is summarized. It provides a novel and broader perspective to improve the practicability of current myoelectric interaction systems, in which factors in human-robot interaction, robot-environment interaction, and state perception by human sensations are considered, which has never been done by previous studies.","PeriodicalId":54230,"journal":{"name":"Ieee-Caa Journal of Automatica Sinica","volume":null,"pages":null},"PeriodicalIF":11.8,"publicationDate":"2024-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140555999","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The opaque property plays an important role in the operation of a security-critical system, implying that pre-defined secret information of the system is not able to be inferred through partially observing its behavior. This paper addresses the verification of current-state, initial-state, infinite-step, and $K$ -step opacity of networked discrete event systems modeled by labeled Petri nets, where communication losses and delays are considered. Based on the symbolic technique for the representation of states in Petri nets, an observer and an estimator are designed for the verification of current-state and initial-state opacity, respectively. Then, we propose a structure called an I-observer that is combined with secret states to verify whether a networked discrete event system is infinite-step opaque or $K$ -step opaque. Due to the utilization of symbolic approaches for the state-based opacity verification, the computation of the reachability graphs of labeled Petri nets is avoided, which dramatically reduces the computational overheads stemming from networked discrete event systems.
不透明特性在安全关键型系统的运行中起着重要作用，它意味着无法通过部分观察其行为来推断系统的预定义秘密信息。本文探讨了由标记 Petri 网建模的网络离散事件系统的当前状态、初始状态、无限步和 $K$ 步不透明性的验证问题，其中考虑了通信损耗和延迟。基于在 Petri 网中表示状态的符号技术，我们设计了一个观测器和一个估计器，分别用于验证当前状态和初始状态的不透明度。然后，我们提出了一种称为 I- 观察器的结构，它与秘密状态相结合，可验证网络离散事件系统是无限步不透明还是 $K$ 步不透明。由于在基于状态的不透明验证中使用了符号方法，因此避免了计算标记 Petri 网的可达性图，从而大大减少了网络离散事件系统的计算开销。
{"title":"State-Based Opacity Verification of Networked Discrete Event Systems Using Labeled Petri Nets","authors":"Yifan Dong;Naiqi Wu;Zhiwu Li","doi":"10.1109/JAS.2023.124128","DOIUrl":"https://doi.org/10.1109/JAS.2023.124128","url":null,"abstract":"The opaque property plays an important role in the operation of a security-critical system, implying that pre-defined secret information of the system is not able to be inferred through partially observing its behavior. This paper addresses the verification of current-state, initial-state, infinite-step, and \u0000<tex>$K$</tex>\u0000-step opacity of networked discrete event systems modeled by labeled Petri nets, where communication losses and delays are considered. Based on the symbolic technique for the representation of states in Petri nets, an observer and an estimator are designed for the verification of current-state and initial-state opacity, respectively. Then, we propose a structure called an I-observer that is combined with secret states to verify whether a networked discrete event system is infinite-step opaque or \u0000<tex>$K$</tex>\u0000-step opaque. Due to the utilization of symbolic approaches for the state-based opacity verification, the computation of the reachability graphs of labeled Petri nets is avoided, which dramatically reduces the computational overheads stemming from networked discrete event systems.","PeriodicalId":54230,"journal":{"name":"Ieee-Caa Journal of Automatica Sinica","volume":null,"pages":null},"PeriodicalIF":11.8,"publicationDate":"2024-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140555876","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Kaiyuan Chen;Runqi Chai;Runda Zhang;Zhida Xing;Yuanqing Xia;Guoping Liu
Dear Editor, This letter presents a novel data-driven trajectory planning and control scheme for the unmanned ground vehicles (UGVs). A recent work [1] has demonstrated the effectiveness of approximating the optimal state feedback for a nonlinear unmanned system via deep neural network (DNN). To further the previous research, we construct a long-short term memory recurrent deep neural network (LSTMRDNN) to improve the performance of the data-driven approximation instrument. The proposed strategy is evaluated and verified through theoretical analyses and experiments.
{"title":"A Data-Driven Real-Time Trajectory Planning and Control Methodology for UGVs Using LSTMRDNN","authors":"Kaiyuan Chen;Runqi Chai;Runda Zhang;Zhida Xing;Yuanqing Xia;Guoping Liu","doi":"10.1109/JAS.2024.124269","DOIUrl":"https://doi.org/10.1109/JAS.2024.124269","url":null,"abstract":"Dear Editor, This letter presents a novel data-driven trajectory planning and control scheme for the unmanned ground vehicles (UGVs). A recent work [1] has demonstrated the effectiveness of approximating the optimal state feedback for a nonlinear unmanned system via deep neural network (DNN). To further the previous research, we construct a long-short term memory recurrent deep neural network (LSTMRDNN) to improve the performance of the data-driven approximation instrument. The proposed strategy is evaluated and verified through theoretical analyses and experiments.","PeriodicalId":54230,"journal":{"name":"Ieee-Caa Journal of Automatica Sinica","volume":null,"pages":null},"PeriodicalIF":11.8,"publicationDate":"2024-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10500708","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140555877","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The shipboard landing problem for a quadrotor is addressed in this paper, where the ship trajectory tracking control issue is transformed into a stabilization control issue by building a relative position model. To guarantee both transient performance and steady-state landing error, a prescribed performance evolution control (PPEC) method is developed for the relative position control. In addition, a novel compensation system is proposed to expand the performance boundaries when the input saturation occurs and the error exceeds the predefined threshold. Considering the wind and wave on the relative position model, an adaptive sliding mode observer (ASMO) is designed for the disturbance with unknown upper bound. Based on the dynamic surface control framework, a shipboard landing controller integrating PPEC and ASMO is established for the quadrotor, and the relative position control error is guaranteed to be uniformly ultimately bounded. Simulation results have verified the feasibility and effectiveness of the proposed shipboard landing control scheme.
{"title":"Prescribed Performance Evolution Control for Quadrotor Autonomous Shipboard Landing","authors":"Yang Yuan;Haibin Duan;Zhigang Zeng","doi":"10.1109/JAS.2024.124254","DOIUrl":"https://doi.org/10.1109/JAS.2024.124254","url":null,"abstract":"The shipboard landing problem for a quadrotor is addressed in this paper, where the ship trajectory tracking control issue is transformed into a stabilization control issue by building a relative position model. To guarantee both transient performance and steady-state landing error, a prescribed performance evolution control (PPEC) method is developed for the relative position control. In addition, a novel compensation system is proposed to expand the performance boundaries when the input saturation occurs and the error exceeds the predefined threshold. Considering the wind and wave on the relative position model, an adaptive sliding mode observer (ASMO) is designed for the disturbance with unknown upper bound. Based on the dynamic surface control framework, a shipboard landing controller integrating PPEC and ASMO is established for the quadrotor, and the relative position control error is guaranteed to be uniformly ultimately bounded. Simulation results have verified the feasibility and effectiveness of the proposed shipboard landing control scheme.","PeriodicalId":54230,"journal":{"name":"Ieee-Caa Journal of Automatica Sinica","volume":null,"pages":null},"PeriodicalIF":11.8,"publicationDate":"2024-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140555929","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
For bipartite angle consensus tracking and vibration suppression of multiple Timoshenko manipulator systems with time-varying actuator faults, parameter and modeling uncertainties, and unknown disturbances, a novel distributed boundary event-triggered control strategy is proposed in this work. In contrast to the earlier findings, time-varying consensus tracking and actuator defects are taken into account simultaneously. In addition, the constructed event-triggered control mechanism can achieve a more flexible design because it is not required to satisfy the input-to-state condition. To achieve the control objectives, some new integral control variables are given by using back-stepping technique and boundary control. Moreover, adaptive neural networks are applied to estimate system uncertainties. With the proposed event-triggered scheme, control inputs can reduce unnecessary updates. Besides, tracking errors and vibration states of the closed-looped network can be exponentially convergent into some small fields, and Zeno behaviors can be excluded. At last, some simulation examples are given to state the effectiveness of the control algorithms.
{"title":"Event-Triggered Bipartite Consensus Tracking and Vibration Control of Flexible Timoshenko Manipulators Under Time-Varying Actuator Faults","authors":"Xiangqian Yao;Hao Sun;Zhijia Zhao;Yu Liu","doi":"10.1109/JAS.2024.124266","DOIUrl":"https://doi.org/10.1109/JAS.2024.124266","url":null,"abstract":"For bipartite angle consensus tracking and vibration suppression of multiple Timoshenko manipulator systems with time-varying actuator faults, parameter and modeling uncertainties, and unknown disturbances, a novel distributed boundary event-triggered control strategy is proposed in this work. In contrast to the earlier findings, time-varying consensus tracking and actuator defects are taken into account simultaneously. In addition, the constructed event-triggered control mechanism can achieve a more flexible design because it is not required to satisfy the input-to-state condition. To achieve the control objectives, some new integral control variables are given by using back-stepping technique and boundary control. Moreover, adaptive neural networks are applied to estimate system uncertainties. With the proposed event-triggered scheme, control inputs can reduce unnecessary updates. Besides, tracking errors and vibration states of the closed-looped network can be exponentially convergent into some small fields, and Zeno behaviors can be excluded. At last, some simulation examples are given to state the effectiveness of the control algorithms.","PeriodicalId":54230,"journal":{"name":"Ieee-Caa Journal of Automatica Sinica","volume":null,"pages":null},"PeriodicalIF":11.8,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140556055","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Battery energy storage systems (BESSs) are widely used in smart grids. However, power consumed by inner impedance and the capacity degradation of each battery unit become particularly severe, which has resulted in an increase in operating costs. The general economic dispatch (ED) algorithm based on marginal cost (MC) consensus is usually a proportional (P) controller, which encounters the defects of slow convergence speed and low control accuracy. In order to solve the distributed ED problem of the isolated BESS network with excellent dynamic and steady-state performance, we attempt to design a proportional integral (PI) controller with a reset mechanism (PI+R) to asymptotically promote MC consensus and total power mismatch towards 0 in this paper. To be frank, the integral term in the PI controller is reset to 0 at an appropriate time when the proportional term undergoes a zero crossing, which accelerates convergence, improves control accuracy, and avoids overshoot. The eigenvalues of the system under a PI+R controller is well analyzed, ensuring the regularity of the system and enabling the reset mechanism. To ensure supply and demand balance within the isolated BESSs, a centralized reset mechanism is introduced, so that the controller is distributed in a flow set and centralized in a jump set. To cope with Zeno behavior and input delay, a dwell time that the system resides in a flow set is given. Based on this, the system with input delays can be reduced to a time-delay free system. Considering the capacity limitation of the battery, a modified MC scheme with PI+R controller is designed. The correctness of the designed scheme is verified through relevant simulations.
电池储能系统（BESS）被广泛应用于智能电网。然而，内部阻抗消耗的电能和每个电池单元的容量衰减变得尤为严重，这导致了运行成本的增加。基于边际成本（MC）共识的一般经济调度（ED）算法通常采用比例（P）控制器，存在收敛速度慢、控制精度低的缺陷。为了以优异的动态和稳态性能解决孤立 BESS 网络的分布式 ED 问题，本文尝试设计一种带有复位机制（PI+R）的比例积分（PI）控制器，以渐进地促进 MC 共识和总功率失配趋于 0。坦率地说，当比例项过零时，PI 控制器中的积分项会适时重置为 0，从而加快收敛速度、提高控制精度并避免超调。在 PI+R 控制器下，系统的特征值得到了很好的分析，确保了系统的正则性，并实现了复位机制。为确保隔离 BESS 内的供需平衡，引入了集中复位机制，使控制器分布于流量集，集中于跳跃集。为了应对 Zeno 行为和输入延迟，给出了系统在流量集中的停留时间。在此基础上，有输入延迟的系统可以简化为无时延系统。考虑到电池容量的限制，设计了一种带有 PI+R 控制器的改进 MC 方案。通过相关模拟验证了所设计方案的正确性。
{"title":"A PI+R Control Scheme Based on Multi-Agent Systems for Economic Dispatch in Isolated BESSs","authors":"Yalin Zhang;Zhongxin Liu;Zengqiang Chen","doi":"10.1109/JAS.2024.124236","DOIUrl":"https://doi.org/10.1109/JAS.2024.124236","url":null,"abstract":"Battery energy storage systems (BESSs) are widely used in smart grids. However, power consumed by inner impedance and the capacity degradation of each battery unit become particularly severe, which has resulted in an increase in operating costs. The general economic dispatch (ED) algorithm based on marginal cost (MC) consensus is usually a proportional (P) controller, which encounters the defects of slow convergence speed and low control accuracy. In order to solve the distributed ED problem of the isolated BESS network with excellent dynamic and steady-state performance, we attempt to design a proportional integral (PI) controller with a reset mechanism (PI+R) to asymptotically promote MC consensus and total power mismatch towards 0 in this paper. To be frank, the integral term in the PI controller is reset to 0 at an appropriate time when the proportional term undergoes a zero crossing, which accelerates convergence, improves control accuracy, and avoids overshoot. The eigenvalues of the system under a PI+R controller is well analyzed, ensuring the regularity of the system and enabling the reset mechanism. To ensure supply and demand balance within the isolated BESSs, a centralized reset mechanism is introduced, so that the controller is distributed in a flow set and centralized in a jump set. To cope with Zeno behavior and input delay, a dwell time that the system resides in a flow set is given. Based on this, the system with input delays can be reduced to a time-delay free system. Considering the capacity limitation of the battery, a modified MC scheme with PI+R controller is designed. The correctness of the designed scheme is verified through relevant simulations.","PeriodicalId":54230,"journal":{"name":"Ieee-Caa Journal of Automatica Sinica","volume":null,"pages":null},"PeriodicalIF":15.3,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142137593","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Ingredient optimization plays a pivotal role in the copper industry, for which it is closely related to the concentrate utilization rate, stability of furnace conditions, and the quality of copper production. To acquire a practical ingredient plan, which should exhibit long duration time with sufficient utilization and feeding stability for real applications, an ingredient plan optimization model is proposed in this study to effectively guarantee continuous production and stable furnace conditions. To address the complex challenges posed by this integer programming model, including multiple coupling feeding stages, intricate constraints, and significant non-linearity, a multi-stage differential-multifac-torial evolution algorithm is developed. In the proposed algorithm, the differential evolutionary (DE) algorithm is improved in three aspects to efficiently tackle challenges when optimizing the proposed model. First, unlike traditional time-consuming serial approaches, the multifactorial evolutionary algorithm is utilized to optimize multiple complex models contained in the population of evolutionary algorithm caused by the feeding stability in a parallel manner. Second, a repair algorithm is employed to adjust infeasible ingredient lists in a timely manner. In addition, a local search strategy taking feedback from the current optima and considering the different positions of global optimum is developed to avoiding premature convergence of the differential evolutionary algorithm. Finally, the simulation experiments considering different planning horizons using real data from the copper industry in China are conducted, which demonstrates the superiority of the proposed method on feeding duration and stability compared with other commonly deployed approaches. It is practically helpful for reducing material cost as well as increasing production profit for the copper industry.
{"title":"A Multi-Stage Differential-Multifactorial Evolutionary Algorithm for Ingredient Optimization in the Copper Industry","authors":"Xuerui Zhang;Zhongyang Han;Jun Zhao","doi":"10.1109/JAS.2023.124116","DOIUrl":"https://doi.org/10.1109/JAS.2023.124116","url":null,"abstract":"Ingredient optimization plays a pivotal role in the copper industry, for which it is closely related to the concentrate utilization rate, stability of furnace conditions, and the quality of copper production. To acquire a practical ingredient plan, which should exhibit long duration time with sufficient utilization and feeding stability for real applications, an ingredient plan optimization model is proposed in this study to effectively guarantee continuous production and stable furnace conditions. To address the complex challenges posed by this integer programming model, including multiple coupling feeding stages, intricate constraints, and significant non-linearity, a multi-stage differential-multifac-torial evolution algorithm is developed. In the proposed algorithm, the differential evolutionary (DE) algorithm is improved in three aspects to efficiently tackle challenges when optimizing the proposed model. First, unlike traditional time-consuming serial approaches, the multifactorial evolutionary algorithm is utilized to optimize multiple complex models contained in the population of evolutionary algorithm caused by the feeding stability in a parallel manner. Second, a repair algorithm is employed to adjust infeasible ingredient lists in a timely manner. In addition, a local search strategy taking feedback from the current optima and considering the different positions of global optimum is developed to avoiding premature convergence of the differential evolutionary algorithm. Finally, the simulation experiments considering different planning horizons using real data from the copper industry in China are conducted, which demonstrates the superiority of the proposed method on feeding duration and stability compared with other commonly deployed approaches. It is practically helpful for reducing material cost as well as increasing production profit for the copper industry.","PeriodicalId":54230,"journal":{"name":"Ieee-Caa Journal of Automatica Sinica","volume":null,"pages":null},"PeriodicalIF":15.3,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142137528","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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