检索结果-内蒙古大学图书馆

Approximate dynamic programming for Trajectory Tracking of Switched Systems

IEEE TRANSACTIONS ON AUTOMATIC CONTROL 2025年第2期70卷 1024-1037页

作者： Greene, Max L. Sakha, Masoud S. Kamalapurkar, Rushikesh Dixon, Warren E. Boeing Co Aurora Flight Sci Cambridge MA 02142 USA Univ Florida Dept Mech & Aerosp Engn Gainesville FL 32611 USA

This article develops a technique for online approximate optimization of tracking control policies for a family of switched nonlinear dynamical systems. Optimization is realized via approximate dynamic programming, and integral concurrent learning is used for robustness to parametric uncertainties. The family of switched systems is composed of finitely many subsystems, which may have differing characteristics, such as dynamics and cost functions. This article develops a new result on the analysis of switched systems comprised of locally practically stable subsystems using multiple Lyapunov-like functions. Local practical stability of the overall switched system and convergence of the applied tracking control policies to a neighborhood of the optimal tracking control policies is then proven for an arbitrary switching sequence provided that a set of sufficient gain conditions and a minimum dwell-time condition are satisfied. Simulation results are presented for the optimal control of an autonomous underwater vehicle in the presence of a set of discretely varying irrotational currents to show the efficacy of the developed technique.

关键词： Switches Switched systems Stability analysis Optimal control dynamic programming Optimization Vectors Adaptive control nonlinear systems optimal control switched systems

来源：评论

学校读者我要写书评

暂无评论

An Innovative Strategy Based on dynamic programming to Solve Power Flow Problems in Radial Electric Distribution Systems

引用

IEEE ACCESS 2025年 13卷 1012-1025页

作者： Marinho, Max R. Souza, Eliane S. Sperotto, Lucas K. Romero, Ruben Mato Grosso State Univ UNEMAT Dept Comp BR-78780000 Alto Araguaia Brazil Sao Paulo State Univ UNESP Dept Elect Engn BR-15385000 Ilha Solteira Brazil

In this work, a new strategy based on dynamic programming is proposed to solve the power flow (PF) problem in radial distribution systems using the backward/forward sweep method (BFSM). The strategy consists of a dynamic tree of varied children to represent the radial configuration of the system, allowing a new way of storing and accessing the system information for the PF calculation. This strategy avoids both the bus renumbering procedure for branch ordering used in different BFSMs (due to their branch-oriented characteristic) and the matrix inversion procedure, also used in different BFSMs. The proposed strategy is innovative, since PF problems have been solved in the literature by methods based on static programming. Tests with 14-bus, 33-bus, 84-bus, 136-bus, and 417-bus systems were carried to evaluate both the performance of the construction procedure of the dynamic tree in comparison to the classical branch ordering procedure and the performance of the PF calculation procedure using the proposed dynamic tree in contrast to traditional BFSMs. Promising results were obtained in both evaluated aspects. Therefore, this work contributes to the opening of new studies for a dynamic approach aimed at calculating the PF in radial distribution systems.

关键词： Voltage Substations Topology Proposals dynamic programming Mathematical models Load flow Heuristic algorithms Tree traversal Planning Backward/forward sweep method dynamic programming power flow problem radial electric distribution systems

来源：评论

学校读者我要写书评

暂无评论

Bidding in day-ahead electricity markets: A dynamic programming framework

引用

COMPUTERS & OPERATIONS RESEARCH 2025年 179卷

作者： De Boeck, Jerome Fortz, Bernard Labbe, Martine Marcotte, Etienne Marcotte, Patrice Savard, Gilles Univ Liege Management Sch HEC Liege Liege Belgium Univ Libre Bruxelles Brussels Belgium INRIA Lille Nord Europe INOCS Villeneuve Dascq France ServiceNow Res Montreal PQ Canada Univ Montreal DIRO Montreal PQ Canada Ecole Polytech Montreal Montreal PQ Canada

Strategic bidding problems have gained a lot of attention with the introduction of deregulated electricity markets where producers and retailers trade electricity in a day-ahead market run by a Market Operator (MO). All actors propose bids composed of a unit production price and a quantity of electricity to the MO. Based on these bids, the MO selects the most interesting ones and defines the spot price of electricity at which all actors are paid. As the bids of all actors determine the price of electricity, a bidding Generation Company (GC) faces a high risk regarding its profit when placing bids as the bids of competitors are not known in advance. This paper proposes a novel dynamic programming framework fora GC's Stochastic Bidding Problem (SBP) in the day-ahead market considering uncertainty over the competitor bids. We prove this problem is NP-hard and study two variants of this problem solved with the dynamic programming framework. Firstly, a relaxation provides an upper bound solved in polynomial time (SBP-R). Secondly, we consider a bidding problem using fixed bidding quantities (SBP-Q) that has previously been solved through heuristic methods. We prove that SBPQ is NP-hard and solve it to optimality in pseudo-polynomial time. SBP-Q is solved on much larger instances than in previous studies. We show on realistic instances that its optimal value is typically under 1% of the optimal value of SBP by using the upper bound provided by SBP-R.

关键词： Deregulated electricity markets Strategic bidding dynamic programming Stochastic optimization

来源：评论

学校读者我要写书评

暂无评论

Motion Planners for Path or Waypoint Following and End-Effector Sway Damping With dynamic programming

引用

IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING 2025年 22卷 8439-8452页

作者： Jebellat, Iman Sharf, Inna McGill Univ Dept Mech Engn Montreal PQ H3A 0C3 Canada

We propose two novel motion planners for a robotic manipulator with a passive end-effector that is free to sway during and after the robot's motion. The planners utilize dynamic programming to generate trajectories that damp the end-effector's residual sway while ensuring that the boom tip-the point to which the end-effector is attached-follows a collision-free path or time-dependent waypoints. Our use case is a crane of a forwarder machine, a log-loading machine in the forestry industry, with a passive grapple. In the cluttered forest environment, accurate path following and grapple sway damping are critical to increase the operation efficiency and avoid harming the machine and environment. The results of the simulation in a high-fidelity multibody-dynamics simulator showcase the effectiveness of our methodology in achieving exact path following or timed waypoints following and the residual sway damping. In particular, the average of the maximum residual sway is only $1.9<^>\circ$ , showing an average reduction of $75\%$ , as compared to fifth, sixth, and tenth order polynomial trajectories, in six test cases, including common paths used by operators to pick and place logs. Monte-Carlo simulations also showed that our planners have very good robustness against payload mass uncertainty. Other merits of our dynamic programming trajectories are that they are smooth, computationally inexpensive, and result in reduced residual sway even for nonzero initial sway conditions. Moreover, the generality of our methodology opens a new way to design anti-sway motion planners for construction cranes or quadrotors with a slung payload, in addition to serial manipulators with passive end-effectors. Note to Practitioners-This work was motivated by the problems arising in the operation of log-loading cranes in the forestry industry: the problems of the end-effector's large sway during crane reconfiguration and the collision between the crane and obstacles, which are detrimental to t

关键词： Cranes Trajectory Forestry Industries End effectors Payloads dynamic programming Damping Robots Robustness Motion planner dynamic programming passive end-effector sway damping path and timed waypoints forestry industry

来源：评论

学校读者我要写书评

暂无评论

Piecewise Linear Approximation of Battery Open-Circuit Voltage Characteristics Using dynamic programming

引用

IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT 2025年 74卷

作者： Sunil, Sooraj Pattipati, Krishna R. Balasingam, Balakumar Univ Windsor Dept Elect & Comp Engn Windsor ON N9B 3P4 Canada Univ Connecticut Dept Elect & Comp Engn Storrs CT 06269 USA

An open-circuit voltage (OCV) model, which represents OCV as a function of state of charge (SOC), is essential for estimating the state of a battery. Typically, the OCV-SOC characteristic is approximated using empirical functions, such as polynomials or lookup tables, and stored in a battery management system (BMS). However, polynomial approximations have several limitations: they are sensitive to floating-point errors, can be noninvertible, and require a high-precision computing system for numerical inverse lookups (determining the SOC for a given OCV). Moreover, many OCV models fail to maintain the monotonicity of the OCV-SOC relationship, especially in resource-constrained environments. While table-based (or piecewise linear) approaches have been explored, existing methods often fall short of preserving the accuracy of the OCV-SOC curve with a minimal number of breakpoints. This article introduces a novel dynamic programming approach to model the OCV-SOC characteristic as piecewise line segments. Compared to existing piecewise models, the proposed approach is more resource-efficient in systematically reducing the required table breakpoints while maintaining optimal accuracy. Experimental validation across various lithium-ion chemistries at four ambient temperatures consistently demonstrated a root mean square error below 5 mV. Additionally, differential feature extraction and segmented correlation analysis highlight the model's effectiveness in estimating the battery's state of health (SOH).

关键词： Computational modeling State of charge Batteries Numerical models Polynomials Accuracy Piecewise linear approximation Data models dynamic programming Splines (mathematics) Battery management systems (BMSs) battery modeling dynamic programming lithium-ion batteries open-circuit voltage (OCV) model piecewise linear approximation state of charge (SOC) state of health (SOH)

来源：评论

学校读者我要写书评

暂无评论

Optimal Vehicle-to-Grid Charge Scheduling for Electric Vehicles Based on dynamic programming

引用

ENERGIES 2025年第5期18卷 1109-1109页

作者： Lee, Heeyun Kim, Hyunjoong Kim, Hyewon Kim, Hyunsup Dankook Univ Dept Mech Engn Yongin 16890 South Korea Hyundai Motor Co R&D Ctr Hwaseong 18280 Gyeonggi Do South Korea

Recently, as the market share of electric vehicles (EVs) has increased, how to handle the increased electricity demand for EV charging in the power grid and how to use EV batteries from a grid-operating aspect have become more important. Also, from the perspective of individual EVs, Vehicle-to-Grid (V2G) technologies that reduce the cost for each vehicle's charging in conjunction with the power grid are significant. In this paper, the V2G control problem at the individual vehicle level is studied using a dynamic programming (DP) algorithm that considers EVs' charging efficiency. The DP algorithm is developed to generate an optimized charging/discharging power profile that minimizes electricity costs, while satisfying the constraints of the initial and final battery states of charge, for given a time-of-use electricity price. To show the effectiveness of the proposed algorithm, simulation is conducted for three different charging scenarios (unidirectional charging, bidirectional charging, and unidirectional charging with cost variations based on electricity usage), and the results showed that DP can achieve significant cost savings of about 30% compared to the normal charging method. Also, the result of DP is compared with that of Linear programming, demonstrating that DP outperforms Linear programming in cost savings for the V2G control problem.

关键词： dynamic programming electric vehicles optimal control vehicle-to-grid (V2G)

来源：评论

学校读者我要写书评

暂无评论

Distributed Adaptive dynamic programming for Consensus Control of Multiagent Systems Within Hierarchical Stackelberg-Nash Game Framework

引用

IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS 2025年

作者： Zhang, Haoyan Zhang, Yingwei Zhao, Xudong Su, Chun-Yi Northeastern Univ Sch Informat Sci & Engn Shenyang 110819 Peoples R China Northeastern Univ State Lab Synth Automat Proc Ind Shenyang 110819 Peoples R China Dalian Univ Technol Fac Elect Informat & Elect Engn Dalian 116024 Peoples R China Bohai Univ Coll Control Sci & Engn Jinzhou 121013 Peoples R China Concordia Univ Dept Mech & Ind Engn Montreal PQ H3B 1R6 Canada

This article investigates the leader-follower consensus for nonlinear multiagent systems (MASs) and proposes an adaptive dynamic programming (ADP)-based hierarchical Stackelberg-Nash optimal game control method. Initially, a coupled performance index function associated with consensus errors is constructed. As the positive-definite function with the quadratic form is allocated to the constructed consensus errors-based performance index function, the original system stabilization problem is converted into the issue of seeking an optimal control strategy profile for the leader and followers. Under the hierarchical Stackelberg-Nash differential game framework, the optimal control strategies are derived in sequence and further proved to compose the equilibrium points of Stackelberg-Nash differential games. Afterward, based on the ADP technique, a modified single-critic neural network (NN) is implemented and the coupled Hamilton-Jacobi-Bellman (HJB) equation is approximately identified. Under the proposed control scheme, the leader-follower consensus of the considered MAS can be achieved while consuming less control cost. Meanwhile, all signals of the MAS are ensured to be uniformly ultimately bounded. Finally, a numerical simulation and an application to the electrode regulating system of the three-phase electric arc furnace are given to verify the effectiveness of the proposed control method.

关键词： Games Differential games Optimal control dynamic programming Performance analysis Nash equilibrium Multi-agent systems Artificial neural networks Vectors Topology Distributed adaptive dynamic programming (ADP) hierarchical Stackelberg-Nash game leader-follower consensus nonlinear multiagent systems (MASs) single-critic neural network (NN)

来源：评论

学校读者我要写书评

暂无评论

New dynamic programming algorithm for the Multiobjective Minimum Spanning Tree problem

引用

COMPUTERS & OPERATIONS RESEARCH 2025年 173卷

作者： de las Casas, Pedro Maristany Sedeno-Noda, Antonio Borndoerfer, Ralf Zuse Inst Berlin Network Optimizat Takustr 7 D-14195 Berlin Germany Univ La Laguna Matemat Estadist & Invest Operat San Cristobal De La Lagun 38271 Spain

The Multiobjective Minimum Spanning Tree (MO-MST) problem generalizes the Minimum Spanning Tree problem by weighting the edges of the input graph using vectors instead of scalars. In this paper, we design a new dynamic programming MO-MST algorithm. dynamic programming for a MO-MST instance requests solving a One-to-One Multiobjective Shortest Path (MOSP) instance and both instances have equivalent solution sets. The MOSP instance is defined on a so called transition graph. We study the original size of this graph in detail and reduce its size using cost-dependent arc pruning criteria. To solve the MOSP instance on the reduced transition graph, , we design the Implicit Graph Multiobjective Dijkstra Algorithm (IG-MDA), exploiting recent improvements on MOSP algorithms from the literature. All in all, the new IG-MDA outperforms the current state of the art on a big set of instances from the literature. Our code and results are publicly available.

关键词： Multiple objective programming Multiobjective Minimum Spanning Trees dynamic programming

来源：评论

学校读者我要写书评

暂无评论

Analytical dispatch strategies for pumped storage hydro: A conditional dynamic programming approach to discontinuous multi-period optimization problems

引用

APPLIED ENERGY 2025年 383卷

作者： Liu, Jian Zhang, Jianwen Gong, Zaiwu Wunsch, Donald C. Bo, Rui Nanjing Univ Informat Sci & Technol Sch Management Sci & Engn Nanjing 210044 Jiangsu Peoples R China Missouri Univ Sci & Technol Kummer Inst Ctr Artificial Intelligence & Autonomous Syst Rolla MO 65409 USA Missouri Univ Sci & Technol Dept Elect & Comp Engn Rolla MO 65409 USA

The increasing integration of renewable energy sources like wind and solar poses significant challenges to secure and stable grid operation. Energy storage systems, particularly pumped storage hydro (PSH), play a crucial role in balancing power supply and demand. Traditional analytical studies of PSH economic dispatch problems often assume zero lower bounds for generating and pumping rates to simplify analysis and derive analytical solutions for multi-period optimization problems. However, the inherent mechanical design constraints of PSH require non-zero minimum flow rates for efficient operation. We analyze two scenarios, merchants having PSH only and merchants having both PSH and wind farms. In the PSH-only scenario, four analytically determined State of Charge (SOC) reference points divide the SOC range into five sub-regions, each corresponding to a specific optimal decision. In the co-optimized PSH and wind farms scenario, five SOC reference points split the SOC range into six sub-regions. By simply comparing the current SOC with these reference points in the next period, users can derive unique, analytically optimal economic dispatch decisions for each period. Our findings indicate that non-zero minimum capacity constraints significantly influence the optimal dispatch strategy, increasing the likelihood of PSH systems remaining idle and potentially reducing arbitrage profits. We validate our proposed approach using both synthesized data and real data from the Midcontinent Independent System Operator, demonstrating its practical applicability. This methodology represents a significant advancement in energy storage dispatch strategies by providing scalable, analytically optimal solutions for multi-period optimization problems, enhancing economic efficiency in the management of energy storage systems.

关键词： Energy storage Pumped storage hydropower Renewable energy sources Economic dispatch State of charge dynamic programming Discontinuous constraints Optimization

来源：评论

学校读者我要写书评

暂无评论

Globally optimal sequencing of optimal reactive dispatch control adjustments to minimize operational losses in transmission systems by graph shortest path, parallel computing, and dynamic programming

引用

EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2025年第1期320卷 239-255页

作者： Barros, Rafael Martins Lage, Guilherme Guimaraes Rabelo, Ricardo de Andrade Lira Univ Fed Ceara UFC Ave Profa Machadinha Lima s-n BR-63708825 Crateus CE Brazil Univ Fed Sao Carlos UFSCar Dept Engn Elect Rod Washington Luis SP-310 km 235 BR-13565905 Sao Carlos SP Brazil Campus Univ Minist Petronio Portella Univ Fed Piaui UFPI Dept Ciencia Computacao BR-64049550 Teresina PI Brazil

Minimizing operational losses in transmission systems through the Optimal Reactive Dispatch (ORD), a non- convex mixed-integer nonlinear programming problem, is crucial for operational cost reduction, resource optimization, and greenhouse gas emission mitigation. Besides all intricacies associated with solving ORDs, transmission system operators encounter the challenge of determining sequences in which ORD control adjustments must be implemented before significant changes occur in generators scheduled power output and system loading. Sequencing ORD control adjustments, in spite of not being novel, remains modestly scrutinized in the literature. This paper introduces a two-phase framework that tackles the globally optimal sequencing of n ORD control adjustments over n ! potential paths by solving the ORD to minimize operational losses in transmission systems in the first phase, and optimally sequencing ORD control adjustments employing fast power flow calculations, graph shortest path, parallel computing, and dynamic programming in the second phase. We discuss the framework's second phase asymptotic time complexity, which is exponential over factorial for brute-force approaches, and its capability to guarantee globally optimal paths toward minimal operational losses determined in the framework's first phase. ORD control adjustments for transmission systems with up to 27 controllable variables are benchmarked against two mixed-integer nonlinear programming solvers: BARON, a global non-convex solver, and Knitro, a local solver (assuming convexity around local optima). Globally optimal sequences of ORD control adjustments over n ! potential paths (more than 10 28 for sequencing 27 control adjustments) and average algorithm runtimes validate the straightforward application and, more importantly, effectiveness of such a comprehensive framework.

关键词： OR in energy dynamic programming Graph shortest path Optimal power flow Parallel computing

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：