Search Results - "Approximate Dynamic Programming"

Data-Driven Optimal Control via Linear Programming: Boundedness Guarantees by Falconi, Lucia, Martinelli, Andrea, Lygeros, John

“…The linear programming (LP) approach is, together with value iteration and policy iteration, one of the three fundamental methods to solve optimal control…”
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Online refueling policy for liner ships with offline learning by Liu, Haitao, Liang, Jinpeng, Li, Liming, Tan, Zhijia

“…•We model online refueling in liner shipping with distribution-free fuel prices as a finite-time MDP via Bellman equation.•We design a Bayesian GM model to…”
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A unified framework for efficient, effective, and fair resource allocation by food banks using an Approximate Dynamic Programming approach by Alkaabneh, Faisal, Diabat, Ali, Gao, Huaizhu Oliver

“…•We developed a framework for optimizing resource allocation by food banks.•A Markov Decision Process model of the problem was formulated.•The value function…”
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Reinforcement learning algorithms with function approximation: Recent advances and applications by Xu, Xin, Zuo, Lei, Huang, Zhenhua

“…In recent years, the research on reinforcement learning (RL) has focused on function approximation in learning prediction and control of Markov decision…”
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Opportunities for reinforcement learning in stochastic dynamic vehicle routing by Hildebrandt, Florentin D., Thomas, Barrett W., Ulmer, Marlin W.

“…There has been a paradigm-shift in urban logistic services in the last years; demand for real-time, instant mobility and delivery services grows. This poses…”
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Improved approximate dynamic programming for real-time economic dispatch of integrated microgrids by Lin, Zhiyi, Song, Chunyue, Zhao, Jun, Yin, Huan

“…Economic dispatch of electricity-heat microgrid is critical for real-time power generation and storage. However, conventional economic dispatch algorithms are…”
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Train trajectory optimization for improved on-time arrival under parametric uncertainty by Wang, Pengling, Trivella, Alessio, Goverde, Rob M.P., Corman, Francesco

“…•The uncertainty in traction effort and train resistance is considered.•An approximate dynamic programming approach for off-line value function learning.•A…”
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Dynamic Energy Management of a Microgrid Using Approximate Dynamic Programming and Deep Recurrent Neural Network Learning by Zeng, Peng, Li, Hepeng, He, Haibo, Li, Shuhui

“…This paper focuses on economical operation of a microgrid (MG) in real-time. A novel dynamic energy management system is developed to incorporate efficient…”
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A Reinforcement-Learning, Optimal Approach to In Situ Power Hardware-in-the-Loop Interface Control for Testing Inverter-Based Resources: Theory and Application of the Adaptive Dynamic Programming Based on the Hybrid Iteration to Tackle Uncertain Dynamics by Davari, Masoud, Qasem, Omar, Gao, Weinan, Blaabjerg, Frede, Kotsampopoulos, Panos C., Lauss, Georg, Hatziargyriou, Nikos D.

“…Testing inverter-based resources (IBRs) is of utmost importance. This paper proposes a novel power hardware-in-the-loop (PHIL) interface control (PHIL-IC)…”
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Adaptive Dynamic Programming for Control: A Survey and Recent Advances by Liu, Derong, Xue, Shan, Zhao, Bo, Luo, Biao, Wei, Qinglai

“…This article reviews the recent development of adaptive dynamic programming (ADP) with applications in control. First, its applications in optimal regulation…”
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Stochastic Optimization of Economic Dispatch for Microgrid Based on Approximate Dynamic Programming by Shuai, Hang, Fang, Jiakun, Ai, Xiaomeng, Tang, Yufei, Wen, Jinyu, He, Haibo

“…This paper proposes an approximate dynamic programming (ADP)-based approach for the economic dispatch (ED) of microgrid with distributed generations. The…”
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How good are learning-based control v.s. model-based control for load shifting? Investigations on a single zone building energy system by Fu, Yangyang, Xu, Shichao, Zhu, Qi, O’Neill, Zheng, Adetola, Veronica

“…Both model predictive control (MPC) and deep reinforcement learning control (DRL) have been presented as a way to approximate the true optimality of a dynamic…”
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Decentralized optimal large scale multi-player pursuit-evasion strategies: A mean field game approach with reinforcement learning by Zhou, Zejian, Xu, Hao

“…In this paper, the intelligent design for the pursuit-evasion game with large scale multi-pursuer and multi-evader has been investigated. Due to the vast…”
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Multi-Stage Real-Time Operation of a Multi-Energy Microgrid With Electrical and Thermal Energy Storage Assets: A Data-Driven MPC-ADP Approach by Li, Zhengmao, Wu, Lei, Xu, Yan, Moazeni, Somayeh, Tang, Zao

“…This paper studies the multi-stage real-time stochastic operation of grid-tied multi-energy microgrids (MEMGs) via the hybrid model predictive control (MPC)…”
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An approximate dynamic programming approach for the vehicle routing problem with stochastic demands by Novoa, Clara, Storer, Robert

“…This paper examines approximate dynamic programming algorithms for the single-vehicle routing problem with stochastic demands from a dynamic or reoptimization…”
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A novel dual iterative Q-learning method for optimal battery management in smart residential environments by Wei, Qinglai, Liu, Derong, Shi, Guang

“…In this paper, a novel iterative Q-learning method called "dual iterative Q-learning algorithm" is developed to solve the optimal battery management and…”
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Output feedback adaptive dynamic programming for linear differential zero-sum games by Rizvi, Syed Ali Asad, Lin, Zongli

“…This paper addresses the problem of finding optimal output feedback strategies for solving linear differential zero-sum games using a model-free approach based…”
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Robust optimal control for a class of nonlinear systems with unknown disturbances based on disturbance observer and policy iteration by Song, Ruizhuo, Lewis, Frank L.

“…A robust optimal control method for a class of nonlinear systems with unknown disturbances is addressed in this paper. In this framework, adaptive dynamic…”
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Influence of unmanned combat aerial vehicle agility on short-range aerial combat effectiveness by Wang, Maolin, Wang, Lixin, Yue, Ting, Liu, Hailiang

“…The flight agility of an unmanned combat aerial vehicle (UCAV) determines its ability to rapidly transition from one state to another. In this paper, the…”
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Approximate dynamic programming for planning a ride-hailing system using autonomous fleets of electric vehicles by Al-Kanj, Lina, Nascimento, Juliana, Powell, Warren B.

“…•A comprehensive mathematical model for an autonomous fleet of electric vehicles.•Optimizing over time by capturing the characteristics of the trips demand…”
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