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On Distributed Implementation of Switch-Based Adaptive Dynamic Programming
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DOI：10.1109/TCYB.2020.3029825.png)
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Abstract
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Switch-based adaptive dynamic programming (ADP) is an optimal control problem in which a cost must be minimized by switching among a family of dynamical modes. When the system dimension increases, the solution to switch-based ADP is made prohibitive by the exponentially increasing structure of the value function approximator and by the exponentially increasing modes. This technical correspondence proposes a distributed computational method for solving switch-based ADP. The method relies on partitioning the system into agents, each one dealing with a lower dimensional state and a few local modes. Each agent aims to minimize a local version of the global cost while avoiding that its local switching strategy has conflicts with the switching strategies of the neighboring agents. A heuristic algorithm based on the consensus dynamics and Nash equilibrium is proposed to avoid such conflicts. The effectiveness of the proposed method is verified via traffic and building test cases.
Keywords:
Switches
Neural networks
Games
Dynamic programming
Switched systems
Cybernetics
Consensus
distributed adaptive dynamic programming (ADP)
heuristic dynamic programming
optimal switching
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