Heuristic Dynamic Programming Using Echo State Network For Multivariable Tracking Control Of Wastewater Treatment Process

DOI10.1002/ASJC.994zbMath1333.90144OpenAlexW1561486901MaRDI QIDQ2793990

Yingchun Bo, Jun-Fei Qiao

Publication date: 17 March 2016

Published in: Asian Journal of Control (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1002/asjc.994

zbMATH Keywords

convergencewastewater treatmentadaptive dynamic programmingquadratic performance indexecho state networks

Mathematics Subject Classification ID

Approximation methods and heuristics in mathematical programming (90C59) Nonlinear systems in control theory (93C10) Application models in control theory (93C95) Discrete-time control/observation systems (93C55) Dynamic programming (90C39) Ecology (92D40)

Related Items (4)

Neural optimal tracking control of constrained nonaffine systems with a wastewater treatment application ⋮ Intelligent optimal tracking with asymmetric constraints of a nonlinear wastewater treatment system ⋮ Optimal trajectory tracking control for a class of nonlinear nonaffine systems via generalized N‐step value gradient learning ⋮ Decoupling control for wastewater treatment process based on recurrent fuzzy neural network

Cites Work

• Reservoir computing approaches to recurrent neural network training
• Adaptive consensus protocol for networks of multiple agents with nonlinear dynamics using neural networks
• Adaptive Decentralized NN Control of Nonlinear Interconnected Time-Delay Systems with Input Saturation
• A new adaptive PI for bicarbonate regulation in an anaerobic digestion process
• Continuous Action Generation of Q‐Learning in Multi‐Agent Cooperation
• Learning automata based multi‐agent system algorithms for finding optimal policies in Markov games
• Analysis and Design of Echo State Networks

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