Adaptive Dynamic Programming with Applications in Optimal Control

History of Adaptive Dynamic Programming.- Part I: Continuous-Time Systems.- Optimal Control of Continuous-Time Affine Nonlinear Systems.- Optimal Control of Nonaffine Continuous-Time Systems.- Robust and Guaranteed Cost Control of Continuous-Time Nonlinear Systems.- Decentralized Stabilization and Control of Nonlinear Interconnected Systems.- Online Synchronous Optimal Learnign Algorithms for Multiplayer Nonzero-Sum Games with Unknown Dynamics.- Part II: Discrete-Time Systems.- Value Iteration Adaptive Dynamic Programming for Discrete-Time Nonlinear Systems.- Finite Approximation Error-Based Value Iteration for Adaptive Dynamic Programming.- Policy Iteration for Optimal Control of Discrete-Time Nonlinear Systems.- Generalized Policy Iteration Adaptive Dynamic Programming for Discrete-Time Nonlinear Systems.- Error-Bound Analysis of Adaptive Dynamic Programming Algorithms for Solving Undiscounted Optimal Control Problems.- Part III: Applications.- Adaptive Dynamic Programming for Renewable Energy Scheduling and Battery Management in Smart Homes.- Adaptive Dynamic Programming for Optimal Tracking Control of a Coal Gasification Process.- Data-Driven Neuro-Optimal Temperature Control of Water-Gas Shift Reaction.

Derong Liu received the Ph.D. degree in electrical engineering from the University of Notre Dame, Indiana, USA, in 1994. Dr. Liu was a Staff Fellow with General Motors Research and Development Center, from 1993 to 1995. He was an Assistant Professor with the Department of Electrical and Computer Engineering, Stevens Institute of Technology, from 1995 to 1999. He joined the University of Illinois at Chicago in 1999, and became a Full Professor of Electrical and Computer Engineering and of Computer Science in 2006. He was selected for the "100 Talents Program" by the Chinese Academy of Sciences in 2008. He has published 16 books. Dr. Liu was the Editor-in-Chief of the IEEE Transactions on Neural Networks and Learning Systems, from 2010 to 2015. Currently, he is an elected AdCom member of the IEEE Computational Intelligence Society, he is the Editor-in-Chief of Artificial Intelligence Review, and he serves as the Vice President of Asia-Pacific Neural Network Society. He was the General Chair of 2014 IEEE World Congress on Computational Intelligence and was the General Chair of 2016 World Congress on Intelligent Control and Automation. He received the Faculty Early Career Development Award from the National Science Foundation in 1999, the University Scholar Award from University of Illinois from 2006 to 2009, the Overseas Outstanding Young Scholar Award from the National Natural Science Foundation of China in 2008, and the Outstanding Achievement Award from Asia Pacific Neural Network Assembly in 2014. He is a Fellow of the IEEE and a Fellow of the International Neural Network Society.  

Qinglai Weie="font-family: 'Courier New';"> received the Ph.D. degree in control theory and control engineering, from the Northeastern University, Shenyang, China, in 2009. From 2009 to 2011, he was a postdoctoral fellow with The State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of