Frontiers Of Intelligent Control And Information Processing

The current research and development in intelligent control and information processing have been driven increasingly by advancements made from fields outside the traditional control areas, into new frontiers of intelligent control and information processing so as to deal with ever more complex systems with ever growing size of data and complexity. As researches in intelligent control and information processing are taking on ever more complex problems, the control system as a nuclear to coordinate the activity within a system increasingly need to be equipped with the capability to analyze, and reason so as to make decision. This requires the support of cognitive components, and communication protocol to synchronize events within the system to operate in unison. In this review volume, we invited several well-known experts and active researchers from adaptive/approximate dynamic programming, reinforcement learning, machine learning, neural optimal control, networked systems, and cyber-physical systems, online concept drift detection, pattern recognition, to contribute their most recent achievements into the development of intelligent control systems, to share with the readers, how these inclusions helps to enhance the cognitive capability of future control systems in handling complex problems. This review volume encapsulates the state-of-art pioneering works in the development of intelligent control systems. Proposition and evocations of each solution is backed up with evidences from applications, could be used as references for the consideration of decision support and communication components required for today intelligent control systems.Contents: Dynamic Graphical Games: Online Adaptive Learning Solutions Using Approximate Dynamic Programming (Mohammed I Abouheaf & Frank L Lewis) Reinforcement-Learning-Based Online Learning Control for Discrete-Time Unknown Nonaffine Nonlinear Systems (Xiong Yang, Derong Liu, Qinglai Wei & Ding Wang) Experimental Studies on Data-Driven Heuristic Dynamic Programming for POMDP (Zhen Ni, Haibo He & Xiangnan Zhong) Online Reinforcement Learning for Continuous-State Systems (Yuanheng Zhu & Dongbin Zhao) Adaptive Iterative Learning Control of Robot Manipulators in the Presence of Environmental Constraints (Xiongxiong He, Zhenhua Qin & Xianqing Wu) Neural Network Control of Nonlinear Discrete-Time Systems in Affine Form in the Presence of Communication Network (Hao Xu, Avimanyu Sahoo & Sarangapani Jagannathan) Nonlinear and Robust Model Predictive Control of Systems with Unmodeled Dynamics Based on Supervised Learning and Neurodynamic Optimization (Zheng Yan & Jun Wang) Packet-Based Communication and Control Co-Design for Networked Control Systems (Yun-Bo Zhao & Guo-Ping liu) Review of Some Approximate Privacy Measures of Multi-Agent Communication Protocols (Bhaskar DasGupta & Venkatakumar Srinivasan) Encoding-Decoding Machines for Online Concept-Drift Detection on Datastreams (Cesare Alippi, Giacomo Boracchi, Li Bu & Dongbin Zhao) Recognizing sEMG Patterns for Interacting with Prosthetic Manipulation (Zhaojie Ju, Gaoxiang Ouyang, Marzena Wilamowska-Korsak & Honghai Liu) Energy Demand Management Through Uncertain Data Forecasting: A Hybrid Approach (Marco Severini, Stefano Squartini & Francesco Piazza) Many-Objective Evolutionary Algorithms and Hybrid Performance Metrics (Zhenan He & Gary G Yen) Synchronization Control of Memristive Chaotic Circuits and Their Applications in Image Encryptions (Shiping Wen & Zhigang Zeng) Graph Embedded Total Margin Twin Support Vector Machine and Its Applications (Xiaobo Chen & Jian Yang) Regularized Covariance Matrix Estimation Based on MDL Principle (Xiuling Zhou, Ping Guo & C L Philip Chen) An Evolution of Evolutionary Algorithms with Big Data (Weian Guo, Lei Wang & Qidi Wu) Readership: Researchers in development of intelligent control systems with big data, as well as postgraduate students in adaptive control systems. Key Features: A review volume that...