An ILC-based adaptive control for general stochastic systems with strictly decreasing entropy

IEEE Transactions on Neural Networks

Volumn 20, Issue 3, 2009, Pages 471-482

  Afshar, Puya ^a   Wang, Hong ^a   Chai, Tianyou ^b  

^a UNIVERSITY OF MANCHESTER   (United Kingdom)

^b NORTHEASTERN UNIVERSITY   (China)

Author keywords

Adaptive controller; Entropy; Iterative learning control (ILC); Neural networks; Stochastic systems and optimization

Indexed keywords

CONTROLLERS; CONVERGENCE OF NUMERICAL METHODS; ENTROPY; LEARNING ALGORITHMS; LEARNING SYSTEMS; NEURAL NETWORKS; RANDOM PROCESSES; STOCHASTIC CONTROL SYSTEMS; STOCHASTIC SYSTEMS; TWO TERM CONTROL SYSTEMS;

ADAPTIVE CONTROLLER; ADAPTIVE CONTROLS; CLOSED LOOPS; CLOSED-LOOP TRACKING; CONTROL ALGORITHMS; CONTROL HORIZONS; CONTROLLER PARAMETERS; DYNAMIC NEURAL NETWORKS; GENERAL STOCHASTIC SYSTEMS; ITERATIVE LEARNING CONTROL (ILC); MINIMUM ENTROPY CONTROLS; MODELING AND CONTROLS; NONLINEAR AND NON-GAUSSIAN; PLANT MODELS; SUBINTERVALS; TIME DOMAINS; TIME HORIZONS;

ADAPTIVE CONTROL SYSTEMS;

EID: 63049091678     PISSN: 10459227     EISSN: None     Source Type: Journal    
DOI: 10.1109/TNN.2008.2010351     Document Type: Article

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