Neural network based iterative learning predictive control design for mechatronic systems with isolated nonlinearity

Journal of Process Control

Volumn 19, Issue 1, 2009, Pages 68-74

  Zhang, Ridong ^a   Xue, Anke ^a   Wang, Jianzhong ^a   Wang, Shuqing ^b   Ren, Zhengyun ^c  

^a HANGZHOU DIANZI UNIVERSITY   (China)

^b STATE KEY LABORATORY OF INDUSTRIAL CONTROL TECHNOLOGY   (China)

^c DONGHUA UNIVERSITY   (China)

Author keywords

Iterative learning; Mechatronic drive systems; Neural network; Predictive control

Indexed keywords

DESIGN; DISTURBANCE REJECTION; FORECASTING; IMAGE CLASSIFICATION; LAWS AND LEGISLATION; LEARNING SYSTEMS; MECHATRONICS; NEURAL NETWORKS; NONLINEAR CONTROL SYSTEMS; NONLINEAR SYSTEMS; PREDICTIVE CONTROL SYSTEMS; RECEPTION QUALITY; UNCERTAIN SYSTEMS;

CONTROL LAWS; CONTROL PERFORMANCES; DRIVE SYSTEMS; FEED FORWARD CONTROLS; ITERATIVE LEARNING; ITERATIVE LEARNINGS; LINEAR PREDICTIVE CONTROLLERS; LINEAR TIMES; LINEARIZED METHODS; LOAD DISTURBANCE REJECTIONS; MECHATRONIC SYSTEMS; NON LINEAR PREDICTIVE CONTROLS; NON LINEARITIES; NONLINEAR OPTIMIZATIONS; NONLINEAR PARTS; OBJECTIVE FUNCTIONS; OPTIMAL CONTROL METHODS; OPTIMAL REGULATORS; OUTPUT ERRORS; PREDICTION METHODS; PREDICTIVE CONTROL; PREDICTIVE CONTROL DESIGNS; REFERENCE INPUTS; STATE SPACE PREDICTIVE CONTROLS; SYSTEM STATE VARIABLES; TRACKING PERFORMANCES; VARIANT SYSTEMS;

CONTROL THEORY;

EID: 57349099450     PISSN: 09591524     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jprocont.2008.01.008     Document Type: Article

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