Neural dynamic optimization for control systems-Part III: Applications

IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics

Volumn 31, Issue 4, 2001, Pages 502-513

  Seong, Chang Yun ^a,b   Widrow, Bernard ^a,c  

^a IEEE   (United States)

^b Fineground Networks   (United States)

^c Stanford University   (United States)

Author keywords

Autonomous vehicles; Dynamic programming; Information time shift operator; Learning operator; Neural dynamic optimization; Neural networks; Nonlinear systems; Optimal feedback control; Robots

Indexed keywords

AUTONOMOUS VEHICLES; INFORMATION TIME SHIFT OPERATOR; LEARNING OPERATOR; MULTIPLE INPUT MULTIPLE OUTPUT SYSTEMS; NEURAL DYNAMIC OPTIMIZATION;

COMPUTATIONAL COMPLEXITY; CONTROL SYSTEM SYNTHESIS; DYNAMIC PROGRAMMING; FEEDBACK CONTROL; NONLINEAR CONTROL SYSTEMS; OPTIMAL CONTROL SYSTEMS; ROBOTIC ARMS;

NEURAL NETWORKS;

EID: 0035421174     PISSN: 10834419     EISSN: None     Source Type: Journal    
DOI: 10.1109/3477.938256     Document Type: Article

References (10)

1. Neural dynamic optimization for control systems-Part I: Background
2. Neural dynamic optimization for control systems-Part II: Theory
3. Improving the learning speed of 2-layer neural networks by choosing initial values of the adaptive weights
4. The truck backer-upper: An example of self-learning in neural networks
5. Beyond regression: New tools for prediction and analysis in the behavioral sciences
6. Adaptive inverse control of plants with disturbances