Adaptive critic designs: A case study for neurocontrol

Neural Networks

Volumn 8, Issue 9, 1995, Pages 1367-1372

  Prokhorov, Danil V ^a   Santiago, Roberto A ^b   Wunsch II, Donald C ^a  

^a TEXAS TECH UNIVERSITY   (United States)

^b BehavHeuristics Inc ^*  (United States)

Author keywords

Adaptive critic; Aircraft autolanding; Heuristic dynamic programming; Neural networks for control and optimization; Neurocontrol

Indexed keywords

ADAPTIVE CONTROL SYSTEMS; AIRCRAFT LANDING; ALGORITHMS; APPROXIMATION THEORY; AUTOMATION; COMPUTATIONAL COMPLEXITY; DYNAMIC PROGRAMMING; HEURISTIC PROGRAMMING; PROBLEM SOLVING; THREE TERM CONTROL SYSTEMS;

ADAPTIVE CRITIC DESIGN; AIRCRAFT AUTOLANDING; HEURISTIC DYNAMIC PROGRAMMING; NEUROCONTROL;

NEURAL NETWORKS;

ARTICLE; ARTIFICIAL NEURAL NETWORK; PRIORITY JOURNAL;

EID: 0029592634     PISSN: 08936080     EISSN: None     Source Type: Journal    
DOI: 10.1016/0893-6080(95)00042-9     Document Type: Article

References (10)

1. Challenging control problems
2. Neuronlike elements that can solve difficult learning control problems
3. Artificial neural networks in manufacturing and process control
4. A neural network baseline problem for control of aircraft flare and touchdown
5. Neural networks for self-learning control systems
6. An aircraft autolander based on backpropagated adaptive critic
7. A new progress towards truly brain-like control
8. A menu of designs for reinforcement learning over time
9. Approximate dynamic programming for real-time control and neural modeling
10. Neurocontrol and supervised learning: an overview and valuation