Feedback control of minimum‐time optimal control problems using neural networks

Optimal Control Applications and Methods

Volumn 14, Issue 1, 1993, Pages 1-16

  Goh, C J ^a   Edwards, N J ^a   Zomaya, A Y ^a  

^a UNIVERSITY OF WESTERN AUSTRALIA   (Australia)

Author keywords

Minimum time; Neural networks; Optimal feedback control; Robot manipulator

Indexed keywords

INDUSTRIAL ROBOTS; NEURAL NETWORKS; NONLINEAR CONTROL SYSTEMS;

OPTIMAL FEEDBACK CONTROL; ROBOT MANIPULATOR; ROBOT TRAJECTORY CONTROL;

OPTIMAL CONTROL SYSTEMS;

EID: 0027277832     PISSN: 01432087     EISSN: 10991514     Source Type: Journal    
DOI: 10.1002/oca.4660140102     Document Type: Article

References (35)

1. The dynamic performance of robot manipulator under different operating conditions
2. The near minimum‐time control of open‐loop kinematic chains
3. Time optimal control of robotic manipulators along specified path
4. A concept for manipulator trajectory planning
5. Selection of near minimum time geometric paths for robotic manipulators
6. A dynamic programming approach to trajectory planning of robotic manipulators
7. Time‐optimal motions of robots in assembly tasks
8. Time optimal trajectories for robot manipulators
9. Neural networks in robotics: a survey
10. A linear programming regulator applied to hydroelectric reservoir level control
11. Heuristically enhanced feedback control of constrained discrete‐time linear systems
12. Identification and control of dynamical systems using neural networks
13. On the approximate realization of continuous mapping by neural networks
14. Multilayer feedforward networks are universal approximators
15. Networks for approximation and learning
16. Backpropagation fails to separate where perceptrons succeed
17. Effective parallel learning algorithms for neural networks
18. Parallel recursive prediction error algorithm for training layered neural networks
19. MISER: A FORTRAN program for solving optimal control problems
20. MISER3: solving optimal control problems: an update
21. Control parametrization: a unified approach to optimal control problems with general constraint
22. Skeletonization: a technique for trimming the fat from a network via relevance assessment
23. A simple procedure for pruning back‐propagation trained neutral networks
24. A neural model for category learning
25. Dynamic connections in neural networks
26. Neural networks for routing communication traffic
27. Sensitivity of feedforward neural networks to weight errors
28. Fast robot kinematic modelling via transputer networks