A Simplified Neural Network Solution Through Problem Decomposition: The Case of the Truck Backer-Upper

IEEE Transactions on Neural Networks

Volumn 4, Issue 4, 1993, Pages 718-720

  Jenkins, Robert E ^a   Yuhas, Ben P ^b  

^a JOHNS HOPKINS UNIVERSITY   (United States)

^b TELCORDIA TECHNOLOGIES   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CONTROL EQUIPMENT; CONTROL NONLINEARITIES; LEARNING SYSTEMS; NUMERICAL METHODS; SIMULATION; STATE SPACE METHODS; SYSTEM THEORY; TRUCK TRAILERS; TRUCKS;

CONTROL LAWS; FEED FORWARD NEURAL NETWORK; HARD WIRING; PROBLEM DECOMPOSITION; TRACTOR TRAILER TRUCK; TRUCK BACKER UPPER; TRUCK DYNAMICS;

NEURAL NETWORKS;

EID: 0027634760     PISSN: 10459227     EISSN: 19410093     Source Type: Journal    
DOI: 10.1109/72.238326     Document Type: Article

References (3)

1. D. H. Nguyen and B. Widrow, “Neural networks for self-learning control systems,” IEEE Contr. Syst. Mag., pp. 18–23, 1990.
2. D. E. Rumelhart, J. L. McClelland, and R. J. Williams, “Learning internal representations by error propagation,” in Parallel Distributed Processing in the Microstructure of Cognition: vol. 1, Foundations, D. E. Rumelhart and J. L. McClelland, Eds. Cambridge, MA: MIT Press, 1986.
3. S. G. Kong and B. Kosko, “Adaptive fuzzy systems for backing up a truck-and-trailer,” IEEE Trans. Neural Networks,” vol. 3, pp. 211–223, 1992.