Adaptive control of nonlinear multivariable systems using neural networks

Neural Networks

Volumn 7, Issue 5, 1994, Pages 737-752

  Narendra, Kumpati S ^a   Mukhopadhyay, Snehasis ^a  

^a YALE UNIVERSITY   (United States)

Author keywords

Adaptive control; Decoupling; Dynamic back propagation; Input output representation; Intelligent control; Neural networks; Nonlinear multivariable systems; Relative degree

Indexed keywords

ADAPTIVE CONTROL SYSTEMS; ARTIFICIAL INTELLIGENCE; CONTROL EQUIPMENT; IDENTIFICATION (CONTROL SYSTEMS); LARGE SCALE SYSTEMS; MATHEMATICAL MODELS; MULTIVARIABLE SYSTEMS; PARAMETER ESTIMATION;

DECOUPLING; DYNAMIC BACK PROPAGATION; INPUT OUTPUT REPRESENTATION; INTELLIGENT CONTROL; MULTILAYER NEURAL NETWORKS; NONLINEAR MULTIVARIABLE SYSTEMS; RADIAL BASIS FUNCTION NETWORKS; RELATIVE DEGREE;

NEURAL NETWORKS;

EID: 0028137961     PISSN: 08936080     EISSN: None     Source Type: Journal    
DOI: 10.1016/0893-6080(94)90096-5     Document Type: Article

References (17)

1. Universal approximation bounds for superpositions of a sigmoidal function
2. Approximation by superposition of a sigmoidal function
3. Decoupling in the design and synthesis of multivariable control systems
4. Layered neural networks with Gaussian hidden units as universal approximators
5. Multilayer feedforward networks are universal approximators
6. Universal approximation of an unknown mapping and its derivatives using multilayer feedforward networks
7. Computational schemes and neural network models for formation and control of multi-joint arm trajectory
8. Control of nonlinear dynamical systems using neural networks part II: Observability and identification
9. Control of nonlinear dynamical systems using neural networks part III: Regulation and tracking
10. Control of nonlinear dynamical systems using neural networks: Controllability and stabilization
11. Adaptive control of dynamical systems using neural networks
12. Intelligent control using neural networks
13. Identification and control of dynamical systems using neural networks
14. Gradient methods for the optimization of dynamical systems containing neural networks
15. Beyond regression: New tools for prediction and analysis in the behavioral sciences