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Adaptive neural network decentralized backstepping output-feedback control for nonlinear large-scale systems with
Shao Cheng Tong1, Yong Ming Li, Hua-Guang Zhang
1Department of Mathematics, Liaoning University of Technology, Jinzhou, China. jztsc@sohu.com
IEEE Transactions on Neural Networks
|June 7, 2011
Summary
This study presents two adaptive neural network (NN) control methods for complex nonlinear systems with unknown states and time delays. These novel approaches ensure system stability and accurate state estimation for improved performance.
Area of Science:
- Control Systems Engineering
- Artificial Intelligence
- Nonlinear Dynamics
Background:
- Large-scale nonlinear systems often suffer from immeasurable states and unknown time delays, complicating control design.
- Traditional control methods struggle with the inherent uncertainties and complexity of these systems.
- Neural networks (NNs) offer a powerful tool for approximating unknown nonlinear functions.
Purpose of the Study:
- To develop adaptive neural network (NN) decentralized output feedback control strategies for uncertain nonlinear large-scale systems.
- To address challenges posed by immeasurable states and unknown time delays.
- To mitigate the 'explosion of complexity' issue in adaptive control design.
Main Methods:
- Designed an NN state observer to estimate immeasurable states using NNs for function approximation.
- Combined adaptive backstepping with decentralized control principles for output feedback control.
- Integrated dynamic surface control (DSC) to simplify the adaptive NN decentralized control scheme, reducing computational complexity.
Main Results:
- Proved that both proposed control approaches ensure semi-globally uniformly ultimately bounded states for the closed-loop system.
- Demonstrated convergence of observer errors and tracking errors to a small neighborhood of the origin.
- Simulation results validated the effectiveness of the developed adaptive NN decentralized output feedback control strategies.
Conclusions:
- The proposed adaptive NN decentralized output feedback control methods effectively manage uncertain nonlinear large-scale systems.
- The integration of DSC provides a simplified yet robust control solution.
- These approaches guarantee system stability and accurate state estimation in the presence of significant system uncertainties.
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