Neural network control of unknown systems
AuthorKosmatopoulos, Elias B.
Boussalis, Helen R.
Ioannou, Petros A.
SourceIEEE International Conference on Neural Networks - Conference Proceedings
Proceedings of the 1998 IEEE International Joint Conference on Neural Networks. Part 1 (of 3)
Google Scholar check
MetadataShow full item record
In this paper, we show that for all unknown Multi-Input (MI) nonlinear system that affected by external disturbances, it is possible to construct a semi-global state-feedback stabilizer when the only information about the unknown system is that (A1) the system is robustly stabilizable. (A2) the state dimension of the system is known. (A3) the system vector-fields are at least C1. The proposed stabilizer uses linear-in-the-weights neural networks whose synaptic weights are adaptively adjusted. Robust Control Lyapunov Functions (RCLF) and the switching adaptive derivative feedback control of [14, 15, 16]. Using Lyapunov stability arguments, we show that the closed-loop system is stable and the state vector converges arbitrarily close to zero, provided that the controller's neural networks have sufficiently large number of regressor terms, and that the controller parameters are appropriately chosen. It is worth noticing, that no growth conditions are imposed on the unknown system nonlinearities: also, the proposed approach does not require knowledge of the RCLF of the system. Moreover, although the proposed controller is a discontinuous one, the closed-loop system does not enter in sliding motions. However, the proposed controller might be a very conservative one and may result in very poor transient behavior and/or very large control inputs.
Showing items related by title, author, creator and subject.
Kuipers, M.; Ioannou, Petros A. (2010)Despite the remarkable theoretical accomplishments and successful applications of adaptive control, the field is not sufficiently mature to solve challenging control problems where strict performance and robustness guarantees ...
Robust adaptive attenuation of unknown periodic disturbances in uncertain multi-input multi-output systems Jafari, S.; Ioannou, Petros A. (2016)In high-performance high-accuracy systems, the attenuation of vibrational disturbances is essential. In this paper, we design and analyze a robust output-feedback adaptive control scheme to attenuate noise-corrupted ...
Xu, H.; Mirmirani, M.; Ioannou, Petros A.; Boussalis, Helen R. (2001)A switching adaptive control algorithm based on a sliding mode method is proposed for a class of single-input, single-output nonlinear systems with unknown dynamics. The plant is assumed to be linear-in-the-control input ...