Global Neural Dynamic Surface Tracking Control of Strict-Feedback Systems With Application to Hypersonic Flight Vehicle

• Published in: IEEE transaction on neural networks and learning systems Vol. 26; no. 10; pp. 2563 - 2575
• Main Authors: Xu, Bin, Yang, Chenguang, Pan, Yongping
• Format: Journal Article
• Language: English
• Published: United States IEEE 01.10.2015; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Aerodynamics; Approximation methods; Artificial neural networks; Computer simulation; Control systems; Controllers; Dynamic surface control; Dynamic tests; Dynamical systems; Dynamics; Feedback; global stability; Humans; Hypersonic flight; hypersonic flight vehicle; indirect and direct neural control; Mathematical analysis; Models, Neurological; Neural Networks (Computer); Neurons - physiology; Nonlinear Dynamics; smooth switching; Stability analysis; Stochastic Processes; strict-feedback system; Support Vector Machine; Switches; Vehicle dynamics; global stability; Dynamic surface control; smooth switching; indirect and direct neural control; strict-feedback system; hypersonic flight vehicle
• ISSN: 2162-237X; 2162-2388
• DOI: 10.1109/TNNLS.2015.2456972

This paper studies both indirect and direct global neural control of strict-feedback systems in the presence of unknown dynamics, using the dynamic surface control (DSC) technique in a novel manner. A new switching mechanism is designed to combine an adaptive neural controller in the neural approximation domain, together with the robust controller that pulls the transient states back into the neural approximation domain from the outside. In comparison with the conventional control techniques, which could only achieve semiglobally uniformly ultimately bounded stability, the proposed control scheme guarantees all the signals in the closed-loop system are globally uniformly ultimately bounded, such that the conventional constraints on initial conditions of the neural control system can be relaxed. The simulation studies of hypersonic flight vehicle (HFV) are performed to demonstrate the effectiveness of the proposed global neural DSC design.