Robust approximation-free prescribed performance control for nonlinear systems and its application

ABSTRACT

This paper presents a robust prescribed performance control approach and its application to nonlinear tail-controlled missile systems with unknown dynamics and uncertainties. The idea of prescribed performance function (PPF) is incorporated into the control design, such that both the steady-state and transient control performance can be strictly guaranteed. Unlike conventional PPF-based control methods, we further tailor a recently proposed systematic control design procedure (i.e. approximation-free control) using the transformed tracking error dynamics, which provides a proportional-like control action. Hence, the function approximators (e.g. neural networks, fuzzy systems) that are widely used to address the unknown nonlinearities in the nonlinear control designs are not needed. The proposed control design leads to a robust yet simplified function approximation-free control for nonlinear systems. The closed-loop system stability and the control error convergence are all rigorously proved. Finally, comparative simulations are conducted based on nonlinear missile systems to validate the improved response and the robustness of the proposed control method.

KEYWORDS:

• Nonlinear systems
• prescribed performance control
• robust control
• missile systems

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work was supported by the Natural Science Foundation of China (NSFC) [grant number 11176012], [grant number 61573174].

Notes on contributors

Ruisheng Sun

Ruisheng Sun was born in 1978. He received his PhD degree in navigation, guidance and control from Nanjing University of Science and Technology (NJUST), China, in 2010. He is an associate professor at NJUST. His research interests include nonlinear adaptive control and guidance, adaptive observer design, multidiscipline optimisation.

Jing Na

Jing Na received his BS and PhD degrees from the School of Automation, Beijing Institute of Technology, Beijing, China, in 2004 and 2010, respectively. He was a visiting student with the Universitat Politècnica de Catalunya, Spain, in 2008, a research collaborator with the University of Bristol, U.K., from 2008 to 2009. He was a post-doctoral fellow with the Cryogenic System Section, ITER Organization, Cadarache, France, from 2011 to 2012 and a Marie Curie fellow hosted in the University of Bristol from 2015 to 2016. He has been with the Faculty of Mechanical and Electrical Engineering, Kunming University of Science and Technology, China, since 2010, where he has been promoted as a Professor in 2013. His current research interests include adaptive control, parameter estimation, nonlinear control and applications.

Bin Zhu

Bin Zhu was born in 1991. He received his BEng degree in system engineering from Nanjing University of Science and Technology (NJUST), China, in 2013. He is currently working toward to his PhD degree at NJUST. His research interests include flight dynamics modelling, robust adaptive control.