Sliding Mode Learning Control and its Applications Manh Tuan Do Submitted in total fulfilment of the requirements of the degree of Doctor of Philosophy Faculty of Science, Engineering and Technology Swinburne University of Technology Melbourne, Australia 2014 Abstract ith the rapid advancement of control technologies, there have been various Wintelligent control schemes established for complex systems with or without uncertain dynamics. Given a certain control problem, desirable qualities such as simplicity, applicability, adaptability, and robustness are the touchstones of control design so as to ensure excellent control performance against system parameter variations and unpredicted external disturbances. Amongst many robust control techniques, Sliding Mode Control (SMC) has been increasingly receiving a great deal of attention in both theoretical and applied disciplines owing to its distinguishing features such as insensitivity to bounded matched uncertainties, order reduction of sliding motion equations, decoupling design procedure, and zero-error convergence of the closed-loop system, just to name a few. Nevertheless, the shortcomings inherent in conventional SMC approaches are yet to be fully addressed. For one, the chattering phenomenon has not been uprooted without compromising on the zero-error convergence. More importantly, from the control design perspective, there are certain constraints in the design of SMC, such as prior information about the bounds of uncertainties is often required, this in turn has greatly restrained the applications of SMC in many practical circumstances. Therefore, how to make the best use of SMC in order to develop a simple but effective SMC technique has remained a big challenge for both researchers and engineers in the areas of control engineering and the related technologies. To tackle these issues, this thesis is concerned with the sliding mode based learning control technique and its applications. The sliding mode learning control (SMLC) developed in this research enjoys several overwhelming superiorities over its conventional counterparts: (i) since the learning algorithm is adopted, the knowledge of the uncertainty is no longer a prerequisite for controller design and thus (ii) the control input is completely chattering-free, and (iii) the SMLC scheme poses a strong robustness with respect to unmodelled dynamics. It is seen that the proposed SMLC not only inherits all the appealing characteristics of SMC, but also helps curb the drawbacks that befall conventional SMC approaches. Therefore, it is for this reason that the iii proposed SMLC will potentially play an essential role in years to come, in terms of relaxing many constrains associated with the bounds of uncertain dynamics in conventional SMC schemes. In this thesis, novel SMLC schemes will be developed for a wide range of uncertain dynamic systems. In particular, the concept of the most recently introduced SMLC technique associated with the so-called Lipschitz-like condition is extensively studied. First of all, the SMLC scheme is well examined with mathematical proofs and then developed for a class of uncertain dynamic systems in a continuous-time domain. Some concluding remarks are highlighted to boost the significant advantages of the proposed SMLC scheme over existing control ones. Numerical results are presented to verify the SMLC algorithm. Next, the SMLC technique is applied to address the stabilization of nonminimum phase nonlinear systems and congestion control of communication networks. Following this development, the SMLC scheme is further tested and successfully deployed to control steer-by-wire systems of modern vehicles. The experimental results have confirmed the excellent performance of the proposed SMLC. Finally, the framework is further developed for a class of uncertain dynamic systems in a discrete- time domain followed by the application of congestion control in connection-oriented communication networks. iv Declaration This is to certify that this thesis: contains no material which has been accepted for the award to me towards any other degree or diploma, except where due reference is made in the text of the examinable outcome; to the best of my knowledge, contains no material previously published or written by another person except where due reference is made in the text of the examinable outcome; and where the work is based on joint research and publications, discloses the relative contributions of the respective authors. ________________________ Manh Tuan Do, 2014 v Preface This thesis is based on the research work conducted over the course of the past four years in the Faculty of Science, Engineering and Technology, Swinburne University of Technology, under the supervision of Prof. Zhihong Man, Prof. Cishen Zhang, and Dr. Jiong Jin. As a result, a number of journal papers and international conference papers have been published or submitted for publication. The following summarizes the author’s publications and contributions pertaining to the relevance of each particular chapter of this thesis, and the complete list of the author’s publications can be found at the end of the thesis. The work in Chapter 3 on the proposed SMLC scheme, the backbone of the SMLC concept developed in this thesis, presents the fundamental and conceptual theory of the proposed SMLC and the significance of the approach, as well as the so-called Lipschitz- like condition newly initiated by Man et al. [84]. The research outcome in Chapter 4 on Robust Stabilization of Nonminimum Phase Systems Using Sliding Mode Learning Controller has led to a journal paper submitted to IEEE Transactions on Cybernetics and a conference paper presented at ICIEA 2013 (Do et al. [154]). The work in Chapter 5 on Sliding Mode Learning Based Congestion Control for DiffServ Networks has resulted in a journal paper submitted to IEEE Transactions on Control of Network Systems. The result of Chapter 6 on Robust Sliding Mode Based Learning Control for Steer- by-Wire Systems in Modern Vehicles has outputted a journal paper published in IEEE Transactions on Vehicular Technology (Do et al. [87]). The work about Robust Sliding Mode Learning Control for Uncertain Discrete- Time MIMO Systems in Chapter 7 has yielded a journal paper published in IET Control Theory and Applications (Do et al. [88]) and a conference paper presented at ICARV 2012 (Do et al. [107]). vii Lastly, the research result of Chapter 8 on Discrete-Time Sliding Mode Learning Based Congestion Control for Connection-Oriented Communication Networks has led to a journal paper submitted to IEEE Transactions on Communications Letters. viii Acknowledgement First and foremost, I would like to thank my supervisory team Prof. Zhihong Man, Prof. Cishen Zhang, and Dr. Jiong Jin for their invaluable guidance and constant support throughout the past four years. They have made tremendous effort to offer me both academic and social advice to make my PhD life a noteworthy and rewarding one. Especially, I would like to express my deepest gratitude to Prof. Zhihong Man for his endless supervision of my doctoral research advancement, for giving me all the opportunities and motivation to pursue my PhD degree at Swinburne University of Technology, and for spurring me to endeavour for the best and to be a goal-oriented individual. I could not have asked for a more supportive and caring mentor who is always accessible and passionate in patiently coaching me about the much desired knowledge and skills that are indispensable for the accomplishment of this thesis. I am grateful to Swinburne University of Technology for awarding me the SUPRA scholarship and catering me with a conducive and favourable working environment. Many thanks go to Melissa, Sophia and Adrianna from the research administration and finance group for promptly looking after any inquiries or concerns I had with a very warm welcome. I would also like to thank the senior technical staff, Walter and Krys, as well as the ITS members for their continual support in swiftly resolving many technical issues and providing resources and assistance whenever needed. Every little thing you did made my everyday life as a PhD candidate a whole lot easier. To Jinchuan, Hai, Feisiang, and Kevin, I am very thankful to have you all as friends and research fellows. It has been my honour to have shared my research experience with all of you in some technical sessions, seminars, conferences, and even through our day- to-day discussions and chats. Thank you very much for your friendship and collaboration. You have made my PhD life in Melbourne much more vibrant and enjoyable. Last but not least, I am truly indebted to my beloved family members who unrelentingly believed in me and encouraged me to follow my dreams. I cannot thank them enough for their endless love, care, and sacrifices. Without their support, neither my life nor my work would bring fulfilment. ix To my wife Mai Tuyet Phung, my daughter Isabella Do, my mother Thin Thi Pham, and in memory of my father Cu Hong Do. x Contents 1 Introduction 1 1.1 Preliminaries .................................................................................................. 1 1.1.1 Variable Structure Systems ................................................................ 2 1.1.2 Sliding Mode Control ........................................................................ 3 1.2 Motivation ..................................................................................................... 6 1.3 Objectives and Major Contributions