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Nonlinear Modeling and Control of Driving Interfaces and Continuum Robots for System Performance Gains

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Nonlinear Modeling and Control of Driving Interfaces and Continuum Robots for System Performance Gains Clemson University TigerPrints All Dissertations Dissertations December 2020 Nonlinear Modeling and Control of Driving Interfaces and Continuum Robots for System Performance Gains Chengshi Wang Clemson University, [email protected] Follow this and additional works at: https://tigerprints.clemson.edu/all_dissertations Recommended Citation Wang, Chengshi, "Nonlinear Modeling and Control of Driving Interfaces and Continuum Robots for System Performance Gains" (2020). All Dissertations. 2720. https://tigerprints.clemson.edu/all_dissertations/2720 This Dissertation is brought to you for free and open access by the Dissertations at TigerPrints. It has been accepted for inclusion in All Dissertations by an authorized administrator of TigerPrints. For more information, please contact [email protected]. NONLINEAR MODELING AND CONTROL OF DRIVING INTERFACES AND CONTINUUM ROBOTS FOR SYSTEM PERFORMANCE GAINS A Dissertation Presented to the Graduate School of Clemson University In Partial Fulfillment of the Requirements for the Degree Doctor of Philosophy Mechanical Engineering by Chengshi Wang December 2020 Accepted by: Dr. John R. Wagner, Committee Chair Dr. Yue Wang Dr. Ian D. Walker Dr. Todd Schweisinger i ABSTRACT With the rise of (semi)autonomous vehicles and continuum robotics technology and applications, there has been an increasing interest in controller and haptic interface designs. The presence of nonlinearities in the vehicle dynamics is the main challenge in the selection of control algorithms for real-time regulation and tracking of (semi)autonomous vehicles. Moreover, control of continuum structures with infinite dimensions proves to be difficult due to their complex dynamics plus the soft and flexible nature of the manipulator body. The trajectory tracking and control of automobile and robotic systems requires control algorithms that can effectively deal with the nonlinearities of the system without the need for approximation, modeling uncertainties, and input disturbances. Control strategies based on a linearized model are often inadequate in meeting precise performance requirements. To cope with these challenges, one must consider nonlinear techniques. Nonlinear control systems provide tools and methodologies for enabling the design and realization of (semi)autonomous vehicle and continuum robots with extended specifications based on the operational mission profiles. This dissertation provides an insight into various nonlinear controllers developed for (semi)autonomous vehicles and continuum robots as a guideline for future applications in the automobile and soft robotics field. A comprehensive assessment of the approaches and control strategies, as well as insight into the future areas of research in this field, are presented. First, two vehicle haptic interfaces, including a robotic grip and a joystick, both of which are accompanied by nonlinear sliding mode control, have been developed and studied on a steer-by-wire platform integrated with a virtual reality driving environment. ii An operator-in-the-loop evaluation that included 30 human test subjects was used to investigate these haptic steering interfaces over a prescribed series of driving maneuvers through real time data logging and post-test questionnaires. A conventional steering wheel with a robust sliding mode controller was used for all the driving events for comparison. Test subjects operated these interfaces for a given track comprised of a double lane-change maneuver and a country road driving event. Subjective and objective results demonstrate that the driver’s experience can be enhanced up to 75.3% with a robotic steering input when compared to the traditional steering wheel during extreme maneuvers such as high-speed driving and sharp turn (e.g., hairpin turn) passing. Second, a cellphone-inspired portable human-machine-interface (HMI) that incorporated the directional control of the vehicle as well as the brake and throttle functionality into a single holistic device will be presented. A nonlinear adaptive control technique and an optimal control approach based on driver intent were also proposed to accompany the mechatronic system for combined longitudinal and lateral vehicle guidance. Assisting the disabled drivers by excluding extensive arm and leg movements ergonomically, the device has been tested in a driving simulator platform. Human test subjects evaluated the mechatronic system with various control configurations through obstacle avoidance and city road driving test, and a conventional set of steering wheel and pedals were also utilized for comparison. Subjective and objective results from the tests demonstrate that the mobile driving interface with the proposed control scheme can enhance the driver’s performance by up to 55.8% when compared to the traditional driving system during aggressive maneuvers. The system’s superior performance during certain iii vehicle maneuvers and approval received from the participants demonstrated its potential as an alternative driving adaptation for disabled drivers. Third, a novel strategy is designed for trajectory control of a multi-section continuum robot in three-dimensional space to achieve accurate orientation, curvature, and section length tracking. The formulation connects the continuum manipulator dynamic behavior to a virtual discrete-jointed robot whose degrees of freedom are directly mapped to those of a continuum robot section under the hypothesis of constant curvature. Based on this connection, a computed torque control architecture is developed for the virtual robot, for which inverse kinematics and dynamic equations are constructed and exploited, with appropriate transformations developed for implementation on the continuum robot. The control algorithm is validated in a realistic simulation and implemented on a six degree-of- freedom two-section OctArm continuum manipulator. Both simulation and experimental results show that the proposed method could manage simultaneous extension/contraction, bending, and torsion actions on multi-section continuum robots with decent tracking performance (e.g. steady state arc length and curvature tracking error of 3.3mm and 130mm-1, respectively). Last, semi-autonomous vehicles equipped with assistive control systems may experience degraded lateral behaviors when aggressive driver steering commands compete with high levels of autonomy. This challenge can be mitigated with effective operator intent recognition, which can configure automated systems in context-specific situations where the driver intends to perform a steering maneuver. In this article, an ensemble learning-based driver intent recognition strategy has been developed. A nonlinear model iv predictive control algorithm has been designed and implemented to generate haptic feedback for lateral vehicle guidance, assisting the drivers in accomplishing their intended action. To validate the framework, operator-in-the-loop testing with 30 human subjects was conducted on a steer-by-wire platform with a virtual reality driving environment. The roadway scenarios included lane change, obstacle avoidance, intersection turns, and highway exit. The automated system with learning-based driver intent recognition was compared to both the automated system with a finite state machine-based driver intent estimator and the automated system without any driver intent prediction for all driving events. Test results demonstrate that semi-autonomous vehicle performance can be enhanced by up to 74.1% with a learning-based intent predictor. The proposed holistic framework that integrates human intelligence, machine learning algorithms, and vehicle control can help solve the driver-system conflict problem leading to safer vehicle operations. v DEDICATION I dedicate this dissertation to my parents, and my sister, who supported me to pursue my doctoral degree and inspired me to be good. This dissertation is also dedicated to my niece Isla, who is the most beautiful baby girl in the world. vi ACKNOWLEDGMENTS I would like to express the deepest appreciation to my committee chair Dr. John Wagner, who has the attitude and the substance of a genius: he continually and convincingly conveyed a spirit of adventure in regard to research and scholarship. Dr. Wagner’s expertise was invaluable in the formulating of the research topic and methodology in particular. Without his guidance and persistent help this dissertation would not have been possible. Besides my advisor, I would like to thank the rest of my dissertation committee members (Dr. Todd Schweisinger, Dr. Ian D. Walker, and Dr. Yue Wang) for their great support and invaluable advice. I would like to thank my committee member, Dr. Yue Wang an expert in human robot interaction (HRI) system, for her crucial remarks that shaped my final dissertation. In addition, a thank you to Dr. Todd Schweisinger, for providing me with opportunities to teach undergraduate courses, an experience which truly shaped me as a scholar and prepared me for future academic endeavors. I would particularly like to single out my committee member Dr. Ian D. Walker, who introduced me to the robotics. I want to thank you for your guidance and for all the opportunities I was given to conduct research on the control of continuum robots and further my dissertation. Last but not least, I would like to express my deepest gratitude to my family and friends. This dissertation would not have been possible without their warm love, continued patience, and endless support. vii TABLE OF CONTENTS Page TITLE PAGE
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