3,190 research outputs found

    Comparison of different repetitive control architectures: synthesis and comparison. Application to VSI Converters

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    Repetitive control is one of the most used control approaches to deal with periodic references/disturbances. It owes its properties to the inclusion of an internal model in the controller that corresponds to a periodic signal generator. However, there exist many different ways to include this internal model. This work presents a description of the different schemes by means of which repetitive control can be implemented. A complete analytic analysis and comparison is performed together with controller synthesis guidance. The voltage source inverter controller experimental results are included to illustrative conceptual developmentsPeer ReviewedPostprint (published version

    Impedance control of redundant manipulators for safe human-robot collaboration

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    In this paper, the impedance control paradigm is used to design control algorithms for safe human-robot collaboration. In particular, the problem of controlling a redundant robot manipulator in task space, while guaranteeing a compliant behavior for the redundant degrees of freedom, is considered first. The proposed approach allows safe and dependable reaction of the robot during deliberate or accidental physical interaction with a human or the environment, thanks to null-space impedance control. Moreover, the case of control for co-manipulation is considered. In particular, the role of the kinematic redundancy and that of the impedance parameters modulation are investigated. The algorithms are verified through experiments on a 7R KUKA lightweight robot arm

    Robust Whole-Body Motion Control of Legged Robots

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    We introduce a robust control architecture for the whole-body motion control of torque controlled robots with arms and legs. The method is based on the robust control of contact forces in order to track a planned Center of Mass trajectory. Its appeal lies in the ability to guarantee robust stability and performance despite rigid body model mismatch, actuator dynamics, delays, contact surface stiffness, and unobserved ground profiles. Furthermore, we introduce a task space decomposition approach which removes the coupling effects between contact force controller and the other non-contact controllers. Finally, we verify our control performance on a quadruped robot and compare its performance to a standard inverse dynamics approach on hardware.Comment: 8 Page

    Sliding modes in constrained systems control

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    Abstractโ€”In this paper, a sliding-mode-based design framework for fully actuated mechanical multibody system is discussed. The framework is based on the possibility to represent complex motion as a collection of tasks and to find effective mapping of the system coordinates that allows decoupling task and constraint control so one is able to enforce concurrently, or in certain time succession, the task and the constraints. The approach seems naturally encompassing the control of motion systems in interaction, and it allows application to bilateral control, multilateral control, etc. Such an approach leads to a more natural interpretation of the system tasks, simpler controller design, and easier establishment of the systems hierarchy. It allows a unified mathematical treatment of task control in the presence of constraints required to be satisfied by the system coordinates. In order to show the applicability of the proposed techniques, simulation and experimental results for high-precision systems in microsystem assembly tasks and bilateral control systems are presented

    Collision Detection and Reaction: A Contribution to Safe Physical Human-Robot Interaction

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    In the framework of physical Human-Robot Interaction (pHRI), methodologies and experimental tests are presented for the problem of detecting and reacting to collisions between a robot manipulator and a human being. Using a lightweight robot that was especially designed for interactive and cooperative tasks, we show how reactive control strategies can significantly contribute to ensuring safety to the human during physical interaction. Several collision tests were carried out, illustrating the feasibility and effectiveness of the proposed approach. While a subjective โ€œsafetyโ€ feeling is experienced by users when being able to naturally stop the robot in autonomous motion, a quantitative analysis of different reaction strategies was lacking. In order to compare these strategies on an objective basis, a mechanical verification platform has been built. The proposed collision detection and reactions methods prove to work very reliably and are effective in reducing contact forces far below any level which is dangerous to humans. Evaluations of impacts between robot and human arm or chest up to a maximum robot velocity of 2.7 m/s are presented

    ์™ธ๋ž€ ๋ฐ ํ† ํฌ ๋Œ€์—ญํญ ์ œํ•œ์„ ๊ณ ๋ คํ•œ ํ† ํฌ ๊ธฐ๋ฐ˜์˜ ์ž‘์—… ๊ณต๊ฐ„ ์ œ์–ด

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    ํ•™์œ„๋…ผ๋ฌธ(๋ฐ•์‚ฌ) -- ์„œ์šธ๋Œ€ํ•™๊ต๋Œ€ํ•™์› : ์œตํ•ฉ๊ณผํ•™๊ธฐ์ˆ ๋Œ€ํ•™์› ์œตํ•ฉ๊ณผํ•™๋ถ€(์ง€๋Šฅํ˜•์œตํ•ฉ์‹œ์Šคํ…œ์ „๊ณต), 2021.8. ๋ฐ•์žฌํฅ.The thesis aims to improve the control performance of the torque-based operational space controller under disturbance and torque bandwidth limitation. Torque-based robot controllers command the desired torque as an input signal to the actuator. Since the torque is at force-level, the torque-controlled robot is more compliant to external forces from the environment or people than the position-controlled robot. Therefore, it can be used effectively for the tasks involving contact such as legged locomotion or human-robot interaction. Operational space control strengthens this advantage for redundant robots due to the inherent compliance in the null space of given tasks. However, high-level torque-based controllers have not been widely used for transitional robots such as industrial manipulators due to the low performance of precise control. One of the reasons is the uncertainty or disturbance in the kinematic and dynamic properties of the robot model. It leads to the inaccurate computation of the desired torque, deteriorating the control stability and performance. To estimate and compensate the disturbance using only proprioceptive sensors, the disturbance observer has been developed using inverse dynamics. It requires the joint acceleration information, which is noisy due to the numerical error in the second-order derivative of the joint position. In this work, a contact-consistent disturbance observer for a floating-base robot is proposed. The method uses the fixed contact position of the supporting foot as the kinematic constraints to estimate the joint acceleration error. It is incorporated into the dynamics model to reduce its effect on the disturbance torque solution, by which the observer becomes less dependent on the low-pass filter design. Another reason for the low performance of precise control is torque bandwidth limitation. Torque bandwidth is determined by the relationship between the input torque commanded to the actuator and the torque actually transmitted into the link. It can be regulated by various factors such as inner torque feedback loop, actuator dynamics, and joint elasticity, which deteriorates the control stability and performance. Operational space control is especially prone to this problem, since the limited bandwidth of a single actuator can reduce the performance of all related tasks simultaneously. In this work, an intuitive way to penalize low performance actuators is proposed for the operational space controller. The basic concept is to add joint torques only to high performance actuators recursively, which has the physical meaning of the joint-weighted torque solution considering each actuator performance. By penalizing the low performance actuators, the torque transmission error is reduced and the task performance is significantly improved. In addition, the joint trajectory is not required, which allows compliance in redundancy. The results of the thesis were verified by experiments using the 12-DOF biped robot DYROS-RED and the 7-DOF robot manipulator Franka Emika Panda.๋ณธ ํ•™์œ„ ๋…ผ๋ฌธ์€ ์™ธ๋ž€๊ณผ ํ† ํฌ ๋Œ€์—ญํญ ์ œํ•œ์ด ์กด์žฌํ•  ๋•Œ ํ† ํฌ ๊ธฐ๋ฐ˜ ์ž‘์—… ๊ณต๊ฐ„ ์ œ์–ด๊ธฐ์˜ ์ œ์–ด ์„ฑ๋Šฅ์„ ๋†’์ด๋Š” ๊ฒƒ์„ ๋ชฉํ‘œ๋กœ ํ•œ๋‹ค. ํ† ํฌ ๊ธฐ๋ฐ˜์˜ ๋กœ๋ด‡ ์ œ์–ด๊ธฐ๋Š” ๋ชฉํ‘œ ํ† ํฌ๋ฅผ ์ž…๋ ฅ ์‹ ํ˜ธ๋กœ์„œ ๊ตฌ๋™๊ธฐ์— ์ „๋‹ฌํ•œ๋‹ค. ํ† ํฌ๋Š” ํž˜ ๋ ˆ๋ฒจ์ด๊ธฐ ๋•Œ๋ฌธ์—, ํ† ํฌ ์ œ์–ด ๋กœ๋ด‡์€ ์œ„์น˜ ์ œ์–ด ๋กœ๋ด‡์— ๋น„ํ•ด ์™ธ๋ถ€ ํ™˜๊ฒฝ์ด๋‚˜ ์‚ฌ๋žŒ์œผ๋กœ๋ถ€ํ„ฐ ๊ฐ€ํ•ด์ง€๋Š” ์™ธ๋ ฅ์— ๋” ์œ ์—ฐํ•˜๊ฒŒ ๋Œ€์‘ํ•  ์ˆ˜ ์žˆ๋‹ค. ๊ทธ๋Ÿฌ๋ฏ€๋กœ ํ† ํฌ ์ œ์–ด๋Š” ๋ณดํ–‰์ด๋‚˜ ์ธ๊ฐ„-๋กœ๋ด‡ ์ƒํ˜ธ์ž‘์šฉ๊ณผ ๊ฐ™์€ ์ ‘์ด‰์„ ํฌํ•จํ•˜๋Š” ์ž‘์—…์„ ์œ„ํ•ด ํšจ๊ณผ์ ์œผ๋กœ ์‚ฌ์šฉ๋  ์ˆ˜ ์žˆ๋‹ค. ์ž‘์—… ๊ณต๊ฐ„ ์ œ์–ด๋Š” ์ด๋Ÿฌํ•œ ํ† ํฌ ์ œ์–ด์˜ ์žฅ์ ์„ ๋” ๊ฐ•ํ™”์‹œํ‚ฌ ์ˆ˜ ์žˆ๋Š”๋ฐ, ๋กœ๋ด‡์ด ์—ฌ์œ  ์ž์œ ๋„๊ฐ€ ์žˆ์„ ๋•Œ ์ž‘์—…์˜ ์˜๊ณต๊ฐ„์—์„œ ์กด์žฌํ•˜๋Š” ๋ชจ์…˜๋“ค์ด ๋‚ด์žฌ์ ์œผ๋กœ ์œ ์—ฐํ•˜๊ธฐ ๋•Œ๋ฌธ์ด๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ์ด๋Ÿฌํ•œ ์žฅ์ ์—๋„ ๋ถˆ๊ตฌํ•˜๊ณ  ํ† ํฌ ๊ธฐ๋ฐ˜์˜ ๋กœ๋ด‡ ์ œ์–ด๊ธฐ๋Š” ์ •๋ฐ€ ์ œ์–ด ์„ฑ๋Šฅ์ด ๋–จ์–ด์ง€๊ธฐ ๋•Œ๋ฌธ์— ์‚ฐ์—…์šฉ ๋กœ๋ด‡ ํŒ”๊ณผ ๊ฐ™์€ ์ „ํ†ต์ ์ธ ๋กœ๋ด‡์—๋Š” ๋„๋ฆฌ ์‚ฌ์šฉ๋˜์ง€ ๋ชปํ–ˆ๋‹ค. ๊ทธ ์ด์œ  ์ค‘ ํ•œ ๊ฐ€์ง€๋Š” ๋กœ๋ด‡ ๋ชจ๋ธ์˜ ๊ธฐ๊ตฌํ•™ ๋ฐ ๋™์—ญํ•™ ๋ฌผ์„ฑ์น˜์— ์กด์žฌํ•˜๋Š” ์™ธ๋ž€์ด๋‹ค. ๋ชจ๋ธ ์˜ค์ฐจ๋Š” ๋ชฉํ‘œ ํ† ํฌ๋ฅผ ๊ณ„์‚ฐํ•  ๋•Œ ์˜ค์ฐจ๋ฅผ ์œ ๋ฐœํ•˜๋ฉฐ, ์ด๊ฒƒ์ด ์ œ์–ด ์•ˆ์ •์„ฑ๊ณผ ์„ฑ๋Šฅ์„ ์•ฝํ™”์‹œํ‚ค๊ฒŒ ๋œ๋‹ค. ์™ธ๋ž€์„ ๋‚ด์žฌ ์„ผ์„œ๋งŒ์„ ์ด์šฉํ•˜์—ฌ ์ถ”์ • ๋ฐ ๋ณด์ƒํ•˜๊ธฐ ์œ„ํ•ด ์—ญ๋™์—ญํ•™ ๊ธฐ๋ฐ˜์˜ ์™ธ๋ž€ ๊ด€์ธก๊ธฐ๊ฐ€ ๊ฐœ๋ฐœ๋˜์–ด ์™”๋‹ค. ์™ธ๋ž€ ๊ด€์ธก๊ธฐ๋Š” ์—ญ๋™์—ญํ•™ ๊ณ„์‚ฐ์„ ์œ„ํ•ด ๊ด€์ ˆ ๊ฐ๊ฐ€์†๋„ ์ •๋ณด๊ฐ€ ํ•„์š”ํ•œ๋ฐ, ์ด ๊ฐ’์ด ๊ด€์ ˆ ์œ„์น˜๋ฅผ ๋‘ ๋ฒˆ ๋ฏธ๋ถ„ํ•œ ๊ฐ’์ด๊ธฐ ๋•Œ๋ฌธ์— ์ˆ˜์น˜์ ์ธ ์˜ค์ฐจ๋กœ ๋…ธ์ด์ฆˆํ•ด์ง€๋Š” ๋ฌธ์ œ๊ฐ€ ์žˆ์—ˆ๋‹ค. ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ๋ถ€์œ ํ˜• ๊ธฐ์ € ๋กœ๋ด‡์„ ์œ„ํ•œ ์ ‘์ด‰ ์กฐ๊ฑด์ด ๊ณ ๋ ค๋œ ์™ธ๋ž€ ๊ด€์ธก๊ธฐ๊ฐ€ ์ œ์•ˆ๋˜์—ˆ๋‹ค. ์ œ์•ˆ๋œ ๋ฐฉ๋ฒ•์€ ๋กœ๋ด‡์˜ ๊ณ ์ •๋œ ์ ‘์ด‰ ์ง€์ ์— ๋Œ€ํ•œ ๊ธฐ๊ตฌํ•™์ ์ธ ๊ตฌ์† ์กฐ๊ฑด์„ ์ด์šฉํ•˜์—ฌ ๊ด€์ ˆ ๊ฐ๊ฐ€์†๋„ ์˜ค์ฐจ๋ฅผ ์ถ”์ •ํ•œ๋‹ค. ์ถ”์ •๋œ ์˜ค์ฐจ๋ฅผ ๋™์—ญํ•™ ๋ชจ๋ธ์— ๋ฐ˜์˜ํ•˜์—ฌ ์™ธ๋ž€ ํ† ํฌ๋ฅผ ๊ณ„์‚ฐํ•จ์œผ๋กœ์จ ์ €์—ญ ํ†ต๊ณผ ํ•„ํ„ฐ ์„ฑ๋Šฅ์— ๋Œ€ํ•œ ์˜์กด๋„๋ฅผ ์ค„์ผ ์ˆ˜ ์žˆ๋‹ค. ํ† ํฌ ๊ธฐ๋ฐ˜ ์ œ์–ด์˜ ์ •๋ฐ€ ์ œ์–ด ์„ฑ๋Šฅ์ด ๋–จ์–ด์ง€๋Š” ๋˜ ๋‹ค๋ฅธ ์ด์œ  ์ค‘ ํ•˜๋‚˜๋Š” ํ† ํฌ ๋Œ€์—ญํญ ์ œํ•œ์ด๋‹ค. ํ† ํฌ ๋Œ€์—ญํญ์€ ๊ตฌ๋™๊ธฐ์— ์ „๋‹ฌ๋˜๋Š” ์ž…๋ ฅ ํ† ํฌ์™€ ์‹ค์ œ ๋งํฌ์— ์ „๋‹ฌ๋˜๋Š” ํ† ํฌ์™€์˜ ๊ด€๊ณ„๋กœ ๊ฒฐ์ •๋œ๋‹ค. ํ† ํฌ ๋Œ€์—ญํญ์€ ๊ตฌ๋™๊ธฐ ๋‚ด๋ถ€์˜ ํ† ํฌ ํ”ผ๋“œ๋ฐฑ ๋ฃจํ”„, ๊ตฌ๋™๊ธฐ ๋™์—ญํ•™, ๊ด€์ ˆ ํƒ„์„ฑ ๋“ฑ์˜ ์š”์ธ๋“ค์— ์˜ํ•ด ์ œํ•œ๋  ์ˆ˜ ์žˆ๋Š”๋ฐ ์ด๊ฒƒ์ด ์ œ์–ด ์•ˆ์ •์„ฑ ๋ฐ ์„ฑ๋Šฅ์„ ๊ฐ์†Œ์‹œํ‚จ๋‹ค. ์ž‘์—… ๊ณต๊ฐ„ ์ œ์–ด๋Š” ํŠนํžˆ ์ด ๋ฌธ์ œ์— ์ทจ์•ฝํ•œ๋ฐ, ๋Œ€์—ญํญ์ด ์ œํ•œ๋œ ๊ตฌ๋™๊ธฐ ํ•˜๋‚˜๊ฐ€ ๊ทธ์™€ ์—ฐ๊ด€๋œ ๋ชจ๋“  ์ž‘์—… ๊ณต๊ฐ„์˜ ์ œ์–ด ์„ฑ๋Šฅ์„ ๊ฐ์†Œ์‹œํ‚ฌ ์ˆ˜ ์žˆ๊ธฐ ๋•Œ๋ฌธ์ด๋‹ค. ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ์ž‘์—… ๊ณต๊ฐ„ ์ œ์–ด๊ธฐ์—์„œ ์„ฑ๋Šฅ์ด ๋‚ฎ์€ ๊ตฌ๋™๊ธฐ์˜ ์‚ฌ์šฉ์„ ์ œํ•œํ•˜๊ธฐ ์œ„ํ•œ ์ง๊ด€์ ์ธ ์ „๋žต์ด ์ œ์•ˆ๋˜์—ˆ๋‹ค. ๊ธฐ๋ณธ ์ปจ์…‰์€ ์ž‘์—… ์ œ์–ด๋ฅผ ์œ„ํ•œ ํ† ํฌ ์†”๋ฃจ์…˜์— ์„ฑ๋Šฅ์ด ์ข‹์€ ๊ด€์ ˆ์—๋งŒ ์ถ”๊ฐ€์ ์œผ๋กœ ํ† ํฌ ์†”๋ฃจ์…˜์„ ๋”ํ•ด๋‚˜๊ฐ€๋Š” ๊ฒƒ์œผ๋กœ, ์ด๊ฒƒ์€ ๊ฐ ๊ด€์ ˆ์˜ ๊ฐ€์ค‘์น˜๊ฐ€ ๊ณ ๋ ค๋œ ํ† ํฌ ์†”๋ฃจ์…˜์ด ๋˜๋Š” ๊ฒƒ์„ ์˜๋ฏธํ•œ๋‹ค. ์„ฑ๋Šฅ์ด ๋‚ฎ์€ ๊ตฌ๋™๊ธฐ์˜ ์‚ฌ์šฉ์„ ์ œํ•œํ•จ์œผ๋กœ์จ ํ† ํฌ ์ „๋‹ฌ ์˜ค์ฐจ๊ฐ€ ์ค„์–ด๋“ค๊ณ  ์ž‘์—… ์„ฑ๋Šฅ์ด ํฌ๊ฒŒ ํ–ฅ์ƒ๋  ์ˆ˜ ์žˆ๋‹ค. ๋ณธ ํ•™์œ„ ๋…ผ๋ฌธ์˜ ์—ฐ๊ตฌ ๊ฒฐ๊ณผ๋“ค์€ 12์ž์œ ๋„ ์ด์กฑ ๋ณดํ–‰ ๋กœ๋ด‡ DYROS-RED์™€ 7์ž์œ ๋„ ๋กœ๋ด‡ ํŒ” Franka Emika Panda๋ฅผ ์ด์šฉํ•œ ์‹คํ—˜์„ ํ†ตํ•ด ๊ฒ€์ฆ๋˜์—ˆ๋‹ค.1 INTRODUCTION 1 1.1 Motivation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 1.2 Contributions of Thesis . . . . . . . . . . . . . . . . . . . . . . . 4 1.3 Overview of Thesis . . . . . . . . . . . . . . . . . . . . . . . . . . 4 2 BACKGROUNDS 6 2.1 Operational Space Control . . . . . . . . . . . . . . . . . . . . . . 6 2.2 Dynamics Formulation . . . . . . . . . . . . . . . . . . . . . . . . 9 2.2.1 Fixed-Base Dynamics . . . . . . . . . . . . . . . . . . . . 9 2.2.1.1 Joint Space Formulation . . . . . . . . . . . . . 9 2.2.1.2 Operational Space Formulation . . . . . . . . . . 11 2.2.2 Floating-Base Dynamics . . . . . . . . . . . . . . . . . . . 12 2.2.2.1 Joint Space Formulation . . . . . . . . . . . . . 12 2.2.2.2 Operational Space Formulation . . . . . . . . . . 14 2.3 Position Tracking via PD Control . . . . . . . . . . . . . . . . . . 17 2.3.1 Torque Solution . . . . . . . . . . . . . . . . . . . . . . . 17 2.3.2 Orientation Control . . . . . . . . . . . . . . . . . . . . . 19 3 CONTACT-CONSISTENT DISTURBANCE OBSERVER FOR FLOATING-BASE ROBOTS 22 3.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22 3.2 Momentum-Based Disturbance Observer . . . . . . . . . . . . . . 24 3.3 The Proposed Method . . . . . . . . . . . . . . . . . . . . . . . . 25 3.4 Experiments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30 3.4.1 Setup . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30 3.4.2 External Force Estimation . . . . . . . . . . . . . . . . . . 33 3.4.3 Internal Disturbance Rejection . . . . . . . . . . . . . . . 35 3.5 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38 4 OPERATIONAL SPACE CONTROL UNDER ACTUATOR BANDWIDTH LIMITATION 40 4.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40 4.2 The Proposed Method . . . . . . . . . . . . . . . . . . . . . . . . 43 4.2.1 General Concepts . . . . . . . . . . . . . . . . . . . . . . . 43 4.2.2 OSF-Based Torque Solution . . . . . . . . . . . . . . . . . 45 4.2.3 Comparison With a Typical Method . . . . . . . . . . . . 47 4.3 Experiments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51 4.3.1 Setup . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51 4.3.2 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54 4.4 Comparison With Other Approaches . . . . . . . . . . . . . . . . 61 4.4.1 Controller Formulation . . . . . . . . . . . . . . . . . . . . 62 4.4.1.1 The Proposed Method . . . . . . . . . . . . . . . 62 4.4.1.2 The OSF Controller . . . . . . . . . . . . . . . . 62 4.4.1.3 The OSF-Filter Controller . . . . . . . . . . . . 62 4.4.1.4 The OSF-Joint Controller . . . . . . . . . . . . . 67 4.4.1.5 The Joint Controller . . . . . . . . . . . . . . . . 68 4.4.2 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . 68 4.5 Frequency Response of Joint Torque . . . . . . . . . . . . . . . . 72 4.6 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83 5 CONCLUSION 85 Abstract (In Korean) 100๋ฐ•

    Steering control for haptic feedback and active safety functions

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    Steering feedback is an important element that defines driverโ€“vehicle interaction. It strongly affects driving performance and is primarily dependent on the steering actuator\u27s control strategy. Typically, the control method is open loop, that is without any reference tracking; and its drawbacks are hardware dependent steering feedback response and attenuated driverโ€“environment transparency. This thesis investigates a closed-loop control method for electric power assisted steering and steer-by-wire systems. The advantages of this method, compared to open loop, are better hardware impedance compensation, system independent response, explicit transparency control and direct interface to active safety functions.The closed-loop architecture, outlined in this thesis, includes a reference model, a feedback controller and a disturbance observer. The feedback controller forms the inner loop and it ensures: reference tracking, hardware impedance compensation and robustness against the coupling uncertainties. Two different causalities are studied: torque and position control. The two are objectively compared from the perspective of (uncoupled and coupled) stability, tracking performance, robustness, and transparency.The reference model forms the outer loop and defines a torque or position reference variable, depending on the causality. Different haptic feedback functions are implemented to control the following parameters: inertia, damping, Coulomb friction and transparency. Transparency control in this application is particularly novel, which is sequentially achieved. For non-transparent steering feedback, an environment model is developed such that the reference variable is a function of virtual dynamics. Consequently, the driverโ€“steering interaction is independent from the actual environment. Whereas, for the driverโ€“environment transparency, the environment interaction is estimated using an observer; and then the estimated signal is fed back to the reference model. Furthermore, an optimization-based transparency algorithm is proposed. This renders the closed-loop system transparent in case of environmental uncertainty, even if the initial condition is non-transparent.The steering related active safety functions can be directly realized using the closed-loop steering feedback controller. This implies, but is not limited to, an angle overlay from the vehicle motion control functions and a torque overlay from the haptic support functions.Throughout the thesis, both experimental and the theoretical findings are corroborated. This includes a real-time implementation of the torque and position control strategies. In general, it can be concluded that position control lacks performance and robustness due to high and/or varying system inertia. Though the problem is somewhat mitigated by a robust H-infinity controller, the high frequency haptic performance remains compromised. Whereas, the required objectives are simultaneously achieved using a torque controller
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