Spelling suggestions: "subject:"path following control"" "subject:"math following control""
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Path Following Control of Automated Vehicle Considering Model Uncertainties External Disturbances and Parametric VaryingDan Shen (12468429) 27 April 2022 (has links)
<p>Automated Vehicle Path Following Control (PFC) is an advanced control system that can regulate the vehicle into a collision-free region in the presence of other objects on the road. Common collision avoidance functions, such as forward collision warning and automatic emergency braking, have recently been developed and equipped on production vehicles. However, it is impossible to develop a perfectly precise vehicle model when the vehicle is driving. The most PFC did not consider uncertainties in the vehicle model, external disturbances, and parameter variations at the same time. To address the issues associated with this important feature and function in autonomous driving, a new vehicle PFC is proposed using a robust model predictive control (MPC) design technique based on matrix inequality and the theoretical approach of the hybrid $\&$ switched system. The proposed methodology requires a combination of continuous and discrete states, e.g. regulating the continuous states of the AV (e.g., velocity and yaw angle) and discrete switching of the control strategy that affects the dynamic behaviors of the AV under different driving speeds. Firstly, considering bounded model uncertainties, norm-bounded external disturbances, the system states and control matrices are modified. In addition, the vehicle time-varying longitudinal speed is considered, and a vehicle lateral dynamic model based on Linear Parameter Varying (LPV) is established by utilizing a polytope with finite vertices. Then the Min-Max robust MPC state feedback control law is obtained at every timestamp by solving a set of matrix inequalities which are derived from Lyapunov stability and the minimization of the worst-case in infinite-horizon quadratic objective function. Compared to adaptive MPC, nonlinear MPC, and cascade LPV control, the proposed robust LPV MPC shows improved tracing accuracy along vehicle lateral dynamics. Finally, the state feedback switched LPV control theory with separate Lyapunov functions under both arbitrary switching and average-dwell-time (ADT) switching conditions are studied and applied to cover the path following control in full speed range. Numerical examples, tracking effectiveness, and convergence analysis are provided to demonstrate and ensure the control effectiveness and strong robustness of the proposed algorithms.</p>
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Trajectory Design Based on Robust Optimal Control and Path Following Control / ロバスト最適制御と経路追従制御に基づく軌道設計Okura, Yuki 25 March 2019 (has links)
付記する学位プログラム名: デザイン学大学院連携プログラム / 京都大学 / 0048 / 新制・課程博士 / 博士(工学) / 甲第21761号 / 工博第4578号 / 新制||工||1713(附属図書館) / 京都大学大学院工学研究科航空宇宙工学専攻 / (主査)教授 藤本 健治, 教授 泉田 啓, 教授 太田 快人 / 学位規則第4条第1項該当 / Doctor of Philosophy (Engineering) / Kyoto University / DGAM
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State relativity and speed-allocated line-of-sight course control for path-following of underwater vehiclesBilale, Abudureheman January 2018 (has links)
Path-following is a primary task for most marine, air or space crafts, especially during autonomous operations. Research on autonomous underwater vehicles (AUV) has received large interests in the last few decades with research incentives emerging from the safe, cost-effective and practical solutions provided by their applications such as search and rescue, inspection and monitoring of pipe-lines ans sub-sea structures. This thesis presents a novel guidance system based on the popular line-of-sight (LOS) guidance law for path-following (PF) of underwater vehicles (UVs) subject to environmental disturbances. Mathematical modeling and dynamics of (UVs) is presented first. This is followed by a comprehensive literature review on guidance-based path-following control of marine vehicles, which includes revised definitions of the track-errors and more detailed illustrations of the general PF problem. A number of advances on relative equations of motion are made, which include an improved understanding of the fluid FLOW frame and expression of its motion states, an analytic method of modeling the signs of forces and moments and the proofs of passivity and boundedness of relative UV systems in 3-D. The revision in the relative equations of motion include the concept of state relativity, which is an improved understanding of relativity of motion states expressed in reference frames and is also useful in incorporating environmental disturbances. In addition, the concept of drift rate is introduced along with a revision on the angles of motion in 3-D. A switching mechanism was developed to overcome a drawback of a LOS guidance law, and the linear and nonlinear stability results of the LOS guidance laws have been provided, where distinctions are made between straight and curved PF cases. The guidance system employs the unique formulation and solution of the speed allocation problem of allocating a desired speed vector into x and y components, and the course control that employs the slip angle for desired heading for disturbance rejection. The guidance system and particularly the general course control problem has been extended to 3-D with the new definition of vertical-slip angle. The overall guidance system employing the revised relative system model, course control and speed allocation has performed well during path-following under strong ocean current and/or wave disturbances and measurement noises in both 2-D and 3-D scenarios. In 2-D and 3-D 4 degrees-of-freedom models (DOF), the common sway-underactuated and fully actuated cases are considered, and in 3-D 5-DOF model, sway and heave underactuated and fully actuated cases are considered. Stability results of the LOS guidance laws include the semi-global exponential stability (SGES) of the switching LOS guidance and enclosure-based LOS guidance for straight and curved paths, and SGES of the loolahead-based LOS guidance laws for curved paths. Feedback sliding mode and PID controllers are applied during PF providing a comparison between them, and simulations are carried out in MatLab.
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