Relaxed Barrier Function Based Model Predictive Control
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Relaxed Barrier Function Based Model Predictive Control
Author: Christian Feller
language: en
Publisher: Logos Verlag Berlin GmbH
Release Date: 2017
In this thesis, we introduce the novel concept of relaxed barrier function based model predictive control and present a comprehensive theoretical and algorithmic framework for the design, analysis, and implementation of relaxed barrier function based MPC approaches. Instead of treating the underlying optimization as an idealized static map, a key motive of the MPC results and algorithms presented in this thesis is to study the interconnected dynamics of controlled plant and iterative optimization algorithm in an integrated barrier function based framework and to analyze the resulting overall closed-loop system both from a systems theoretic and algorithmic perspective. One of the presented main results is a novel class of barrier function based anytime MPC algorithms that guarantee important properties of the closed-loop system independently of the number of optimization algorithm iterations that are performed at each sampling step. The obtained theoretical results are illustrated by various numerical examples and benchmark tests as well as by an experimental case study in which the proposed class of barrier function based MPC algorithms is applied to the predictive control of a self-driving car.
Trajectory tracking, path following, and learning in model predictive control
Author: Fabian Russell Pfitz
language: en
Publisher: Logos Verlag Berlin GmbH
Release Date: 2023-08-21
In this thesis, we present novel model predictive control (MPC) formulations based on a convex open-loop optimal control problem to tackle the problem setup of trajectory tracking and path following as well as the control of systems with unknown system dynamic. In particular, we consider the framework of relaxed barrier function based MPC (rbMPC). We extend the existing stability theory to the trajectory tracking and the path following problem. We establish important system theoretic properties like closed-loop stability and exact constraint satisfaction under suitable assumptions. Moreover, we evaluate the developed MPC algorithms in the area of automated driving in simulations as well as in a real-world driving scenario. Further, we consider the control of completely unknown systems based on online optimization. We divide the overall problem into the design of an estimation algorithm and a control algorithm. The control algorithm is a model-independent receding horizon control algorithm in which important system theoretic properties like convergence to the origin are guaranteed without the knowledge of the true system parameters. The estimation and control algorithm are combined together and convergence to the origin of the closed-loop system for fully unknown linear time-invariant discrete-time systems is shown.
12th International Munich Chassis Symposium 2021
The increasing automation of driving functions and the electrification of powertrains present new challenges for the chassis with regard to complexity, redundancy, data security, and installation space. At the same time, the mobility of the future will also require entirely new vehicle concepts, particularly in urban areas. The intelligent chassis must be connected, electrified, and automated in order to be best prepared for this future. Contents Driving Simulators.- Innovative Chassis Systems.- Automated Driving and Racing.- New Methods and Systems.- Suspension and Ride Comfort.- All-Wheel Steering.- Future Brake Systems and Testing Technology.- Innovations in Tires and Wheels. Target audiences Automotive engineers and chassis specialists as well as students looking for state-of-the-art information regarding their field of activity - Lecturers and instructors at universities and universities of applied sciences with the main subject of automotive engineering - Experts, researchers and development engineers of the automotive and the supplying industry. Publisher ATZ live stands for top quality and a high level of specialist information and is part of Springer Nature, one of the leading publishing groups worldwide for scientific, educational and specialist literature. Partner TÜV SÜD is an international leading technical service organisation catering to the industry, mobility and certification segment.