With the development of technology and availability of data, it is sometimes easier to learn the control policies directly from the data, rather than modeling a plant and designing a controller. Modeling a plant is not always possible due to the complexity of the plant. Data-enabled predictive control (DeePC) is a recently proposed approach that combines system identification, estimation, and control in a single optimization problem. DeePC is primarily designed for LTI systems. The purpose of this thesis is to extend the application of DeePC to nonlinear systems with a particular focus on a non-holonomic ground robot. To reach this goal, we decompose the system states into different working modes where each mode can be linearly approximated. Furthermore, the data collection policies were also evaluated to conclude how they affect the performance of the DeePC. We identified several key challenges in this direction, namely: data-demanding structure, high computational complexity, and performance deterioration with increased non-linearity. While these challenges prohibited the application of DeePC to the ground robot system; we successfully applied the method to a benchmark non-linear system, the inverted pendulum on cart problem, and studied the effect of various design choices on control performance. Our observations indicate potential areas of improvement toward enabling DeePC for highly nonlinear systems. ; Med utvecklingen av teknik och tillgänglighet av data är det ibland enklare att lära sig styrpolicyerna direkt från data, snarare än att modellera ett system och designa en styrenhet. Att modellera ett system är inte alltid möjligt på grund av systemets komplexitet. Data aktiverad prediktiv kontroll (DeePC) är en nyligen föreslagen metod som kombinerar systemidentifiering, uppskattning och kontroll i ett enda optimeringsproblem. DeePC är främst designad för LTI-system. Syftet med denna avhandling är att utöka tillämpningen av DeePC till icke-linjära system med särskilt fokus på en icke-holonomisk markrobot. ...
Toward Adaptation of Data Enabled Predictive Control for Nonlinear Systems ; Mot Anpassning av Dataaktiverad Prediktiv Kontroll för Icke-linjära System
2022-01-01
Hochschulschrift
Elektronische Ressource
Englisch
DeePC , Data Driven Control , Nonlinear System , Non-holonomic Ground Robot , Double Integrator Model , Inverted Pendulum , Datadriven Kontroll , Icke-linjärt System , Icke-holonomisk Markrobot , Dubbelintegratormodell , Inverterad Pendel , Electrical Engineering , Electronic Engineering , Information Engineering , Elektroteknik och elektronik
DDC: | 629 |
Elektronisches Reifendruck-Kontroll-System
Kraftfahrwesen | 1990
|Elektronisches Reifendruck-Kontroll-System
Tema Archiv | 1990
|Programmu resursosberezhenija-pod osobyjj kontroll
IuD Bahn | 1999
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