Optimal Control of DC-DC Buck Converter via Linear Systems With Inaccessible Markovian Jumping Modes

Abstract

Abstract-The note presents an algorithm for the average cost control problem of continuous-time Markov jump linear systems. The controller assumes a linear state-feedback form and the corresponding control gain does not depend on the Markov chain. In this scenario, the control problem is that of minimizing the long-run average cost. As an attempt to solve the problem, we derive a global convergent algorithm that generates a gain satisfying necessary optimality conditions. Our algorithm has practical implications, as illustrated by the experiments that were carried out to control an electronic dc-dc buck converter. The buck converter supplied a load that suffered abrupt changes driven by a homogeneous Markov chain. Besides, the source of the buck converter also suffered abrupt Markov-driven changes. The experimental results support the usefulness of our algorithm.

Constrained stochastic control of positive Takagi-Sugeno fuzzy systems with Markov jumps and its application to a DC-DC boost converter

“…Markov jump linear systems represent a class of stochastic systems that have attracted widespread interest due to their recent applications in real-time processes subject to random, abrupt changes, which may be engendered by the external environment—we can find current applications in electronics (Vargas et al, 2016, 2017), motors (Kim, 2017; Shen et al, 2019), renewable energy (Lin et al, 2018; Zhai et al, 2019), networks (Zhang et al, 2013), robot arm systems (Li et al, 2017; Zong et al, 2019), among others (Wu et al, 2019; Zhang and Prieur, 2017; Zhang et al, 2018); see also the monographs in Bolzern and Colaneri (2015) and Costa et al (2013) for further motivation.…”

Optimal filter for MJL system with delayed modes and observations

“…This family of systems can model several problems, where the structure of the plant is subject to random abrupt changes due to sudden environment changes, failures or repairs, modification of the operating point of a non‐linear system, etc. Without attempting to be comprehensive, we can refer to applications of MJLS in robotics, dc motors, mathematical finance, communication networks, fault tolerant control, and flight systems [1–3]. This large number of applications lead to a great interest in this field and many results regarding control and estimation problems can be found in the current literature [4–8].…”

Identification of DC–DC buck converter dynamics using relay feedback method with experimental validation

“…To analyse the converter performance, mathematical modelling is developed using different methods. The state-space averaging method is most commonly used for the design and analysis of converters [7][8][9]. This method is approximated to identify the model during small changes.…”