Emanuel C. Brenag , Paulo S.P. Pessim , Pedro M. Oliveira , Reinaldo M. Palhares
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引用次数: 0
Abstract
This paper presents a quasi-data-driven static output feedback (SOF) control framework for discrete-time linear systems subject to time-varying state and input delays. The proposed controller synthesis leverages input-state-output data acquired from the open-loop system, integrated with delay-dependent data-based Linear Matrix Inequality (LMI) conditions derived using Lyapunov–Krasovskii stability theory. A salient feature of this methodology is its ability to compute controller gains without prior knowledge of the system dynamics, thereby eliminating the dependence on explicit mathematical models. Furthermore, a data-driven reference-tracking input scheme is developed for time-delay systems, addressing piecewise-constant reference trajectories while guaranteeing asymptotic stability of the tracking error. The efficacy of the proposed approach is rigorously validated through numerical simulations and also experimental implementation on a twin-rotor system for pitch angle tracking, demonstrating robust performance in both theoretical and practical settings.
期刊介绍:
The European Control Association (EUCA) has among its objectives to promote the development of the discipline. Apart from the European Control Conferences, the European Journal of Control is the Association''s main channel for the dissemination of important contributions in the field.
The aim of the Journal is to publish high quality papers on the theory and practice of control and systems engineering.
The scope of the Journal will be wide and cover all aspects of the discipline including methodologies, techniques and applications.
Research in control and systems engineering is necessary to develop new concepts and tools which enhance our understanding and improve our ability to design and implement high performance control systems. Submitted papers should stress the practical motivations and relevance of their results.
The design and implementation of a successful control system requires the use of a range of techniques:
Modelling
Robustness Analysis
Identification
Optimization
Control Law Design
Numerical analysis
Fault Detection, and so on.