Robust Control of Input-Delay Linear Parameter-Varying (LPV) Systems

Practical systems are nonlinear and time-varying and thus linear techniques can expose their control design to extra conservatism. Nevertheless, the Linear Parameter-Varying (LPV) representation can effectively describe them, which in contrast to linearization, maintains the principal dynamic modes of the original system. Additionally, the LPV and gain-scheduling control design benefit from the wealth of robust and optimal control techniques to acquire better performance over classical linear methods. Moreover, the majority of engineering systems are affected by input delays. Since there is a lag between the control signal and the system's response to it, input delay degrades a system's performance by reducing the bandwidth and even cause instability in severe cases. This research on input-delay LPV systems addresses their robust control in the presence of parameter variations and also time-varying delays. Previous works have typically addressed the LPV systems with state delays which are constant or mostly slowly varying. In contrast to such works, our first approach through the frequency-domain analysis assumes the delay and system parameters can vary arbitrarily within a priori known bounds which are pre-determined through tests. Then a low-pass filter is proposed to acquire robust stability over all parameter and delay variations for first-order time-delay systems which leads to a closed-form inequality for the filter tuning parameter in terms of nominal parameters and delay and their bounds. The results are applied to Air-Fuel Ratio (AFR) control in Spark-Ignition (SI) lean-burn engines and automated Mean Arterial Blood Pressure (MAP) regulation for the clinical resuscitation of hypotensive patients. In our second approach, time-domain techniques are employed to stabilize input-delay LPV systems characterized via a prescribed level of performance for the closed-loop system. It is assumed that parameters and the delay rate are varying within a priori known bounds. Moreover, the problem of such systems under input constraints or saturation is addressed in this framework and stabilizability conditions are described via convex constraints, known as Linear Matrix Inequality (LMI) conditions, to be solved numerically. The results are applied to AFR control in conventional SI engines and the MAP LPV model estimation and control for clinically resuscitating patients with hypotension.

Name thesis:degree_name

Doctor of Philosophy

Discipline thesis:degree_discipline

Mechanical Engineering

Grantor

University of Houston

Year dc:date.issued

2020

Author dc:creator

• Salavati, Saeed

Advisors dc:contributor.advisor

• Grigoriadis, Karolos
• Franchek , Matthew A.

Committee members dc:contributor.committeemember

• Chen, Zheng
• Song, Gangbing
• Provence, Robert

• Biomedical engineering
• Mechanical engineering
• Engineering

Language dc:language.iso

en

Handle dc:identifier.uri

https://hdl.handle.net/10657/19857

OAI identifier oai:identifier

oai:uh-ir.tdl.org:10657/19857