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Linear Controller Design: Limits of Performance Via Convex Optimization (1990)
| Citations: | 201 - 25 self |
BibTeX
@MISC{Boyd90linearcontroller,
author = {Stephen Boyd and Craig Barratt and Stephen Norman},
title = {Linear Controller Design: Limits of Performance Via Convex Optimization},
year = {1990}
}
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Abstract
this paper, we first give a very brief overview of control engineering. The goal of control engineering is to improve, or in some cases ena- ble, the performance of a system by the addition of sensors, which measure various signals in the system and external command signals, control processors, which process the measu red signals to drive actuators, which affect the behav- ior of the system. A schematic diagram of a general control system is shown in Fig. 1. The use of the sensed response of the system (and not just the command signals) in the computation of the actuator signals is called feedback control, an old idea which has been developed and applied with great success in this century [1], [2]. Control engineering involves 1. Modeling or identification. The designer develops mathematical models of the relevant aspects of system to be controlled. This can be done using knowl- edge of the system (for example by applying Newton 's equations of motion to a mechanical system), and experimentally by observing responses of the Manuscript received November 30,1988; revised August 4,1989. This work was supported in part by the National Science Foundation (NSF) under ECS-85-52465, the Air Force Office of Scientific Research (AFOSR) under 89-0228, Boeing Electronics Company under LF0937, and Bell Communications Research, and the National Science and Engineering Research Council (Canada) 1967 Science and Engineering Scholarship. The authors arewith the Dept. of Electrical Engineering, Stanford University, Stanford, CA 94305, USA. IEEE Log Number 8933936. system to various excitations, a procedure known as s)zstem identification [3]. In some cases, several models are developed, varying in complexity and accu racy. 2. Control configuration: selection and placement of sensors an...
Keyphrases
control engineering performance via convex optimization linear controller design engineering scholarship mechanical system accu racy control processor great success general control system national science foundation various excitation sensed response command signal scientific research relevant aspect several model air force office engineering research council actuator signal bell communication research feedback control various signal old idea stanford university mathematical model ieee log number knowl edge control configuration national science zstem identification external command signal measu red signal behav ior electrical engineering brief overview boeing electronics company schematic diagram
