{"title":"约束优化控制器设计的实用方法:H2或H/spl优化与多个H2和/或H/spl infin/约束","authors":"P. Titterton, J. Olkin","doi":"10.1109/ACSSC.1995.540902","DOIUrl":null,"url":null,"abstract":"This paper presents a practical algorithm for multi-input multi-output control law synthesis with an H/sup 2/- or H/sup /spl infin//-norm minimization criterion and multiple H/sup 2/- and/or H/sup /spl infin//-norm constraints. The plant is described by its discrete-time impulse response matrix, which can be determined directly from measurements. The control law design parameters are the tap weights of an FIR discretization of the Q-parameter. The multi-constraint H/sup 2//H/sup /spl infin// control law synthesis is written as a convex constrained optimization problem and solved as a structured semi-definite program. As a design example, we control the acoustic radiation from a (mathematically modeled) submerged spherical shell. The plant-model impulse response matrix has McMillan degree 800. We specify, synthesize, and compare three controllers: one designed by standard H/sup 2/ techniques; one designed by H/sup /spl infin// minimization with three H/sup /spl infin// and three H/sup 2/ constraints; and one designed by H/sup 2/ minimization with the same constraints. In a single design iteration, the multi-constraint H/sup 2//H/sup /spl infin// controllers achieve the best possible performance given the constraints; after several design iterations, the standard H/sup 2/ controller achieves slightly worse performance with several constraint violations.","PeriodicalId":171264,"journal":{"name":"Conference Record of The Twenty-Ninth Asilomar Conference on Signals, Systems and Computers","volume":"49 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1995-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"A practical method for constrained-optimization controller design: H2 or H/spl infin/ optimization with multiple H2 and/or H/spl infin/ constraints\",\"authors\":\"P. Titterton, J. Olkin\",\"doi\":\"10.1109/ACSSC.1995.540902\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents a practical algorithm for multi-input multi-output control law synthesis with an H/sup 2/- or H/sup /spl infin//-norm minimization criterion and multiple H/sup 2/- and/or H/sup /spl infin//-norm constraints. The plant is described by its discrete-time impulse response matrix, which can be determined directly from measurements. The control law design parameters are the tap weights of an FIR discretization of the Q-parameter. The multi-constraint H/sup 2//H/sup /spl infin// control law synthesis is written as a convex constrained optimization problem and solved as a structured semi-definite program. As a design example, we control the acoustic radiation from a (mathematically modeled) submerged spherical shell. The plant-model impulse response matrix has McMillan degree 800. We specify, synthesize, and compare three controllers: one designed by standard H/sup 2/ techniques; one designed by H/sup /spl infin// minimization with three H/sup /spl infin// and three H/sup 2/ constraints; and one designed by H/sup 2/ minimization with the same constraints. In a single design iteration, the multi-constraint H/sup 2//H/sup /spl infin// controllers achieve the best possible performance given the constraints; after several design iterations, the standard H/sup 2/ controller achieves slightly worse performance with several constraint violations.\",\"PeriodicalId\":171264,\"journal\":{\"name\":\"Conference Record of The Twenty-Ninth Asilomar Conference on Signals, Systems and Computers\",\"volume\":\"49 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1995-10-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Conference Record of The Twenty-Ninth Asilomar Conference on Signals, Systems and Computers\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ACSSC.1995.540902\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Conference Record of The Twenty-Ninth Asilomar Conference on Signals, Systems and Computers","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ACSSC.1995.540902","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A practical method for constrained-optimization controller design: H2 or H/spl infin/ optimization with multiple H2 and/or H/spl infin/ constraints
This paper presents a practical algorithm for multi-input multi-output control law synthesis with an H/sup 2/- or H/sup /spl infin//-norm minimization criterion and multiple H/sup 2/- and/or H/sup /spl infin//-norm constraints. The plant is described by its discrete-time impulse response matrix, which can be determined directly from measurements. The control law design parameters are the tap weights of an FIR discretization of the Q-parameter. The multi-constraint H/sup 2//H/sup /spl infin// control law synthesis is written as a convex constrained optimization problem and solved as a structured semi-definite program. As a design example, we control the acoustic radiation from a (mathematically modeled) submerged spherical shell. The plant-model impulse response matrix has McMillan degree 800. We specify, synthesize, and compare three controllers: one designed by standard H/sup 2/ techniques; one designed by H/sup /spl infin// minimization with three H/sup /spl infin// and three H/sup 2/ constraints; and one designed by H/sup 2/ minimization with the same constraints. In a single design iteration, the multi-constraint H/sup 2//H/sup /spl infin// controllers achieve the best possible performance given the constraints; after several design iterations, the standard H/sup 2/ controller achieves slightly worse performance with several constraint violations.