A new PI optimal linear quadratic state-estimate tracker for continuous-time non-square non-minimum phase systems

Jason Sheng Hong Tsai; Ying Ting Liao; Faezeh Ebrahimzadeh; Sheng Ying Lai; Te Jen Su; Shu Mei Guo; Leang San Shieh; Tzong Jiy Tsai

doi:10.1080/00207721.2016.1261201

A new PI optimal linear quadratic state-estimate tracker for continuous-time non-square non-minimum phase systems

Jason Sheng Hong Tsai, Ying Ting Liao, Faezeh Ebrahimzadeh, Sheng Ying Lai, Te Jen Su, Shu Mei Guo, Leang San Shieh, Tzong Jiy Tsai

研究成果: Article › 同行評審

5 引文斯高帕斯（Scopus）

摘要

Based on the proportional-integral-derivative (PID) filter-shaping approach, this paper presents a new proportional-plus-integral (PI) optimal linear quadratic state estimator (LQSE) for the continuous-time non-square and non-minimum phase (NMP) multivariable systems. Together with the recently developed optimal linear quadratic tracker (LQT), the proposed LQSE-based tracker is able to optimally achieve good minimum phase-like tracking performances for a non-square NMP multivariable system with unmeasurable states and arbitrary command inputs.

原文	English
頁（從 - 到）	1438-1459
頁數	22
期刊	International Journal of Systems Science
卷	48
發行號	7
DOIs	https://doi.org/10.1080/00207721.2016.1261201
出版狀態	Published - 2017 5月 19

All Science Journal Classification (ASJC) codes

控制與系統工程
理論電腦科學
電腦科學應用

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10.1080/00207721.2016.1261201

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引用此

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title = "A new PI optimal linear quadratic state-estimate tracker for continuous-time non-square non-minimum phase systems",

abstract = "Based on the proportional-integral-derivative (PID) filter-shaping approach, this paper presents a new proportional-plus-integral (PI) optimal linear quadratic state estimator (LQSE) for the continuous-time non-square and non-minimum phase (NMP) multivariable systems. Together with the recently developed optimal linear quadratic tracker (LQT), the proposed LQSE-based tracker is able to optimally achieve good minimum phase-like tracking performances for a non-square NMP multivariable system with unmeasurable states and arbitrary command inputs.",

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AU - Lai, Sheng Ying

AU - Su, Te Jen

AU - Guo, Shu Mei

AU - Shieh, Leang San

AU - Tsai, Tzong Jiy

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N2 - Based on the proportional-integral-derivative (PID) filter-shaping approach, this paper presents a new proportional-plus-integral (PI) optimal linear quadratic state estimator (LQSE) for the continuous-time non-square and non-minimum phase (NMP) multivariable systems. Together with the recently developed optimal linear quadratic tracker (LQT), the proposed LQSE-based tracker is able to optimally achieve good minimum phase-like tracking performances for a non-square NMP multivariable system with unmeasurable states and arbitrary command inputs.

AB - Based on the proportional-integral-derivative (PID) filter-shaping approach, this paper presents a new proportional-plus-integral (PI) optimal linear quadratic state estimator (LQSE) for the continuous-time non-square and non-minimum phase (NMP) multivariable systems. Together with the recently developed optimal linear quadratic tracker (LQT), the proposed LQSE-based tracker is able to optimally achieve good minimum phase-like tracking performances for a non-square NMP multivariable system with unmeasurable states and arbitrary command inputs.

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A new PI optimal linear quadratic state-estimate tracker for continuous-time non-square non-minimum phase systems

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