Precise Tracking for Continuous‐Time Non‐Minimum Phase Systems

2018 ◽  
Vol 21 (5) ◽  
pp. 2395-2406 ◽  
Author(s):  
Youling Zhang ◽  
Qiuguo Zhu ◽  
Rong Xiong
Keyword(s):  
Continuous Time ◽  
Minimum Phase ◽  
Phase Systems

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

2016 ◽  
Vol 48 (7) ◽  
pp. 1438-1459 ◽  
Author(s):  
Jason Sheng-Hong Tsai ◽  
Ying-Ting Liao ◽  
Faezeh Ebrahimzadeh ◽  
Sheng-Ying Lai ◽  
Te-Jen Su ◽  
...  
Keyword(s):  
Continuous Time ◽  
Minimum Phase ◽  
Linear Quadratic ◽  
State Estimate ◽  
Optimal Linear ◽  
Phase Systems

scholarly journals Positive stable realizations of fractional continuous-time linear systems

2011 ◽  
Vol 21 (4) ◽  
pp. 697-702 ◽  
Author(s):  
Tadeusz Kaczorek
Keyword(s):  
Linear Systems ◽  
Continuous Time ◽  
Minimum Phase ◽  
Transfer Matrices ◽  
Phase Systems ◽  
Poles And Zeros ◽  
Time Linear

Positive stable realizations of fractional continuous-time linear systemsConditions for the existence of positive stable realizations with system Metzler matrices for fractional continuous-time linear systems are established. A procedure based on the Gilbert method for computation of positive stable realizations of proper transfer matrices is proposed. It is shown that linear minimum-phase systems with real negative poles and zeros always have positive stable realizations.

scholarly journals Decentralized control of sequentially minimum phase systems

1999 ◽  
Vol 44 (10) ◽  
pp. 1909-1913 ◽  
Author(s):  
K.H. Johansson ◽  
A. Rantzer
Keyword(s):  
Decentralized Control ◽  
Minimum Phase ◽  
Phase Systems

Tracking Control of Non-Minimum Phase Systems Using Filtered Basis Functions: A NURBS-Based Approach

2015 ◽  
Author(s):  
Molong Duan ◽  
Keval S. Ramani ◽  
Chinedum E. Okwudire
Keyword(s):  
Tracking Control ◽  
Phase Error ◽  
Approximate Model ◽  
Basis Functions ◽  
Minimum Phase ◽  
Tracking Errors ◽  
Model Inversion ◽  
B Spline ◽  
Phase Systems ◽  
Zero Phase

This paper proposes an approach for minimizing tracking errors in systems with non-minimum phase (NMP) zeros by using filtered basis functions. The output of the tracking controller is represented as a linear combination of basis functions having unknown coefficients. The basis functions are forward filtered using the dynamics of the NMP system and their coefficients selected to minimize the errors in tracking a given trajectory. The control designer is free to choose any suitable set of basis functions but, in this paper, a set of basis functions derived from the widely-used non uniform rational B-spline (NURBS) curve is employed. Analyses and illustrative examples are presented to demonstrate the effectiveness of the proposed approach in comparison to popular approximate model inversion methods like zero phase error tracking control.

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