Optimal Feedforward Prefilter With Frequency Domain Specification for Nonminimum Phase Systems

1996 ◽  
Vol 118 (4) ◽  
pp. 791-795 ◽  
Author(s):  
Dirk Torfs ◽  
Joris De Schutter
Keyword(s):  
Phase Error ◽  
Time Domain Analysis ◽  
Least Square ◽  
Superior Performance ◽  
Reference Trajectory ◽  
Nonminimum Phase ◽  
Nonminimum Phase Systems ◽  
Gain Error ◽  
Phase Systems ◽  
Zero Phase

The paper shows the influence of the location of unstable zeros on the tracking performance of feedforward prefilters. Unstable zeros are divided into a number of classes. It is shown that existing feedforward prefilters (Zero Phase Error Tracking Control (ZPETC), E-filter, Extended Bandwidth ZPETC, ...) perform well for two classes, but fail for a particular class of unstable zeros. For this class, a characteristic frequency, fc, exists such that the induced gain error attenuates all frequencies of the reference trajectory f ≤ fc and amplifies frequencies f > fc. Hence, it is impossible to freely select the tracking bandwidth. Therefore, an optimal feedforward prefilter for discrete time nonminimum phase systems is presented to deal with this class of unstable zeros. As in the ZPETC method, the prefilter compensates for unstable zeros in the inverse system model, retains the zero phase property, and introduces small gain errors. But in addition, the design minimizes a cost function for which a least square solution is found. A frequency and time domain analysis shows the superior performance of the presented optimal prefilter design even for trajectory with high frequency components.

Extended Bandwidth Zero Phase Error Tracking Control of Nonminimal Phase Systems

1992 ◽  
Vol 114 (3) ◽  
pp. 347-351 ◽  
Author(s):  
D. Torfs ◽  
J. De Schutter ◽  
J. Swevers
Keyword(s):  
Tracking Control ◽  
Control Algorithm ◽  
Phase Error ◽  
Tracking Error ◽  
Flexible Robot ◽  
Phase Errors ◽  
Gain Error ◽  
Small Gain ◽  
Phase Systems ◽  
Zero Phase

This paper describes a new feedforward algorithm for accurate tracking control of nonminimal phase systems. Accurate feedforward calculation involves a prefilter design using the inverse system model. Nonminimal phase systems cause problems with this prefilter design, because unstable zeros become unstable poles in the inverse model. The zero phase error tracking control algorithm (ZPETC) consists of a substitution scheme, which removes the unstable zeros. This scheme introduces a small gain error, which increases with frequency, but no phase error. This paper investigates additional properties which give more insight into the ZPETC algorithm, and allow to improve it. The improved algorithm is based on the same substitution scheme as ZPETC, but adds additional feedforward terms to compensate for the gain error. These additional terms increase the frequency range for which the overall transfer function has only limited gain error, without introducing phase errors. The additional feedforward terms repeatedly reduce the tracking error proportional to ε2, ε4, ε6, …, where ε is the ZPETC tracking error. The new feedforward algorithm or new substitution scheme is therefore called “extended bandwidth zero phase error tracking control algorithm” (EBZPETC). Experimental results on a one-link flexible robot compares both methods.

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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