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.

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.

A zero phase error tracking based path precompensation method for high-speed machining

2015 ◽  
Vol 230 (2) ◽  
pp. 230-239 ◽  
Author(s):  
Xuewei Li ◽  
Jun Zhang ◽  
Wanhua Zhao ◽  
Bingheng Lu
Keyword(s):  
Tracking Control ◽  
High Speed ◽  
Control Algorithm ◽  
Phase Error ◽  
Great Influence ◽  
Contour Error ◽  
Machining Accuracy ◽  
High Speed Machining ◽  
Feed System ◽  
Zero Phase

Contour error due to the dynamic characteristics of feed system has a great influence on machining accuracy, in high-speed machining. In this paper, a new path precompensation method is proposed using zero phase error tracking control algorithm to improve the contouring accuracy for multiaxis machining with large feed rates. In this method, the outputs are predicted with the identified position-loop models of feed systems, and a contour error calculator is designed to calculate contour error in each sample instance using the predicted output and reference input. In order to compensate the contour error resulting from the dynamic tracking error of feed systems, the contour error vector is decomposed orthogonally and the compensation components for individual axis are calculated using zero phase error tracking control algorithm. Simulations showed that contour errors can be significantly improved with small compensation using the new path precompensation method for linear, circular, and parabola contours. Experimental results showed that the new method can reduce contour error significantly and achieve a better compensation compared with zero phase error tracking control and cross-coupled path pre-compensation.

Zero Phase Error Tracking Control for Square Sampled-Data Systems

1991 ◽  
Vol 113 (3) ◽  
pp. 506-509 ◽  
Author(s):  
H. Ali Pak ◽  
G. Q. Li
Keyword(s):  
Tracking Control ◽  
Control Algorithm ◽  
Phase Error ◽  
Data Systems ◽  
Sampled Data ◽  
Minimal Order ◽  
Phase Cancellation ◽  
Feedforward Controller ◽  
Zero Phase ◽  
Function Matrix

A multivariable version of the zero phase error tracking control algorithm is presented for sampled-data systems. The feedforward controller is based on the minimal-order inverse of a square system’s transfer function matrix. It is shown that, apart from phase cancellation, complete input/output decoupling will result from the use of the controller. Using a simulation study, the control algorithm’s performance is demonstrated for a multivariable positioning system.

Design of Optimum Controller of APT Fine Tracking Control System

2013 ◽  
Vol 712-715 ◽  
pp. 2738-2741 ◽  
Author(s):  
Ming Qiu Li ◽  
Shu Hua Jiang
Keyword(s):  
Pid Control ◽  
Tracking Control ◽  
Control Algorithm ◽  
Tracking System ◽  
Dynamic Performance ◽  
Tracking Error ◽  
Stable State ◽  
Response Speed ◽  
Optimum Control ◽  
Performance Requirements

APT (Acquisition, Pointing, and Tracking) system of space laser communication adopts compound axis structure; it consists of coarse tracking and fine tracking system. Its response speed and tracking precision mainly rests with the fine tracking system. Traditional PID control algorithm often is used in APT fine tracking system. In order to improve the dynamic performance of the system and decrease the tracking error, optimum control technology was adopted in this paper. On the basis of considering the system dynamic performance requirements and tracking precision requirement, optimum controller was designed. The simulation result shows that the bandwidth of APT fine tracking system is up to 1310 Hz, and the stable state error is less than 0.002. Compared with PID control, optimum control can improve the tracking performance of system.

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