Spatially Periodic Disturbance Rejection With Spatially Sampled Robust Repetitive Control

Author(s):  
Cheng-Lun Chen ◽  
George T.-C. Chiu

Repetitive controllers have been shown to be effective for tracking periodic reference commands or for rejecting periodic disturbances. Typical repetitive controllers are synthesized in temporal domain where the periods of the reference or disturbance signals are assumed to be known and stationary. For periodic references and disturbances with varying periods, researchers usually resort to adaptive and robust control approaches. For rotational motion systems where the disturbances or reference signals are spatially periodic (i.e., periodic with respect to angular displacement), the temporal period of the disturbance and reference signals will be inversely proportional to the rotational speed and vary accordingly. Motivating by reducing halftone banding for laser printers, we propose a design framework for synthesizing spatially sampled repetitive controller by reformulating a linear time-invariant system subject to spatially periodic disturbances using angular displacement as the independent variable. The resulting nonlinear system can be represented as a quasi-linear parameter-varying (quasi-LPV) system with the angular velocity as one of the varying state-dependent parameters. An LPV self-gain–scheduling controller that includes a spatially sampled repetitive control can be designed to take into consideration bounded model uncertainty and input nonlinearity, such as actuator saturation. Using the signal from an optical encoder pulse as a triggering interrupt, experimental results verified the effectiveness of the proposed approach in rejecting spatially periodic disturbances that cannot be compensated with fixed period temporal repetitive controllers.

1998 ◽  
Vol 120 (3) ◽  
pp. 423-426 ◽  
Author(s):  
Joono Sur ◽  
Brad E. Paden

In this paper we introduce a state observer for linear time-invariant systems with quantized outputs. The observer employs an orthogonal projection operation at quantizer output discontinuities to enhance its convergence rate for stable systems. The increasing rate of convergence and stability has been proven by using Lyapunov second method. Some sufficient and necessary conditions of stability for the unstable systems are derived. The sufficient condition of noise stability is given and the maximal bound of noise stability is presented. The proposed methodology has been applied to state estimation of a DC-motor with optical encoder.


2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Lan Zhou ◽  
Jinhua She ◽  
Shaowu Zhou ◽  
Qiwei Chen

This paper presents a method of designing a state-observer based modified repetitive-control system that provides a given H∞ level of disturbance attenuation for a class of strictly proper linear plants. Since the time delay in a repetitive controller can be treated as a kind of disturbance, we convert the system design problem into a standard state-feedback H∞ control problem for a linear time-invariant system. The Lyapunov functional and the singular-value decomposition of the output matrix are used to derive a linear-matrix-inequality (LMI) based design algorithm for the parameters of the feedback controller and the state-observer. A numerical example demonstrates the validity of the method.


Author(s):  
Zongxuan Sun ◽  
Tsu-Chin Tsao

Repetitive control that asymptotically tracks or rejects periodic signals has been widely used in many applications. For linear time invariant system, this problem has been thoroughly studied and solved. This paper presents the analysis and synthesis of repetitive control algorithms to track or reject periodic signals for linear time varying systems. Both continuous and discrete time domain results will be presented. A time varying internal model is embedded in the feedback loop to ensure asymptotic performance. It is shown that asymptotic performance can’t be achieved with a finite dimensional controller in the continuous time domain, while it is possible in the discrete time domain. Simulation results demonstrate the effectiveness of the proposed algorithms.


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