Design and Experimental Evaluation of a Data-Oriented Generalized Predictive PID Controller

2016 ◽  
Vol 28 (5) ◽  
pp. 722-729 ◽  
Author(s):  
Zhe Guan ◽  
◽  
Shin Wakitani ◽  
Toru Yamamoto ◽  
Keyword(s):  
Predictive Control ◽  
Pid Controller ◽  
Control Design ◽  
Point Of View ◽  
Generalized Predictive Control ◽  
Control Law ◽  
Control Parameters ◽  
Proportional Integral Derivative ◽  
Molding Machine ◽  
Output Data

[abstFig src='/00280005/15.jpg' width='300' text='Schematic figure of data-oriented GPC-PID controller' ] This paper presents a data-oriented technique for designing a proportional-integral-derivative (PID) controller based on a generalized predictive control law for linear unknown systems. In several control design approaches, a model-based control theory, which requires accurate modeling and identification of the plant, is used to calculate the control parameters. However, in higher-order systems and/or systems with an unknown time delay such as chemical industries and thermal industries, it is difficult to model or identify the plant accurately. Over the last decade, data-oriented techniques in which the online or offline data are utilized have been attracting considerable attention. Designing the controllers for unknown plants based on only the input/output data is the main feature of this technique. In this study, controller parameters are first obtained by using a generalized predictive control law with the data-oriented technique, and are converted to PID parameters from the practical point of view. The proposed method is validated experimentally using a real injection-molding machine. The results demonstrate the efficiency of the proposed method.

scholarly journals GPC-Based Stable Reconfigurable Control

2003 ◽  
Author(s):  
Jianjun Shi ◽  
Atul G. Kelkar ◽  
Donald Soloway
Keyword(s):  
State Space ◽  
Predictive Control ◽  
Flight Control ◽  
Actuator Saturation ◽  
Control Design ◽  
Generalized Predictive Control ◽  
Control Law ◽  
Reconfigurable Control ◽  
Space Formulation ◽  
The Stability

This paper presents development of multi-input multi-output (MIMO) Generalized Predictive Control (GPC) law and its application to reconfigurable control design in the event of actuator saturation. The stability of the GPC control law without reconfiguration is first established using Riccati-based approach and state-space formulation. A novel reconfiguration strategy is developed for the systems which have actuator redundancy and are faced with actuator saturation type failure. An elegant reconfigurable control design is presented with stability proof. A numerical example with application to reconfigurable flight control is presented to demonstrate the results presented in the paper.

scholarly journals Injection Molding Process Control of Servo–Hydraulic System

2019 ◽  
Vol 10 (1) ◽  
pp. 71
Author(s):  
Chun-Ying Lin ◽  
Fang-Cheng Shen ◽  
Kuo-Tsai Wu ◽  
Huei-Huang Lee ◽  
Sheng-Jye Hwang
Keyword(s):  
Injection Molding ◽  
Hydraulic System ◽  
Pid Controller ◽  
Position Control ◽  
Performance Standards ◽  
Pressure Control ◽  
Injection Molding Process ◽  
Proportional Integral Derivative ◽  
Molding Machine ◽  
Molding Process

The present study constructs a servo–hydraulic system to simulate the filling and packing processes of an injection molding machine. Experiments are performed to evaluate the velocity and position control of the system in the filling stage and the pressure control in the packing stage. The results demonstrate that the proposed system meets the required performance standards when operated with the proportional-integral–derivative (PID) controller under a sampling frequency of 1000 Hz.

A Multi-Resolution PID Controller Based on the Wavelet Transform

2012 ◽  
Vol 472-475 ◽  
pp. 632-636 ◽  
Author(s):  
Cun Zhi Yao ◽  
Gui Xiang Zhang
Keyword(s):  
Control System ◽  
Wavelet Transform ◽  
Pid Controller ◽  
Control Design ◽  
Cumulative Effect ◽  
Measurement Noise ◽  
Time Varying ◽  
Error Signal ◽  
Proportional Integral Derivative ◽  
Proportional Integral Derivative Controller

The non-linear and time-varying natures of the process together with the large disturbances of several types are the key challenge for the control design. A controller based on multi- resolution decomposition using wavelets is presented in the paper. The wavelet is used to decompose the error signal into signals at different scales.These signals are then used to compensate for the uncertainties in the plant.The controller is similar to proportional integral derivative controller in principle and application. the output from this control system represents the cumulative effect of uncertainties such as measurement noise, frictional variations and external torque disturbances which manifest at different scales. This controller better solves the nonlinear and time-varying togetther with the great disturbance.

scholarly journals Fractional-Order Generalized Predictive Control: Application for Low-Speed Control of Gasoline-Propelled Cars

2013 ◽  
Vol 2013 ◽  
pp. 1-10 ◽  
Author(s):  
M. Romero ◽  
A. P. de Madrid ◽  
C. Mañoso ◽  
V. Milanés ◽  
B. M. Vinagre
Keyword(s):  
Predictive Control ◽  
Pid Controller ◽  
Control Strategies ◽  
Generalized Predictive Control ◽  
Unmodeled Dynamics ◽  
Mathematical Tool ◽  
Test Bed ◽  
External Disturbances ◽  
Highly Nonlinear ◽  
Control Application

There is an increasing interest in using fractional calculus applied to control theory generalizingclassicalcontrol strategies as the PID controller and developing new ones with the intention of taking advantage of characteristics supplied by this mathematical tool for the controller definition. In this work, the fractional generalization of the successful and spread control strategy known as model predictive control is applied to drive autonomously a gasoline-propelled vehicle at low speeds. The vehicle is a Citroën C3 Pluriel that was modified to act over the throttle and brake pedals. Its highly nonlinear dynamics are an excellent test bed for applying beneficial characteristics of fractional predictive formulation to compensate unmodeled dynamics and external disturbances.

Improving the Tracking of Generalized Predictive Control Controllers

1996 ◽  
Vol 210 (3) ◽  
pp. 169-182 ◽  
Author(s):  
J A Rossiter ◽  
B G Grinnell
Keyword(s):  
Frequency Domain ◽  
Predictive Control ◽  
Time Domain ◽  
Degree Of Freedom ◽  
Generalized Predictive Control ◽  
Control Law ◽  
Set Point ◽  
The Poor ◽  
Fixed Order ◽  
Two Degree Of Freedom

One of the advantages of predictive control is its ability to take optimal account of information about future set point changes in the specification of the control law. However, the optimum GPC (generalized predictive control) prefilter that uses this information can lead to a deterioration rather than an improvement in the accuracy of tracking. Some simple modifications to GPC to overcome this problem are discussed. It will then be shown how some simple algorithms can be used to design an optimal prefilter that does not have any of the poor effects arising from the standard choice and hence always improves the performance. The basis of the technique is analogous to the two-degree-of-freedom designs common in the literature on H∞. However, here the emphasis is on fixed-order prefilters designed from a time domain, not a frequency domain, objective.

Performance-Adaptive Generalized Predictive Control-Based Proportional-Integral-Derivative Control System and Its Application

2014 ◽  
Vol 136 (6) ◽  
Author(s):  
Takao Sato ◽  
Toru Yamamoto ◽  
Nozomu Araki ◽  
Yasuo Konishi
Keyword(s):  
Control System ◽  
Predictive Control ◽  
Pid Control ◽  
Design Method ◽  
Design Parameters ◽  
Generalized Predictive Control ◽  
Control Performance ◽  
Proportional Integral Derivative ◽  
Proportional Integral ◽  
Proportional Integral Derivative Control

In the present paper, we discuss a new design method for a proportional-integral-derivative (PID) control system using a model predictive approach. The PID compensator is designed based on generalized predictive control (GPC). The PID parameters are adaptively updated such that the control performance is improved because the design parameters of GPC are selected automatically in order to attain a user-specified control performance. In the proposed scheme, the estimated plant parameters are updated only when the prediction error increases. Therefore, the control system is not updated frequently. The control system is updated only when the control performance is sufficiently improved. The effectiveness of the proposed method is demonstrated numerically. Finally, the proposed method is applied to a weigh feeder, and experimental results are presented.

scholarly journals A Design of Auto-Tuning PID Controller Based on Generalized Predictive Control for a PVC Reactor.

1999 ◽  
Vol 25 (2) ◽  
pp. 248-252
Author(s):  
NORIO MIURA ◽  
MASAO IMAEDA ◽  
KYOUJI HASHIMOTO ◽  
R. K. WOOD ◽  
HIROFUMI HATTORI ◽  
...  
Keyword(s):  
Predictive Control ◽  
Pid Controller ◽  
Generalized Predictive Control ◽  
Auto Tuning
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