Design of an Auto-Tuning PID Controller by a Generalized Predictive Control Method

2005 ◽  
Vol 38 (2) ◽  
pp. 147-153 ◽  
Author(s):  
Wenlong Zhang ◽  
Masao Imaeda ◽  
Reginald K. Wood ◽  
Kyoji Hashimoto
Keyword(s):  
Predictive Control ◽  
Pid Controller ◽  
Control Method ◽  
Generalized Predictive Control ◽  
Auto Tuning

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

Auto-Tuning PID Control With Generalized Predictive Control Method Using Kalman Filter

2003 ◽  
Vol 2003.5 (0) ◽  
pp. 133-134
Author(s):  
Wenlong Zhang ◽  
Masao IMAEDA ◽  
Kyoji HASHIMOTO ◽  
Takaaki KANBE
Keyword(s):  
Kalman Filter ◽  
Predictive Control ◽  
Pid Control ◽  
Control Method ◽  
Generalized Predictive Control ◽  
Auto Tuning

scholarly journals Adaptive Air-Fuel Ratio Regulation for Port-Injected Spark-Ignited Engines Based on a Generalized Predictive Control Method

Energies ◽  
2019 ◽  
Vol 12 (1) ◽  
pp. 173 ◽  
Author(s):  
Lei Meng ◽  
Xiaofeng Wang ◽  
Chunnian Zeng ◽  
Jie Luo
Keyword(s):  
Predictive Control ◽  
Noise Suppression ◽  
Control Method ◽  
Simulation Analysis ◽  
Catalytic Converter ◽  
Exhaust Emission ◽  
Generalized Predictive Control ◽  
Si Engine ◽  
Fuel Ratio ◽  
Wall Wetting

The accurate air-fuel ratio (AFR) control is crucial for the exhaust emission reduction based on the three-way catalytic converter in the spark ignition (SI) engine. The difficulties in transient cylinder air mass flow measurement, the existing fuel mass wall-wetting phenomenon, and the unfixed AFR path dynamic variations make the design of the AFR controller a challenging task. In this paper, an adaptive AFR regulation controller is designed using the feedforward and feedback control scheme based on the dynamical modelling of the AFR path. The generalized predictive control method is proposed to solve the problems of inherent nonlinearities, time delays, parameter variations, and uncertainties in the AFR closed loop. The simulation analysis is investigated for the effectiveness of noise suppression, online prediction, and self-correction on the SI engine system. Moreover, the experimental verification shows an acceptable performance of the designed controller and the potential usage of the generalized predictive control in AFR regulation application.

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.

Temperature Control in Distillation Column Using Generalized Predictive Control Method

2003 ◽  
Vol 29 (4) ◽  
pp. 541-545 ◽  
Author(s):  
Zhang Wenlong ◽  
Masao Imaeda ◽  
Kyouji Hashimoto ◽  
Takaaki Kanbe ◽  
Hirofumi Hattori
Keyword(s):  
Predictive Control ◽  
Temperature Control ◽  
Distillation Column ◽  
Control Method ◽  
Generalized Predictive Control

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.

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