FUTURE REFERENCE TRAJECTORY IMPROVEMENT IN SELF-TUNING I-PD CONTROLLER BASED ON GENERALIZED PREDICTIVE CONTROL LAW

2005 ◽  
Vol 38 (1) ◽  
pp. 24-29 ◽  
Author(s):  
Takao Sato ◽  
Akira Inoue
Keyword(s):  
Predictive Control ◽  
Generalized Predictive Control ◽  
Control Law ◽  
Reference Trajectory ◽  
Pd Controller ◽  
Self Tuning ◽  
Future Reference

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.

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.

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 The PVC Stripping Process Predictive Control Based on the Implicit Algorithm

2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
Shuzhi Gao ◽  
Liangliang Luan
Keyword(s):  
Real Time ◽  
Predictive Control ◽  
Temperature Control ◽  
Temperature Control System ◽  
Generalized Predictive Control ◽  
Control Law ◽  
Time Varying ◽  
Time Model ◽  
Implicit Algorithm ◽  
Online Correction

According to the nonlinear and parameters time-varying characteristics of stripper temperature control system, the PVC stripping process Generalized Predictive Control based on implicit algorithm is proposed. Firstly, supporting vector machine is adopted to dynamically modelize for the stripper temperature; Secondly, combining with real-time model linearized of nonlinear model, a predictive model is linearized for real-time online correction. Then, the implicit algorithm is used for optimal control law. Finally, the simulation results show that the algorithm has excellent validity and robustness of temperature control of the stripper.

Predictive Control Based on Fuzzy Expert PID Tuning Control

2012 ◽  
Vol 466-467 ◽  
pp. 1207-1211 ◽  
Author(s):  
Zheng Zai Qian ◽  
Gong Cai Xin ◽  
Jin Niu Tao
Keyword(s):  
Predictive Control ◽  
Model Uncertainty ◽  
Adaptive Controller ◽  
Automatic Tuning ◽  
Pid Controllers ◽  
Generalized Predictive Control ◽  
Control Law ◽  
Pid Tuning ◽  
Simulation Results ◽  
Expert Pid

In decade years, several simple methods for the automatic tuning of PID controllers have been proposed. There have been different approaches to the problem of deriving a PID-like adaptive controller. All of these can be classified into two broad categories: model-based; or expert systems. In this paper a new expert adaptive controller is proposed in which the underlying control law is a PID structure. The design is based on the fuzzy logic and the generalized predictive control theory. The proposed controller can be applied to a large class of systems which is model uncertainty or strong non-linearity. Simulation results have also been illustrated. It shows that the proposed expert PID-like controller performed well than generally used PID.

Sign in / Sign up

Export Citation Format

Share Document