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.

A Design Method of LS-SVM Based Stable Adaptive Controller for a Class of Nonlinear Systems

2011 ◽  
Vol 48-49 ◽  
pp. 17-20
Author(s):  
Chun Li Xie ◽  
Tao Zhang ◽  
Dan Dan Zhao ◽  
Cheng Shao
Keyword(s):  
Nonlinear Systems ◽  
Design Method ◽  
Nonlinear Function ◽  
Lyapunov Stability Theory ◽  
Adaptive Controller ◽  
Control Law ◽  
Continuous Systems ◽  
Control Schemes ◽  
Closed Systems ◽  
Simulation Results

A design method of LS-SVM based stable adaptive controller is proposed for a class of nonlinear continuous systems with unknown nonlinear function in this paper. Due to the fact that the control law is derived based on the Lyapunov stability theory, the scheme can not only solve the tracking problem of this class of nonlinear systems, but also it can guarantee the asymptotic stability of the closed systems, which is superior to many LS-SVM based control schemes. The effectiveness of the proposed scheme is demonstrated by simulation results.

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 ANÁLISE EM MALHA FECHADA DO CONTROLADOR GENERALIZED PREDICTIVE CONTROL (GPC)

2009 ◽  
Vol 3 ◽  
pp. 119 ◽  
Author(s):  
Anderson Luiz Cavalcanti
Keyword(s):  
Stability Analysis ◽  
Predictive Control ◽  
Robust Stability ◽  
Closed Loop ◽  
Generalized Predictive Control ◽  
Loop Analysis ◽  
Closed Loop Systems ◽  
Robust Stability Analysis ◽  
Predictive Controller ◽  
Simulation Results

RESUMO O presente trabalho tem o objetivo de apresentar uma análise em malha fechada do controlador Generalized Predictive Control (GPC). Esta análise visa observar, com detalhes, as características deste tipo de controlador. Os detalhes apresentados são de extrema importância na análise de estabilidade robusta. Alguns resultados de simulação são apresentados. PALAVRAS-CHAVE: Controle preditivo, sistemas em malha fechada. CLOSED-LOOP ANALYSIS OF GENERALIZED PREDICTIVE CONTROL (GPC) ABSTRACT This paper presents a closed loop analysys of Generalized Predictive Control GPC. This analysis observes, in details, the features of this kind of predictive controller The details showed are very important in robust stability analysis. Simulation results are shown. KEY-WORDS: Predictive control, closed-loop systems.

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.

Simulation Study on Feed Rate Optimization Technique Based on Generalized Predictive Control

2013 ◽  
Vol 572 ◽  
pp. 555-558
Author(s):  
Xia Li ◽  
Hong Bin Liang ◽  
Shu Zhi Zhang
Keyword(s):  
Predictive Control ◽  
Feed Rate ◽  
Optimization Technique ◽  
Adaptive Controller ◽  
Open Architecture ◽  
Generalized Predictive Control ◽  
Software Modules ◽  
Rate Optimization ◽  
Cnc Controller ◽  
Feed Rate Optimization

Optimization is an important way to improve the machining quality, efficiency, security and safety. In traditional way, feed rate is specified off-line in CAM system by process planner, which leads to the low machining efficiency. In the paper feed rate optimization technique based on generalized predictive control is researched. The open architecture is adopted to develop an adaptive controller, where the feed rate can be real-time adjusted in CNC system according to the measured cutting force. An open CNC controller with the function of feed rate optimization is implemented, which consists of a series of software modules. Simulation experiment has been finished to prove the proposed method.

Model Predictive Control of a Differential-Drive Mobile Robot

2018 ◽  
Vol 10 (1) ◽  
pp. 20-41
Author(s):  
Samir Bouzoualegh ◽  
El-Hadi Guechi ◽  
Ridha Kelaiaia
Keyword(s):  
Mathematical Model ◽  
Model Predictive Control ◽  
Mobile Robot ◽  
Predictive Control ◽  
Control Law ◽  
Input Output ◽  
Linearization Technique ◽  
Differential Drive ◽  
Predictive Controller ◽  
Simulation Results

Abstract This paper presents a model predictive control (MPC) for a differential-drive mobile robot (DDMR) based on the dynamic model. The robot’s mathematical model is nonlinear, which is why an input–output linearization technique is used, and, based on the obtained linear model, an MPC was developed. The predictive control law gains were acquired by minimizing a quadratic criterion. In addition, to enable better tuning of the obtained predictive controller gains, torques and settling time graphs were used. To show the efficiency of the proposed approach, some simulation results are provided.

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