Nonlinear Generalized Predictive Control Approach for Challenging Processes

2009 ◽  
Author(s):  
Ma’moun Abu-Ayyad ◽  
Lakshamirinyan Chinta Venkateswararao ◽  
Rickey Dubay
Keyword(s):  
Predictive Control ◽  
Control Strategies ◽  
Temperature Control System ◽  
Generalized Predictive Control ◽  
Original Structure ◽  
Real Time Control ◽  
Steel Cylinder ◽  
Control Approach ◽  
Dynamic Matrix ◽  
Sampling Instant

This paper presents the implementation of the fundamental concept of the infinite modeling methodology to the generalized predictive control (GPC) algorithm. This method was termed as infinite modeling generalized predictive control (IMGPC) which uses the nonlinear characteristics of the process such as the process gain and time constant to recalculate the dynamic matrix every sampling instant. Computer simulations were performed on nonlinear plants with different degrees of nonlinearity demonstrating that the infinite modeling approach is readily implemented providing improved control performance comparing to the original structure of GPC. Practical work included real-time control application on a steel cylinder temperature control system. Simulation and experimental results demonstrate that the methodology of infinite modeling is applicable to other advanced control strategies making the methodology generic.

A New Adaptive Generalized Predictive Control Algorithm for Nonlinear Processes

2010 ◽  
Author(s):  
Ma’moun Abu-Ayyad ◽  
Rickey Dubay ◽  
Bambang Pramujati
Keyword(s):  
Predictive Control ◽  
Closed Loop ◽  
Control Strategies ◽  
Temperature Control System ◽  
Generalized Predictive Control ◽  
Steel Cylinder ◽  
Unique Method ◽  
Predictive Controller ◽  
Process Prediction ◽  
Sampling Instant

This paper presents a unique method for improving the performance of the generalized predictive control (GPC) algorithm for controlling nonlinear systems. This method is termed adaptive generalized predictive control which uses a multi-dimensional surface of the nonlinear plant to recalculate the controller parameters every sampling instant. This results in a more accurate process prediction and improved closed-loop performance over the original GPC algorithm. The adaptive generalized predictive controller was tested in simulation and its control performance compared to GPC on several nonlinear plants with different degrees of nonlinearity. Practical testing and comparisons were performed on a steel cylinder temperature control system. Simulation and experimental results both demonstrate that the adaptive generalized predictive controller demonstrated improved closed-loop performance. The formulation of the nonlinear surface provides the mechanism for the adaptive approach to be readily applied to other advanced control strategies making the methodology generic.

scholarly journals A Predictive Control Strategy for Energy Management in Micro-Grid Systems

Electronics ◽  
2021 ◽  
Vol 10 (14) ◽  
pp. 1666
Author(s):  
Abdellatif Elmouatamid ◽  
Radouane Ouladsine ◽  
Mohamed Bakhouya ◽  
Najib El kamoun ◽  
Khalid Zine-Dine
Keyword(s):  
Energy Storage ◽  
Energy Management ◽  
Predictive Control ◽  
Energy Production ◽  
Storage Systems ◽  
Control Strategies ◽  
Renewable Energy Sources ◽  
Energy Storage Systems ◽  
Control Approach ◽  
Variable Nature

The integration of renewable energy sources (RES) was amplified, during the past decades, in order to tackle the challenges related to energy demands and CO2 increases. Recently, many initiatives have been taken by promoting the deployment and the usage of micro-grids (MG) in buildings, as decentralized systems, for energy production. However, the variable nature of RESs and the limited size of energy storage systems require the deployment of adaptive control strategies for efficient energy balance. In this paper, a generalized predictive control (GPC) strategy is introduced for energy management (EM) in MG systems. Its main objective is to efficiently connect the electricity generators and consumers in order to predict the most suitable actions for energy flow management. In fact, based on energy production and consumption profiles as well as the availability of energy storage systems, the proposed EM will be able to select the best suitable energy source for supplying the building’s loads. It will efficiently manage the usage of energy storage and the utility grid while maximizing RESs power generation. Simulations have been conducted, using real-sitting scenarios, and results are presented to validate the proposed predictive control approach by showing its effectiveness for MG systems control.

ON MODEL PREDICTIVE CONTROL OF QUASI-RESONANT CONVERTERS

2009 ◽  
Vol 18 (07) ◽  
pp. 1167-1183 ◽  
Author(s):  
FARZAD TAHAMI ◽  
MEHDI EBAD
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Linear Models ◽  
Control Strategies ◽  
Sampling Interval ◽  
Control Synthesis ◽  
Resonant Converters ◽  
Control Input ◽  
Model Approximation ◽  
Dynamic Matrix

In this paper, different model predictive control synthesis frameworks are examined for DC–DC quasi-resonant converters in order to achieve stability and desired performance. The performances of model predictive control strategies which make use of different forms of linearized models are compared. These linear models are ranging from a simple fixed model, linearized about a reference steady state to a weighted sum of different local models called multi model predictive control. A more complicated choice is represented by the extended dynamic matrix control in which the control input is determined based on the local linear model approximation of the system that is updated during each sampling interval, by making use of a nonlinear model. In this paper, by using and comparing these methods, a new control scheme for quasi-resonant converters is described. The proposed control strategy is applied to a typical half-wave zero-current switching QRC. Simulation results show an excellent transient response and a good tracking for a wide operating range and uncertainties in modeling.

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.

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.

scholarly journals A Deep-Sea Pipeline Skin Effect Electric Heat Tracing System

Energies ◽  
2019 ◽  
Vol 12 (13) ◽  
pp. 2466 ◽  
Author(s):  
Ding ◽  
Zhang ◽  
Lin
Keyword(s):  
Predictive Control ◽  
Control Strategy ◽  
Control Algorithm ◽  
Skin Effect ◽  
Distribution Model ◽  
Temperature Control System ◽  
Generalized Predictive Control ◽  
Oil Pipeline ◽  
Power Frequency ◽  
Electric Heat

In order to ensure deep-water flowline safety, this paper combined the axial temperature distribution model of the submarine pipeline and the distributed parameter circuit model of the skin effect electric heat tracing system; such work is conducive to proving that the heating effect of the skin effect electric heat tracing system depends on the distributed circuit parameters and power frequency of the system. Due to the complexity of the power supply device, the frequency cannot be increased indefinitely. Therefore, for the case that the input of the skin electric heat tracing system is constrained, a generalized predictive control algorithm introducing the input softening factor is proposed, and the constrained generalized predictive control strategy is applied to the electric heating temperature control system of the submarine oil pipeline. Simulation results demonstrated that the control quantity of the skin effect electric heat tracing system is effectively controlled within a constraint range, and also the values of heating power and power frequency are obtained by theoretical calculations rather than empirical estimations. Moreover, compared with the conventional control algorithm, the proposed constrained generalized predictive algorithm unfolds more significant dynamic response and better adaptive adjustment ability, which verifies the feasibility of the proposed control strategy.

Diameter regulation of an optical fiber using a generalized predictive control approach

1999 ◽  
Vol 32 (2) ◽  
pp. 8793-8797
Author(s):  
Philippe Dorléans ◽  
Olivier Gehan ◽  
Eric Pigeon ◽  
Mohammed M'Saad ◽  
M. Hertz ◽  
...  
Keyword(s):  
Optical Fiber ◽  
Predictive Control ◽  
Generalized Predictive Control ◽  
Control Approach
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