An improved constrained predictive functional control for industrial processes: A chamber pressure process study

Wu, Shan; Zou, Hongbo

doi:10.1177/0020294019881739

Cited by 4 publications

(3 citation statements)

References 37 publications

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“…The predictive functional control (PFC) algorithm, as the third generation of the MPC control algorithm, differs from the traditional MPC algorithm in that it is a structured control input [23]. It introduces the concept of basis function, and its output response can be obtained through offline calculation in advance, thereby reducing the workload of the computer that needs to be solved online and improving work efficiency.…”

Section: Robust Model Predictive Control With Integral Actionmentioning

confidence: 99%

Application of Feedforward Cascade Compound Control Based on Improved Predictive Functional Control in Heat Exchanger Outlet Temperature System

Miao

2023

Applied Sciences

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Aiming at the problems of large delay and poor anti-disturbance ability in the outlet temperature control system of the heat exchanger to optimize the control accuracy of the system and improve the control performance, this paper proposes a control scheme combining predictive functional control with proportional-integral-derivative control. Using the incremental proportional-integral-derivative control algorithm to improve the optimization objective function of the predictive functional control algorithm, a predictive functional control optimization model with a proportional-integral-derivative structure is established. The feedforward compensation control is adopted to eliminate the influence of external disturbances on the heat exchanger temperature control system. Through simulation, the proposed control scheme is compared with the feedforward cascade compound control scheme based on a proportional-integral-derivative main controller. The results show that the scheme has a small over harmonic and strong anti-interference ability. The adaptability and stability of the system are significantly improved, and the exit temperature of the heat exchanger can be effectively controlled.

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Section: Robust Model Predictive Control With Integral Actionmentioning

confidence: 99%

Application of Feedforward Cascade Compound Control Based on Improved Predictive Functional Control in Heat Exchanger Outlet Temperature System

Miao

2023

Applied Sciences

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“…In (19), A c = A + BS L + BS y C. Based on assumption (A.1) in Section 2.2, it is obvious that the elements of the C vector are bounded. The A matrix and B vector of the model are time-invariant.…”

Section: Stability Analysismentioning

confidence: 99%

“…PFC is convenient for fast processes and nonlinear systems [15,18]. Many applications of PFC have been reported in recent years in industrial processes [19][20][21][22].…”

Section: Introductionmentioning

confidence: 99%

Adaptive Predictive Functional Control of X-Y Pedestal for LEO Satellite Tracking Using Laguerre Functions

Tehrani¹,

Givi

Cican

2021

Applied Sciences

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In this paper, Predictive Functional Control (PFC) is used for X-Y pedestal control for LEO satellite tracking. According to the nonlinear characteristics of the X-Y pedestal and pedestal model variation caused by its operating point change, the use of system identification algorithm, which is based on special types of orthonormal functions known as Laguerre functions, is presented. This algorithm is combined with PFC to obtain a novel adaptive control algorithm entitled Adaptive Predictive Functional Control (APFC). In this combination, Laguerre functions are utilized for system identification, while the PFC is the control law. An interesting feature of the proposed algorithm is its desirable performance against the interference effect of channel X and channel Y. The proposed APFC algorithm is compared with Proportional Integral Derivative (PID) controller using simulation results. The results confirm that the proposed controller improves the performance in terms of the pedestal model variations; that is, the controller is capable of adapting to the model changes desirably.

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Predictive functional control for chamber pressure: A quantum simultaneous whale optimization approach

Ghadiri,

Khodadadi

2024

Transactions of the Institute of Measurement and Control

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This study introduces a Constrained Predictive Functional Controller (CPFC) designed for regulating chamber pressure in a coke furnace. While the traditional controllers face challenges posed by the system’s complex multi-input multi-output (MIMO) structure, cross-coupling, time delays, physical constraints, and uncertainties, this article’s approach realized set-point tracking and disturbance rejection, addressing model mismatches while considering constraints on system inputs, input variations, and outputs. To tackle the constrained Model Predictive Control (MPC) optimization problem and minimize the cost function, the Quantum Simultaneous Whale Optimization Algorithm (QSWOA) is employed. This meta-heuristic optimization method integrates quantum coding and simultaneous search with the whale optimization algorithm, enhancing convergence speed and precision. Furthermore, the performance of the proposed CPFC-QSWOA controller is assessed through simulations of the chamber pressure control of a Coke furnace. Results demonstrate the superiority of the CPFC-QSWOA approach, showcasing high precision and robustness, particularly in the face of uncertainties and disturbances.

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An improved constrained predictive functional control for industrial processes: A chamber pressure process study

Cited by 4 publications

References 37 publications

Application of Feedforward Cascade Compound Control Based on Improved Predictive Functional Control in Heat Exchanger Outlet Temperature System

Application of Feedforward Cascade Compound Control Based on Improved Predictive Functional Control in Heat Exchanger Outlet Temperature System

Adaptive Predictive Functional Control of X-Y Pedestal for LEO Satellite Tracking Using Laguerre Functions

Predictive functional control for chamber pressure: A quantum simultaneous whale optimization approach

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