Constrained model predictive control for an induction heating load

Nawaz, Muhammad; Saqib, Muhammad Asghar; Kashif, Syed Abdul Rahman; Gul, Mehreen

doi:10.1177/0142331218758887

Cited by 9 publications

(9 citation statements)

References 33 publications

(41 reference statements)

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“…However, considering IH applications, little research or industrial applications have been yet described. In [16], a furnace control is proposed and compared with current state-of-the-art alternatives, highlighting benefits of MPC, and an IH furnace with a parallel-resonant load and unity input power factor is described in [17]. In [18], Laguerre functions are applied in order to obtain a less demanding computational complexity.…”

Section: Mpc For Induction Heating Systemsmentioning

confidence: 99%

Development of new high-performance induction heating systems using model predictive control1

Lucia

Navarro

Sarnago

et al. 2020

JAE

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Modern induction heating systems involve usually many non-linear systems with different constraints, making difficult implementing classical controllers. In this context, model predictive control arises as a powerful technique able to provide high performance controllers with advanced functionalities. This paper will discuss the benefits of this control technique for induction heating systems and will provide an example of application for domestic systems. As a conclusion, MPC will help powering future induction heating systems with improved control capabilities and performance.

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Section: Mpc For Induction Heating Systemsmentioning

confidence: 99%

Development of new high-performance induction heating systems using model predictive control1

Lucia

Navarro

Sarnago

et al. 2020

JAE

View full text Add to dashboard Cite

show abstract

“…Different sequence of events of disturbance can be used to test the performance of a VSC -MTDC system. Optimal performance of a system requires best control scheme with optimized parameters of controllers [9], [10]. Some papers addressed the parameters optimization of proportional-integral (PI) DC voltage controllers [11], [12].…”

Section: Introductionmentioning

confidence: 99%

Controller Parameters Optimization for Multi-Terminal DC Power System Using Ant Colony Optimization

et al. 2021

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Voltage source converter based multi -terminal DC grids (VSC -MTDC) are widely used for integration of renewable resources. Control of these grids requires vector control method, which includes inner and outer current controllers, tuning of these controllers is very important. Conventionally used tuning methods consider approximated linear model to tune the proportional -integral (PI) parameters of voltage source converter (VSC) which fails to produce optimum disturbance rejection results. In this research an Ant Colony Optimization (ACO) technique is used to get the optimum parameters of inner and outer power control layers for multi -terminal DC system. ACO is applied simultaneously on inner and outer control layers and results are compared with classical tuning method and well established meta -herustic technique, Particle Swarm Optimization (PSO) using MATLAB software. Dynamic models of VSC -MTDC are developed in PSCAD/EMTDC to exalt the qualities of the presented tuning method. In this paper, a four terminal VSC -MTDC has been used under different sequence of events of disturbances e.g. load change on AC side, active power reference change for inverter and rectifier mode and disconnection of one terminal to evaluate the robustness of ACO algorithm with respect to classical method. The proposed tuning method gives superior results under different disturbance compared to conventional method.

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“…It determines that the lack of intelligence PID control is difficult to apply in the lining induction heating system. In recent years, it is based on model prediction [4,5] and the intelligent adjustment method based on PID has good control effects, solving this problem, but predictive control requires a large number of samples to ensure accuracy, which is difficult. In fact, as a method of intelligent tuning PID parameters, fuzzy control is efficient.…”

Section: Introductionmentioning

confidence: 99%

Research on Variable Universe Fuzzy PID Control Strategy of Pipe Lining Induction Heating System

Wang

Wei

et al. 2020

Modelling and Simulation in Engineering

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It is a promising heat supply strategy to use induction heating for the pipe lining process, but temperature control is hindering its application. In this study, we designed the variable universe fuzzy PID controller, and the lining induction heating system model was used to verify its performance. First, the transfer function parameters of the lining induction heating system are obtained by the step response method. Then, a point-by-point convergent interpolator is established through the contraction-expansion factors to realize the adaptive expansion of the fuzzy universe. Finally, the performance of PID, fuzzy PID, and variable universe fuzzy PID are compared through simulation experiments, and the ability of the controller to resist disturbance is verified by adding interference. The results show that the variable universe fuzzy PID controller can greatly improve the performance of fuzzy PID in response speed and settle time. The average stability error is smaller than PID and fuzzy PID control. It can meet the speed and accuracy requirements of the lining induction heating system. This research can be used as a reference for induction heating precise control and evidence that the variable universe fuzzy PID control can satisfy the lining induction heating process.

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Constrained model predictive control for an induction heating load

Cited by 9 publications

References 33 publications

Development of new high-performance induction heating systems using model predictive control1

Development of new high-performance induction heating systems using model predictive control1

Controller Parameters Optimization for Multi-Terminal DC Power System Using Ant Colony Optimization

Research on Variable Universe Fuzzy PID Control Strategy of Pipe Lining Induction Heating System

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