scholarly journals PLC based fractional-order PID temperature control in pipeline: design procedure and experimental evaluation

Meccanica ◽  
2020 ◽  
Author(s):  
Jakub Możaryn ◽  
Jakub Petryszyn ◽  
Stepan Ozana
Keyword(s):  
Fractional Order ◽  
Temperature Control ◽  
Experimental Evaluation ◽  
Design Procedure ◽  
Fractional Order Pid ◽  
Pipeline Design

scholarly journals Fractional-Order PID and Active Disturbance Rejection Control with Tuning Parameter Optimization for Induction Heating

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Bingyu Li ◽  
Jining Guo ◽  
Ying Fu
Keyword(s):  
Fractional Order ◽  
Temperature Control ◽  
Induction Heating ◽  
Disturbance Rejection ◽  
Active Disturbance Rejection Control ◽  
Heating Systems ◽  
Active Disturbance Rejection ◽  
Disturbance Rejection Control ◽  
Fractional Order Pid ◽  
Control Accuracy

Induction heating systems are characterized by model uncertainty, nonlinearity, and external disturbances, and the control accuracy of the system directly affects the performance of the heated workpiece. In order to improve the temperature control accuracy and anti-interference performance of induction heating systems, this paper proposes a composite control strategy combining fractional-order PID (FOPID) and active disturbance rejection control (ADRC). Meanwhile, for the problem of too many controller tuning parameters, an improved quantum behavior particle swarm optimization (QPSO) algorithm is used to transform the nine parameters to be tuned in fractional-order PID active disturbance rejection control (FOPID-ADRC) into a minimization value optimization problem for solving. The simulation results show that the FOPID-ADRC controller improves the anti-interference capability and control accuracy of the temperature control system, and the improved QPSO algorithm has better global search capability and local optimal adaptation value.

Temperature Control of a Cutting Process Using Fractional Order Proportional-Integral-Derivative Controller

2011 ◽  
Vol 133 (5) ◽  
Author(s):  
Mahsan Tavakoli-Kakhki ◽  
Mohammad Haeri
Keyword(s):  
Fractional Order ◽  
Temperature Control ◽  
Reduction Method ◽  
Cutting Process ◽  
Specific Class ◽  
Proportional Integral Derivative ◽  
Proportional Integral Derivative Controller ◽  
Proportional Integral ◽  
The Stability ◽  
Fractional Order Pid

In this paper, the fractionalized differentiating method is implemented to reduce commensurate fractional order models complexity. The prominent properties of this method are its simplicity and guarantee of preserving the stability of a specific class of fractional order models in their reduced counterparts. The presented reduction method is employed in simplifying complicated fractional order controllers to a fractional order PID (FOPID) controller and proposing tuning rules for its parameters adjustment. Finally, the efficiency of the FOPID tuning rule obtained based on the proposed reduction method is shown in the temperature control of a cutting process.

scholarly journals General type industrial temperature system control based on fuzzy fractional-order PID controller

2021 ◽  
Author(s):  
Lu Liu ◽  
Dingyu Xue ◽  
Shuo Zhang
Keyword(s):  
Fractional Order ◽  
Temperature Control ◽  
Pid Controller ◽  
General Type ◽  
External Disturbance ◽  
Control Process ◽  
Temperature Control System ◽  
System Control ◽  
Fractional Order Pid ◽  
Fractional Order Pid Controller

AbstractA fuzzy fractional-order PID control algorithm for a general type industrial temperature control system is proposed in this paper. In order to improve the production quality and controlled model accuracy, a fractional-order elementary system is used to describe the temperature control process. The gain coefficients of the proposed fractional-order PID controller is updated online based on a set of fractional-order fuzzy rules which are defined by Mittag–Leffler functions and follow fat-tailed distributions. Therefore, the proposed controller parameters could be auto-tuned according to model uncertainties, noise disturbance, random delay, and etc. Examples of the studied temperature control systems are shown to verify the effectiveness of the proposed controller. The superiority of fractional calculus is fully explored in the presented control methodology. The controlled temperature profile with the proposed algorithm could realize more satisfactory dynamic performance, better robustness respect to environment changes caused by internal and external disturbance.

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