A novel fractional order PID plus derivative (PIλDµDµ2) controller for AVR system using equilibrium optimizer

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Abdulsamed Tabak
Keyword(s):  
Fractional Order ◽  
Transient Response ◽  
Superior Performance ◽  
Control Performance ◽  
Proportional Integral Derivative ◽  
Content Type ◽  
Proportional Integral ◽  
Avr System ◽  
Optimization Parameters ◽  
Fractional Order Pid

Purpose The purpose of this paper is to improve transient response and dynamic performance of automatic voltage regulator (AVR). Design/methodology/approach This paper proposes a novel fractional order proportional–integral–derivative plus derivative (PIλDµDµ2) controller called FOPIDD for AVR system. The FOPIDD controller has seven optimization parameters and the equilibrium optimizer algorithm is used for tuning of controller parameters. The utilized objective function is widely preferred in AVR systems and consists of transient response characteristics. Findings In this study, results of AVR system controlled by FOPIDD is compared with results of proportional–integral–derivative (PID), proportional–integral–derivative acceleration, PID plus second order derivative and fractional order PID controllers. FOPIDD outperforms compared controllers in terms of transient response criteria such as settling time, rise time and overshoot. Then, the frequency domain analysis is performed for the AVR system with FOPIDD controller, and the results are found satisfactory. In addition, robustness test is realized for evaluating performance of FOPIDD controller in perturbed system parameters. In robustness test, FOPIDD controller shows superior control performance. Originality/value The FOPIDD controller is introduced for the first time to improve the control performance of the AVR system. The proposed FOPIDD controller has shown superior performance on AVR systems because of having seven optimization parameters and being fractional order based.

Robustness Study of Fractional Order PID Controller Optimized by Particle Swarm Optimization in AVR System

2016 ◽  
Vol 6 (5) ◽  
pp. 2033 ◽  
Author(s):  
N. Ramesh Raju ◽  
P. Linga Reddy
Keyword(s):  
Particle Swarm Optimization ◽  
Fractional Order ◽  
Pid Controller ◽  
Design Method ◽  
Particle Swarm ◽  
Superior Performance ◽  
Swarm Optimization ◽  
Modeling And Control ◽  
Avr System ◽  
Fractional Order Pid

<p>In this paper a novel design method for determining fractional order PID (PI<sup>λ</sup>D<sup>µ</sup>) controller parameters of an AVR system using particle swarm optimization algorithm is presented. This paper presents how to employ the particle swarm optimization to seek efficiently the optimal parameters of PI<sup>λ</sup>D<sup>µ</sup> controller. The robustness study is made for this controller against parameter variation of AVR system. This work has been simulated in MATLAB environment with FOMCON (Fractional Order Modeling and Control) tool box.The proposed PSOPI<sup>λ</sup>D<sup>µ</sup> controller has superior performance and robust compared to GA tuned PI<sup>λ</sup>D<sup>µ</sup> controller. The results are also compared with PSO tuned PID controller.</p>

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 Robustness Study of Fractional Order PID Controller Optimized by Particle Swarm Optimization in AVR System

2016 ◽  
Vol 6 (5) ◽  
pp. 2033
Author(s):  
N. Ramesh Raju ◽  
P. Linga Reddy
Keyword(s):  
Particle Swarm Optimization ◽  
Fractional Order ◽  
Pid Controller ◽  
Design Method ◽  
Particle Swarm ◽  
Superior Performance ◽  
Swarm Optimization ◽  
Modeling And Control ◽  
Avr System ◽  
Fractional Order Pid

<p>In this paper a novel design method for determining fractional order PID (PI<sup>λ</sup>D<sup>µ</sup>) controller parameters of an AVR system using particle swarm optimization algorithm is presented. This paper presents how to employ the particle swarm optimization to seek efficiently the optimal parameters of PI<sup>λ</sup>D<sup>µ</sup> controller. The robustness study is made for this controller against parameter variation of AVR system. This work has been simulated in MATLAB environment with FOMCON (Fractional Order Modeling and Control) tool box.The proposed PSOPI<sup>λ</sup>D<sup>µ</sup> controller has superior performance and robust compared to GA tuned PI<sup>λ</sup>D<sup>µ</sup> controller. The results are also compared with PSO tuned PID controller.</p>

Fractional PID Controller Applied to a Chemical Plant with Level and pH Control

2018 ◽  
Vol 13 (4) ◽  
Author(s):  
Renato Aparecido Aguiar ◽  
Ivan Carlos Franco ◽  
Fabrizio Leonardi ◽  
Fábio Lima
Keyword(s):  
Fractional Order ◽  
Pid Control ◽  
Pid Controller ◽  
Ph Control ◽  
Dynamic Responses ◽  
Control Performance ◽  
Proportional Integral Derivative ◽  
Control Effort ◽  
Multivariable Process ◽  
Fractional Order Pid

Abstract One of the most important processes in the chemical, biological and petrochemical industries is the control of the potential of hydrogen (pH). As it is a multivariable process and non-linear, pH control gives rise to many challenges for designers in both dynamic responses and robustness issues. Despite all this complexity, in many circumstances pH control is performed by using a conventional proportional integral derivative (PID) control, which is very common in industry. This paper proposes using a fractional-order PID to improve the pH control performance of a lab-scale process, as it is more flexible, i. e., there is a higher number of variables to be adjusted. Results from a simulation have been compared to those from both conventional and fractional-order PID controls, which has shown the better performance of the latter related to important metrics such as the control effort and dynamic response of the controlled variables.

Improved Jaya algorithm-based FOPID/PID for AVR system

2020 ◽  
Vol 39 (4) ◽  
pp. 775-790
Author(s):  
Jailsingh Bhookya ◽  
Ravi Kumar Jatoth
Keyword(s):  
Time Domain ◽  
Pid Controller ◽  
Controller Design ◽  
Optimal Controller ◽  
Jaya Algorithm ◽  
Proportional Integral Derivative ◽  
Content Type ◽  
Proportional Integral ◽  
Avr System ◽  
Pid Controller Design

Purpose This paper aims to get the optimal controller parameters of fractional order proportional integral derivative (FOPID)/proportional integral derivative (PID) i.e. Kp, Ki, Kd, λ and µ for designing controller in automatic voltage regulator (AVR) system. Design/methodology/approach A novel method is proposed to get the optimal controller parameters for designing controller in AVR system using improved Jaya algorithm (IJA). The time domain objective and regular integral error objectives are used to design the controller to estimate the performance of the AVR system based on optimal tuning FOPID/PID controller. Findings The proposed method captures time domain objective of the FOPID/PID controller design and demonstrates effective transient response and better control action. The efficient tuning of FOPID controller results in high superiority of control efforts. Practical implications The simulations of IJA-based FOPID/PID controller design method are performed in MatLab tool and compared with several methods in the recent state of the art and the same are observed to be robust for the AVR system. Originality/value The developed optimal FOPID/PID controller tuning using IJA optimization method is totally a new approach for the AVR system in the literature.

scholarly journals Performance Evaluation of Fractional Order Pid and Sliding Mode Control with Optimization Tuning Access

2019 ◽  
Vol 8 (2S8) ◽  
pp. 1448-1454
Keyword(s):  
Fractional Order ◽  
Pid Controller ◽  
World Economy ◽  
Sliding Mode ◽  
Proportional Integral Derivative ◽  
Robust Controller ◽  
The Past ◽  
Control Schemes ◽  
Different Types ◽  
Fractional Order Pid

The statistical analyses in the past showing the important properties of the electrohydraulic actuator (EHA) system, especially in the growth of the world economy. Dealing with the existing drawback in the EHA system, various types of control schemes have been introduced in the past. In this paper, to produce a more insightful view of the performance and the capabilities of the controller, three different types of controllers have been designed and compared. The favourite controller in the industry field, which is the proportional-integral-derivative (PID) controller will be first introduced. Follow by the improved PID controller, named Fractional Order (FO-PID) controller will be designed. Then, the prominent robust controller in the control field, called sliding mode controller (SMC) will be established. Instead of obtaining the controller’s parameters without any appropriate technique, the well-known tuning technique in computer science, named particle swarm optimization (PSO) will be utilized. Referring to the performances produced by these controllers, it can be concluded that the SMC is capable to generate most desired control performance that produced the highest accuracy with the smallest error in the analyses.

An active control for hydrostatic journal bearing using optimization algorithms

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Waheed Ur Rehman ◽  
Xinhua Wang ◽  
Yingchun Chen ◽  
Xiaogao Yang ◽  
Zia Ullah ◽  
...  
Keyword(s):  
Mathematical Model ◽  
Peer Review ◽  
Fractional Order ◽  
Journal Bearing ◽  
Optimization Techniques ◽  
Performance Criteria ◽  
Content Type ◽  
Control Techniques ◽  
Fractional Order Controller ◽  
Fractional Order Pid

Purpose The purpose of this paper is to improve static/dynamic characteristics of active-controlled hydrostatic journal bearing by using fractional order control techniques and optimizing algorithms. Design/methodology/approach Active lubrication has ability to overcome the unpredictable harsh environmental conditions which often lead to failure of capillary controlled traditional hydrostatic journal bearing. The research develops a mathematical model for a servo feedback-controlled hydrostatic journal bearing and dynamics of model is analyzed with different control techniques. The fractional-order PID control system is tuned by using particle swarm optimization and Nelder mead optimization techniques with the help of using multi-objective performance criteria. Findings The results of the current research are compared with previously published theoretical and experimental results. The proposed servo-controlled active bearing system is studied under a number of different dynamic situations and constraints of variable spindle speed, external load, temperature changes (viscosity) and variable bearing clearance (oil film thickness). The simulation results show that the proposed system has better performance in terms of controllability, faster response, stability, high stiffness and strong resistance. Originality/value This paper develops an accurate mathematical model for servo-controlled hydrostatic bearing with fractional order controller. The results are in excellent agreement with previously published literature. Peer review The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-07-2020-0272

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