scholarly journals OPTIMAL TUNING OF FRACTIONAL ORDER CONTROLLER USING WOUND HEALING ALGORITHM BASED ON CLONAL SELECTION PRINCIPLE

Author(s):  
Mehmet Çinar ◽  

Fractional-order PID (FOPID) controller is a generalization of standard PID controller using fractional calculus. Compared to PID controller, the tuning of FOPID is more complex and remains a challenge problem. This paper focuses on the design of FOPID controller using wound healing algorithm (WHA) based on clonal selection principle. The tuning of FOPID controller is formulated as a nonlinear optimization problem, in which the objective function is composed of overshoot, steady-state error, raising time and settling time. WHA algorithm, a newly developed evolutionary algorithm inspired by human immune system, is used as the optimizer to search the best parameters of FOPID controller. The designed WHA-FOPID controller is applied to various systems. Numerous numerical simulations and comparisons with other FOPID/PID controllers show that the WHA-FOPID controller can not only ensure good control performance with respect to reference input but also improve the system robustness with respect to model uncertainties.

2014 ◽  
Vol 716-717 ◽  
pp. 1620-1623
Author(s):  
Peng Zhang ◽  
Ping Li ◽  
Qing Rui Li

A new training method is proposed, which could solve the problem of that parameters of fractional order controller are not easy to be selected. This method which based on the principle of gravity optimizes parameters. Random initial parameter based on step was set as coordinate form which in the midpoint of the multidimensional space. The error between the actual output and the target output was set as radius. This method had advantages which could not need to calculate the gradient and could randomly select initial. Through the simulation experiment, this method is successfully applied in the fractional order PID controller, which obtains the optimal parameters.


Author(s):  
Mehmet Çinar

Control strategies for uncertainties or nonlinear effects need to be developed for control systems. Optimization algorithms developed with the rapid development of computer technology are frequently used to improve the steady-state response with the help of the ambiguous mathematical characteristics or nonlinearity of control systems. In this study, an optimum proportional–integral–derivative (PID) controller was designed using the wound healing algorithm based on the clonal selection principle. The proposed algorithm is applied in self-tuning a PID controller in the ball and hoop system which represents a system of complex industrial processes. In order to adjust the PID parameters with the aid of the developed algorithm, an integral absolute error (IAE) has been chosen as the objective function. Thus, the system reached the optimum solution quickly and time was saved. The advantages of the proposed algorithm have been proved by comparing the obtained results with other algorithms. To succeed this, a programme was written in the MATLAB GUI environment.


2021 ◽  
Vol 11 (15) ◽  
pp. 6693
Author(s):  
Sagar Gupta ◽  
Abhaya Pal Singh ◽  
Dipankar Deb ◽  
Stepan Ozana

Robotic manipulators have been widely used in industries, mainly to move tools into different specific positions. Thus, it has become necessary to have accurate knowledge about the tool position using forward kinematics after accessing the angular locations of limbs. This paper presents a simulation study in which an encoder attached to the limbs gathers information about the angular positions. The measured angles are applied to the Kalman Filter (KF) and its variants for state estimation. This work focuses on the use of fractional order controllers with a Two Degree of Freedom Serial Flexible Links (2DSFL) and Two Degree of Freedom Serial Flexible Joint (2DSFJ) and undertakes simulations with noise and a square wave as input. The fractional order controllers fit better with the system properties than integer order controllers. The KF and its variants use an unknown and assumed process and measurement noise matrices to predict the actual data. An optimisation problem is proposed to achieve reasonable estimations with the updated covariance matrices.


2021 ◽  
Vol 4 (3) ◽  
pp. 50
Author(s):  
Preeti Warrier ◽  
Pritesh Shah

The control of power converters is difficult due to their non-linear nature and, hence, the quest for smart and efficient controllers is continuous and ongoing. Fractional-order controllers have demonstrated superior performance in power electronic systems in recent years. However, it is a challenge to attain optimal parameters of the fractional-order controller for such types of systems. This article describes the optimal design of a fractional order PID (FOPID) controller for a buck converter using the cohort intelligence (CI) optimization approach. The CI is an artificial intelligence-based socio-inspired meta-heuristic algorithm, which has been inspired by the behavior of a group of candidates called a cohort. The FOPID controller parameters are designed for the minimization of various performance indices, with more emphasis on the integral squared error (ISE) performance index. The FOPID controller shows faster transient and dynamic response characteristics in comparison to the conventional PID controller. Comparison of the proposed method with different optimization techniques like the GA, PSO, ABC, and SA shows good results in lesser computational time. Hence the CI method can be effectively used for the optimal tuning of FOPID controllers, as it gives comparable results to other optimization algorithms at a much faster rate. Such controllers can be optimized for multiple objectives and used in the control of various power converters giving rise to more efficient systems catering to the Industry 4.0 standards.


2009 ◽  
Author(s):  
Bijoy K. Mukherjee ◽  
Santanu Metia ◽  
Sio-Iong Ao ◽  
Alan Hoi-Shou Chan ◽  
Hideki Katagiri ◽  
...  

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