Optimal tuning of a PID controller using a wound healing algorithm based on the clonal selection principle

2021 ◽  
pp. 014233122110646
Author(s):  
Mehmet Çinar
Keyword(s):  
Wound Healing ◽  
Control Systems ◽  
Pid Controller ◽  
Clonal Selection ◽  
Control Strategies ◽  
Rapid Development ◽  
Nonlinear Effects ◽  
Absolute Error ◽  
Selection Principle ◽  
Optimum Solution

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.

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

2021 ◽  
Vol 15 (1) ◽  
pp. 31-51
Author(s):  
Mehmet Çinar ◽  
Keyword(s):  
Wound Healing ◽  
Fractional Order ◽  
Pid Controller ◽  
Clonal Selection ◽  
Good Control ◽  
Human Immune System ◽  
Selection Principle ◽  
System Robustness ◽  
Fractional Order Controller ◽  
Fractional Order Pid

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.

scholarly journals Control Strategies for Thermal Processes in Chemical Industry

Proceedings ◽  
2020 ◽  
Vol 63 (1) ◽  
pp. 34
Author(s):  
Mircea Dulău
Keyword(s):  
Pid Controller ◽  
Internal Model ◽  
Control Strategies ◽  
Absolute Error ◽  
Economic Conditions ◽  
Saturated Steam ◽  
Industrial Processes ◽  
Thermal Processes ◽  
Proportional Integral Derivative ◽  
Current Context

In the current context, the control of the industrial processes continues to be very important, due to the rapid modification of the economic conditions, the development of production and the tightening of environmental and safety conditions. This paper presents the technological scheme for obtaining the saturated steam from superheated steam and proposes Proportional–Integral-Derivative (PID) controller options based on an internal model, Integral of Time Multiplied by Absolute Error (ITAE) criterion and Ziegler–Nichols criterion. The simulation tests are performed using the Matlab software.

scholarly journals Adaptive Tracking PID and FOPID Speed Control of an Elastically Attached Load Driven by a DC Motor at Almost Step Disturbance of Loading Torque and Parametric Excitation

2021 ◽  
Vol 11 (2) ◽  
pp. 679
Author(s):  
Paweł Olejnik ◽  
Paweł Adamski ◽  
Damian Batory ◽  
Jan Awrejcewicz
Keyword(s):  
Pid Controller ◽  
Closed Loop ◽  
Control Method ◽  
Control Strategies ◽  
Absolute Error ◽  
System Response ◽  
Closed Loop Control ◽  
Loop Control ◽  
Adaptive Tracking Control ◽  
Adaptive Tracking

Adaptive tracking control of the speed of a very elastically attached circular load driven by a direct current motor accompanied with an adaptive conventional and a fractional-order Proportional Integral Derivative (PID) controller is studied. It refers to improving the closed-loop control system response of elastically coupled components of drivelines. The motor and the load mechatronic models and the block diagrams are constructed. Parameters of the PID controller in the model reference control are both constant, as well as vary in time. The adaptive control method is improved by the application of a new closed-loop control structure canceling error dynamics. A few competing control strategies are tested based on the application of two types low and high frequency stepwise increasing variations of loading torque and damping coefficient of motion. Moreover, the performance of the control strategies is verified by Integral Time-Weighted Absolute Error (ITAE) index, since their robustness is evaluated by applying a sine modulated triangle waves of selected electric parameters. Therefore, a dynamic forcing and parameter uncertainty is applied. Simulation results are compared for checking the proposed methods.

Design and application of an optimally tuned PID controller for DC motor speed regulation via a novel hybrid Lévy flight distribution and Nelder–Mead algorithm

2021 ◽  
pp. 014233122110196
Author(s):  
Davut Izci
Keyword(s):  
Pid Controller ◽  
Search Algorithm ◽  
Cuckoo Search ◽  
Absolute Error ◽  
Dc Motor ◽  
Cuckoo Search Algorithm ◽  
Lévy Flight ◽  
Motor Speed ◽  
Levy Flight ◽  
Speed Regulation

This paper deals with the design of an optimally performed proportional–integral–derivative (PID) controller utilized for speed control of a direct current (DC) motor. To do so, a novel hybrid algorithm was proposed which employs a recent metaheuristic approach, named Lévy flight distribution (LFD) algorithm, and a simplex search method known as Nelder–Mead (NM) algorithm. The proposed algorithm (LFDNM) combines both LFD and NM algorithms in such a way that the good explorative behaviour of LFD and excellent local search capability of NM help to form a novel hybridized version that is well balanced in terms of exploration and exploitation. The promise of the proposed structure was observed through employment of a DC motor with PID controller. Optimum values for PID gains were obtained with the aid of an integral of time multiplied absolute error objective function. To verify the effectiveness of the proposed algorithm, comparative simulations were carried out using cuckoo search algorithm, genetic algorithm and original LFD algorithm. The system behaviour was assessed through analysing the results for statistical and non-parametric tests, transient and frequency responses, robustness, load disturbance, energy and maximum control signals. The respective evaluations showed better performance of the proposed approach. In addition, the better performance of the proposed approach was also demonstrated through experimental verification. Further evaluation to demonstrate better capability was performed by comparing the LFDNM-based PID controller with other state-of-the-art algorithms-based PID controllers with the same system parameters, which have also confirmed the superiority of the proposed approach.

scholarly journals Quadratic Model-Based Dynamically Updated PID Control of CSTR System with Varying Parameters

Algorithms ◽  
2021 ◽  
Vol 14 (2) ◽  
pp. 31
Author(s):  
Dushko Stavrov ◽  
Gorjan Nadzinski ◽  
Stojche Deskovski ◽  
Mile Stankovski
Keyword(s):  
Pid Control ◽  
Pid Controller ◽  
Absolute Error ◽  
Error Model ◽  
Quadratic Model ◽  
Control Performance ◽  
Continuous Stirred Tank Reactor ◽  
Quadratic Error ◽  
Varying Parameters ◽  
Cstr System

In this paper, we discuss an improved version of the conventional PID (Proportional–Integral–Derivative) controller, the Dynamically Updated PID (DUPID) controller. The DUPID is a control solution which preserves the advantages of the PID controller and tends to improve them by introducing a quadratic error model in the PID control structure. The quadratic error model is constructed over a window of past error points. The objective is to use the model to give the conventional PID controller the awareness needed to battle the effects caused by the variation of the parameters. The quality of the predictions that the model is able to deliver depends on the appropriate selection of data used for its construction. In this regard, the paper discusses two algorithms, named 1D (one dimensional) and 2D (two dimensional) DUPID. Appropriate to their names, the former selects data based on one coordinate, whereas the latter selects the data based on two coordinates. Both these versions of the DUPID controller are compared to the conventional PID controller with respect to their capabilities of controlling a Continuous Stirred Tank Reactor (CSTR) system with varying parameters in three different scenarios. As a quantifying measure of the control performance, the integral of absolute error (IAE) metric is used. The results from the performed simulations indicated that the two versions of the DUPID controller improved the control performance of the conventional PID controller in all scenarios.

scholarly journals Optimization on Vehicle Routing Problem Based on Immune Clonal Selection Algorithm

2012 ◽  
Vol 6-7 ◽  
pp. 256-260
Author(s):  
Hai Hua Li ◽  
Zong Yan Xu ◽  
Fei Fei Zhou
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Clonal Selection ◽  
Solution Space ◽  
Genetic Mutation ◽  
Initial Population ◽  
Local Optimum ◽  
Clonal Selection Algorithm ◽  
Routing Problem ◽  
Optimum Solution

Vehicle routing problem is a typical NP-hard problem and is difficult to get an optimum solution. Aiming at the shortages of the existing methods, this paper proposed an algorithm based on immune clonal selection to solve vehicle routing problem. In the algorithm, expressed antibody with matrix, generated the initial population of antibodies randomly, and employed the operations such as clonal selection, genetic mutation iteratively to search optimum solution in solution space. The experimental results show that the algorithm presented here can converge to the global optimum solution rapidly, overcoming such disadvantages of the genetic algorithm as slower convergent velocity and the convergence to a local optimum solution.

A Control Strategy for Intelligent Stamp Forming Tooling

2011 ◽  
Vol 133 (6) ◽  
Author(s):  
William J. Emblom ◽  
Klaus J. Weinmann
Keyword(s):  
Fuzzy Logic ◽  
Control Systems ◽  
Control Strategy ◽  
Pid Controller ◽  
Closed Loop ◽  
Closed Loop Control ◽  
Linear Quadratic ◽  
Blank Holder ◽  
Loop Control ◽  
Stamp Forming

This paper describes the development and implementation of closed-loop control for oval stamp forming tooling using MATLAB®’s SIMULINK® and the dSPACE®CONTROLDESK®. A traditional PID controller was used for the blank holder pressure and an advanced controller utilizing fuzzy logic combining a linear quadratic gauss controller and a bang–bang controller was used to control draw bead position. The draw beads were used to control local forces near the draw beads. The blank holder pressures were used to control both wrinkling and local forces during forming. It was shown that a complex, advanced controller could be modeled using MATLAB’s SIMULINK and implemented in DSPACE CONTROLDESK. The resulting control systems for blank holder pressures and draw beads were used to control simultaneously local punch forces and wrinkling during the forming operation thereby resulting in a complex control strategy that could be used to improve the robustness of the stamp forming processes.

scholarly journals Optimal tuning of digital PID controller based on the Integration of Absolute Error.

1987 ◽  
Vol 13 (3) ◽  
pp. 370-372 ◽  
Author(s):  
Masao Imaeda ◽  
Si Chi Ma ◽  
Kyoji Hashimoto
Keyword(s):  
Pid Controller ◽  
Absolute Error ◽  
Optimal Tuning ◽  
Digital Pid

PSO and GA tuned conventional and fractional order PID controllers for quadrotor control

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Hasan Saribas ◽  
Sinem Kahvecioglu
Keyword(s):  
Fractional Order ◽  
Pid Controller ◽  
Controller Design ◽  
Optimization Problems ◽  
Parameter Tuning ◽  
Absolute Error ◽  
Cost Functions ◽  
Pid Controllers ◽  
Content Type ◽  
Quadrotor Control

Purpose This study aims to compare the performance of the conventional and fractional order proportional-integral-derivative (PID and FOPID) controllers tuned with a particle swarm optimization (PSO) and genetic algorithm (GA) for quadrotor control. Design/methodology/approach In this study, the gains of the controllers were tuned using PSO and GA, which are included in the heuristic optimization methods. The tuning processes of the controller’s gains were formulated as optimization problems. While generating the objective functions (cost functions), four different decision criteria were considered separately: integrated summation error (ISE), integrated absolute error, integrated time absolute error and integrated time summation error (ITSE). Findings According to the simulation results and comparison tables that were created, FOPID controllers tuned with PSO performed better performances than PID controllers. In addition, the ITSE criterion returned better results in control of all axes except for altitude control when compared to the other cost functions. In the control of altitude with the PID controller, the ISE criterion showed better performance. Originality/value While a conventional PID controller has three parameters (Kp, Ki, Kd) that need to be tuned, FOPID controllers have two additional parameters (µ). The inclusion of these two extra parameters means more flexibility in the controller design but much more complexity for parameter tuning. This study reveals the potential and effectiveness of PSO and GA in tuning the controller despite the increased number of parameters and complexity.

Control Systems for Automotive Vehicle Fuel Economy: A Literature Review

1981 ◽  
Vol 103 (3) ◽  
pp. 173-180 ◽  
Author(s):  
L. M. Sweet
Keyword(s):  
Control Systems ◽  
Combustion Engine ◽  
Control Strategies ◽  
Engine Performance ◽  
Type Systems ◽  
Open Loop ◽  
Feedback Systems ◽  
Fuel Flow ◽  
Loop Feedback ◽  
Hybrid Vehicle Control

This paper is a review of current research on applications of control systems and theory to achieve energy conservation in automotive vehicles. The development of internal combustion engine control systems that modulate fuel flow, air flow, ignition timing and duration, and exhaust gas recirculation is discussed. The relative advantages of physical and empirical models for engine performance are reviewed. Control strategies presented include optimized open-loop schedule type systems, closed-loop feedback systems, and adaptive controllers. The development of power train and hybrid vehicle control systems is presented, including controllers for both conventional transmissions and those employing flywheel energy storage.

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