scholarly journals Fuzzy pH control of sugarcane juice for sugar production

2020 ◽  
Vol 9 (9) ◽  
pp. e13996321
Author(s):  
Manuel Ferreira Silva Neto ◽  
Antonio Manoel Batista da Silva ◽  
Edilberto Pereira Teixeira ◽  
Marcelo Lucas
Keyword(s):  
Steady State ◽  
Pid Controller ◽  
Ph Control ◽  
Pid Controllers ◽  
Control Methods ◽  
Nonlinear Characteristics ◽  
Fuzzy Controllers ◽  
Sugar Mills ◽  
Comparison Of The Results ◽  
State Error

A proposal to control the pH of the broth in sugar mills is presented in this work. Because it is a system with nonlinear characteristics and disturbances, the conventional control methods do not satisfy the usual requirements of the process. Among these conventional methods, we highlight the PID controller, which is basically linear. Extending the possibilities of action, the control proposal presented in this work proved to be quite satisfactory, by using fuzzy logic in a predictive way in the consideration of the effect of the disturbances in an intelligent way. The details of the proposed controller are presented, including some simulation results. The effectiveness of the proposed controller is illustrated by simulation, showing graphically the disturbances and the consequent control action, which eliminates the steady state error. The comparison of the results obtained with conventional PID controllers and the fuzzy controllers shows the predictive action of the fuzzy controllers allowing a significant reduction in the variability of the steady state error. In addition, this architecture can be modified to include other disturbances for other applications. Thus, the present proposal can be used in general to control non-linear and multivariable systems.

scholarly journals Adaptive neural PD controllers for mobile manipulator trajectory tracking

2021 ◽  
Vol 7 ◽  
pp. e393
Author(s):  
Jesus Hernandez-Barragan ◽  
Jorge D. Rios ◽  
Javier Gomez-Avila ◽  
Nancy Arana-Daniel ◽  
Carlos Lopez-Franco ◽  
...  
Keyword(s):  
Steady State ◽  
Pid Controller ◽  
Poor Performance ◽  
Industrial Applications ◽  
Mobile Manipulator ◽  
Pid Controllers ◽  
Mobile Manipulators ◽  
Pd Controller ◽  
Adaptive Neuron ◽  
State Error

Artificial intelligence techniques have been used in the industry to control complex systems; among these proposals, adaptive Proportional, Integrative, Derivative (PID) controllers are intelligent versions of the most used controller in the industry. This work presents an adaptive neuron PD controller and a multilayer neural PD controller for position tracking of a mobile manipulator. Both controllers are trained by an extended Kalman filter (EKF) algorithm. Neural networks trained with the EKF algorithm show faster learning speeds and convergence times than the training based on backpropagation. The integrative term in PID controllers eliminates the steady-state error, but it provokes oscillations and overshoot. Moreover, the cumulative error in the integral action may produce windup effects such as high settling time, poor performance, and instability. The proposed neural PD controllers adjust their gains dynamically, which eliminates the steady-state error. Then, the integrative term is not required, and oscillations and overshot are highly reduced. Removing the integral part also eliminates the need for anti-windup methodologies to deal with the windup effects. Mobile manipulators are popular due to their mobile capability combined with a dexterous manipulation capability, which gives them the potential for many industrial applications. Applicability of the proposed adaptive neural controllers is presented by simulating experimental results on a KUKA Youbot mobile manipulator, presenting different tests and comparisons with the conventional PID controller and an existing adaptive neuron PID controller.

Research on the Application of the Fuzzy Control Algrithm in the HAPC System

2012 ◽  
Vol 220-223 ◽  
pp. 157-160
Author(s):  
Jing Qing Ma ◽  
Hai Bo Chen
Keyword(s):  
Dynamic Response ◽  
Pid Controller ◽  
Position Control ◽  
Pid Controllers ◽  
Control Methods ◽  
Fuzzy Pid ◽  
Fuzzy Pid Controller ◽  
Main Factors ◽  
High Control ◽  
Control Accuracy

The HAPC(Hydraulic Automatic Position Control) requires quick dynamic response and high control accuracy. Based on the research of the HAPC system, I build the HAPC mathematical model, then design both the Conventional PID controller and fuzzy PID controllers, simulate the two control methods using the MATLAB software, analyze the main factors which influence the results. The simulation results show that the fuzzy PID controller has the better effect in the dynamic response and the control accuracy than the former.

scholarly journals Performance enhancement of split-phase induction motor by using fuzzy-based PID controller

2019 ◽  
Vol 70 (2) ◽  
pp. 103-112
Author(s):  
Mohamed I. Abdelwanis ◽  
Ragab A. El-Sehiemy
Keyword(s):  
Steady State ◽  
Induction Motor ◽  
Pid Controller ◽  
Pulse Width Modulation ◽  
Performance Enhancement ◽  
Fine Tuning ◽  
Motor Speed ◽  
Pumping System ◽  
Total Oscillation ◽  
State Error

Abstract This paper presents control and analysis of a split-phase induction motor (SPIM) to drive a centrifugal pumping system. An optimized proportional- integral and derivative (PID) controller, that is capable with a vector closed-loop split-phase induction motor control, is presented and its simulation results are discussed. The fine-tuning procedure is employed for fuzzy PID (FPID) controller parameters in order to sustain the motor speed at the predefined reference values. To assess the performance of the competitive controllers, conventional PID (CPID) and FPID, four operational indices for are suggested for measure the capability of the two controllers. These indices involve individual steady state error (ISSE) for each operating period, total steady state error (TSSE) for overall loading cycle, Individual oscillation index (IOI) and Total oscillation index (TOI), in order to measure the capability of the FPID compared with CPID. The performance of the SPIM accomplished with these performance indices is checked and tested on high and low speed levels. Pulse width modulation (PWM) based simulation studies were employed for SPIM using MATLAB/SIMULINK software. The results show that the overall performance of the SPIM operated with vector control that is tuned by FPID is enhanced compared with CPID.

scholarly journals Perancangan Pengendalian Kecepatan Motor Induksi Tiga Fasa Pada Mesin Sentrifugal Dengan Pendekatan Model Viteckova Orde Dua Menggunakan Metode Hybridfuzzy-SMC

2018 ◽  
Vol 15 (2) ◽  
pp. 138
Author(s):  
Ahmad Faizal
Keyword(s):  
Steady State ◽  
Induction Motor ◽  
Fuzzy Controller ◽  
Sliding Mode ◽  
Response Analysis ◽  
Transient Time ◽  
Fuzzy Controllers ◽  
Non Linear ◽  
Non Linear System ◽  
State Error

Induction motor has a weakness in the speed settings, the speed will change when there is a change in load or control signal disturbance, it takes a controller that is able to overcome the shortcomings of the induction motor, one of the controller is fuzzy. Fuzzy controllers have the advantage of modeling a complex non-linear function. But fuzzy controllers have weaknesses in the form of overshoot and system oscillation. One of the controllers that is able to overcome the weakness of overshoot and oscillation of the system from the fuzzy controller is the Sliding Mode Control (SMC) controller. SMC has the advantage of being robust and able to work on non-linear system systems that have model or parameter uncertainty. Based on simulation results from fuzzy hybrid controller and SMC able to cover the weakness of fuzzy and robust controller in overcoming the load and disturbance changes. Proven with time response analysis on overshoot and steady state error better than fuzzy controller with longer transient time value at maximum load with steady state error 0,0085 Rpm with Maximum overshoot 0,38% and without system oscillation. 

scholarly journals Experimental Verification of Lead-Lag Compensators on a Twin Rotor System

2018 ◽  
Vol 14 (2) ◽  
pp. 164-171
Author(s):  
Meryem Deniz ◽  
Enver Tatlicioglu ◽  
Alper Bayrak
Keyword(s):  
Steady State ◽  
Experimental Studies ◽  
Research Problem ◽  
Rotor System ◽  
Pid Controllers ◽  
Rotor Systems ◽  
Laboratory Setup ◽  
Nonlinear Controllers ◽  
Twin Rotor ◽  
State Error

AbstractTwin rotor system is a laboratory setup resembling a simplified helicopter model that moves along both horizontal and vertical axes. The literature on control of twin rotor systems reflects a good amount of research on designing PID controllers and their extensions considering several aspects, as well as onsome nonlinear controllers. However, there is almost no previous work on design of lag-lead type compensators for twin rotor systems. In this study, by considering this open research problem, lag and lead type compensators are designed and then experimentally verified on the twin rotor system. Specifically, first, lag and lag-lag compensators are designed to obtain a reduced steady state error as compared with proportional controllers. Secondly, lead compensation is discussed to obtain a reduced overshoot. Finally, lag-lead compensators are designed to make use of their favorable properties. All compensators are applied to the twin rotor system in our laboratory. From experimental studies, it was observed that steady state error was reduced when a lag compensator was used in conjunction with a lead compensator.

scholarly journals Objective functions modification of GA optimized PID controller for brushed DC motor

2020 ◽  
Vol 10 (3) ◽  
pp. 2426
Author(s):  
A.A.M. Zahir ◽  
Syed Sahal Nazli Alhady ◽  
A.A.A Wahab ◽  
M.F. Ahmad
Keyword(s):  
Steady State ◽  
Objective Function ◽  
Rise Time ◽  
Pid Controller ◽  
Optimization Method ◽  
Settling Time ◽  
Performance Parameter ◽  
Objective Functions ◽  
Performance Requirement ◽  
State Error

PID Optimization by Genetic Algorithm or any intelligent optimization method is widely being used recently. The main issue is to select a suitable objective function based on error criteria. Original error criteria that is widely being used such as ITAE, ISE, ITSE and IAE is insufficient in enhancing some of the performance parameter. Parameter such as settling time, rise time, percentage of overshoot, and steady state error is included in the objective function. Weightage is added into these parameters based on users’ performance requirement. Based on the results, modified error criteria show improvement in all performance parameter after being modified. All of the error criteria produce 0% overshoot, 29.51%-39.44% shorter rise time, 21.11%-42.98% better settling time, 10% to 53.76% reduction in steady state error. The performance of modified objective function in minimizing the error signal is reduced. It can be concluded that modification of objective function by adding performance parameter into consideration could improve the performance of rise time, settling time, overshoot percentage, and steady state error

scholarly journals Design and Implementation of PID, GA and Fuzzy logic Controllers for an Electrical Drive with Various Noise Disturbances

2020 ◽  
Vol 9 (3) ◽  
pp. 449-453
Keyword(s):  
Steady State ◽  
Pid Controller ◽  
Fitness Function ◽  
External Noise ◽  
Pid Controllers ◽  
Matlab Simulation ◽  
State Behavior ◽  
Intelligent Technique ◽  
Noise Disturbances ◽  
Transient And Steady State

It is a great challenge for human being to keep up the constant speed in drive when external Noise disturbances occur due to fluctuations of power supply. In order to avoid these issues, PID controllers are intended using predictable method such as Ziegler Nichols method. But finest level is not obtained in transient and steady state. During the MATLAB Simulation, the error is present transient and steady state behavior in conventional PID controllers. Hence it is necessary to design a PID controller with Novel intelligent technique for speed control of drive like fuzzy and Genetic Algorithm. It considers error as fitness function which is to be minimized using various GA operators such as mutation etc. The Drive will be operated with different external noises like sinusoidal noise, Saw tooth noise and Ramp noise and comparison between PID, GA and Fuzzy PID will be presented and their performances are studied.

scholarly journals Speed Control of DC Motor using PID Controller FED H-Bridge

2020 ◽  
Vol 9 (10) ◽  
pp. 274-282
Keyword(s):  
Steady State ◽  
Transient Response ◽  
Pid Controller ◽  
Dc Motor ◽  
Pi Controller ◽  
Pd Controller ◽  
Integral Controller ◽  
The Stability ◽  
Proportional Controller ◽  
State Error

In the present scenario, DC motor is widely used in industries. So, if DC motor is used for industrial purpose, the controlling is necessary. But there are various methods to control any system or plant such as via Proportional controller (P), Integral controller (I), Derivative controller (D), PI controller, PD controller, PID controller. Each controller is used on the basis of requirement. Proportional controller reduces the rise time, improves the steady state accuracy, and reduces the steady state error. But Integral controllers eliminate the steady state error but the process is too slow so it produces the worse transient response. Derivative controller improves the transient response, reduces the overshoots and improves the stability. So, for obtaining the accurate output of any plant, PID controller is best for many others. And for operating the DC motor in forward and backward both, H-bridge MOSFET is also used in this dissertation. Any other power electronics device is not suitable.

scholarly journals Chaos Algorithm versus Traditional and Optimal Approaches for Regulating Line Frequency of Steam Power System

2018 ◽  
Vol 14 (2) ◽  
pp. 120-126
Author(s):  
Ahmed Elhafez ◽  
Ali Yosuf
Keyword(s):  
Optimal Control ◽  
Steady State ◽  
Power System ◽  
Settling Time ◽  
Load Frequency Control ◽  
Pid Controllers ◽  
Frequency Error ◽  
Proportional Integral ◽  
State Frequency ◽  
State Error

Load Frequency Control (LFC) is a basic control strategy for proper operation of the power system. It ensures the ability of each generator in regulating its output power in such way to maintain system frequency and tie-line power of the interconnected system at prescribed levels. This article introduces comprehensive comparative study between Chaos Optimization Algorithm (COA) and optimal control approaches, such as Linear Quadratic Regulator (LQR), and Optimal Pole Shifting (OPS) regarding the tuning of LFC controller. The comparison is extended to the control approaches that result in zero steady-state frequency error such as Proportional Integral (PI) and Proportional Integral Derivative (PID) controllers. Ziegler-Nicholas method is widely adopted for tuning such controllers. The article then compares between PI and PID controllers tuned via Ziegler-Nicholas and COA. The optimal control approaches as LQR and OPS have the characteristic of steady-state error. Moreover, they require the access for full state variables. This limits their applicability. Whereas, Ziegler-Nicholas PI and PID controllers have relatively long settling time and high overshoot. The controllers tuned via COA remedy the defects of optimal and zero steady-state controllers. The performance adequacy of the proposed controllers is assessed for different operating scenarios. Matlab and its dynamic platform, Simulink, are used for stimulating the system under concern and the investigated control techniques. The simulation results revealed that COA results in the smallest settling time and overshoot compared with traditional controllers and zero steady-state error controllers. In the overshoot, COA produces around 80% less than LQR and 98.5% less than OPS, while in the settling time, COA produces around 81% less than LQR and 95% less than OPS. Moreover, COA produces the lowest steady-state frequency error. For Ziegler-Nicholas controllers, COA produces around 53% less in the overshoot and 42% less in the settling time.

scholarly journals PID Controller optimization using Metahuristic Controller with Different Nonlinearities

2021 ◽  
Vol 12 (2) ◽  
pp. 764-771
Author(s):  
G. Sundari, Et. al.
Keyword(s):  
Steady State ◽  
Pid Controller ◽  
Closed Loop ◽  
Error Function ◽  
Second Order ◽  
Settling Time ◽  
Order System ◽  
Pid Controllers ◽  
Dynamic Performances ◽  
Conventional Methods

This paper mainly explains the application of Metaherustic controller for tuning the parameter of PID controller. The minimization of error function has been done by improving the static and dynamic performances of the system like steady state error, Peak Overshoot, and Settling Time. This could be possible by means of applying metaherustic controller like GA in tuning the PID controllers under different Nonlinearities. The main intention of this paper is to support the specifications of PID controller at various Nonlinearities such as sinusoidal and saw tooth noise. The projected scheme derives the wonderful closed-loop response of second order system and then, it provides the effectiveness of the proposed method compared to the conventional methods.

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