scholarly journals A Proportional Integral Derivative (PID) Feedback Control without a Subsidiary Speed Loop

10.14311/973 ◽  
2008 ◽  
Vol 48 (3) ◽  
Author(s):  
M. Aboelhassan
Keyword(s):  
Steady State ◽  
Feedback Control ◽  
Direct Current ◽  
Pid Controller ◽  
Cutting Tool ◽  
Pid Controllers ◽  
Pd Controller ◽  
Bldc Motor ◽  
Proportional Integral Derivative ◽  
Frame Work

The aim of this investigation is to design and describe the essential features of a brushless direct-current (BLDC) motor. The static and dynamical state of the BLDC-Motor is designed and calculated.Within this frame-work, it has been shown that while working with the P-controller in conjunction with the subsidiary speed loop and PD-controller (with non-zero error in a steady state) without a subsidiary speed loop, there is PID-controller without a subsidiary speed loop which has zero error in a steady state. The last part of this paper is dedicated to a simulation of the circle rounds of P and PID controllers with and without a subsidiary speed loop in MATLAB–SIMULINK to decide which of these controllers is suitable, available and reliable with a BLDC-Motor and their application in cutting tool machines in general. 

scholarly journals Optimization of Proportional Integral Derivative Parameters of Brushless Direct Current Motor Using Genetic Algorithm

2020 ◽  
pp. 24-32
Author(s):  
Isaiah Adebayo ◽  
David Aborisade ◽  
Olugbemi Adetayo
Keyword(s):  
Genetic Algorithm ◽  
Direct Current ◽  
Pid Controller ◽  
Absolute Error ◽  
Dc Motor ◽  
Brushless Dc Motor ◽  
Bldc Motor ◽  
Proportional Integral Derivative ◽  
Proportional Integral ◽  
Brushless Dc

Optimal performance of the Brushless Direct Current (BLDC) motor is to be realized using an efficient Proportional Integral Derivative (PID) controller. However, conventional tuning technique fails to perform satisfactorily under parameter variations, nonlinear conditions and time delay. Also using conventional technique to tune the parameters gain of the PID controller is a difficult task. To overcome these difficulties, modern heuristic optimization technique are required to optimally tune the Proportional, Integral, Derivative of the controller for optimal speed control of three phase BLDC motor. Thus, genetic algorithm (GA) based PID controller was used to achieve a high dynamic control performance. The Brushless DC Motor mathematical equation which describes the voltage and corresponding rotational angular speed and torque of the brushless DC motor was employed using electrical DC Machines theorem. The Genetic algorithm was further analyzed by adopting the three common performance indices i.e. Integral Time Absolute Error (ITAE), Integral Square Error (ISE) and Integral Absolute Error (IAE) in order to capture and compare the most suitable BLDC Motor speed and torque control characteristics. All simulations were done using MATLAB (R2018a). The simulation result showed that the system with GA-PID controller had the better system response when compared with the existing technique of ZN-PID controller.

scholarly journals IMPLEMENTASI DAN ANALISIS KENDALI KECEPATAN MOTOR BLDC 1 kW MENGGUNAKAN ALGORITMA PID

JURNAL ELTEK ◽  
2019 ◽  
Vol 17 (2) ◽  
pp. 81
Author(s):  
Muchlis Dwi Ardiansyah ◽  
Fatkhur Rohman
Keyword(s):  
Steady State ◽  
Direct Current ◽  
Pid Control ◽  
Block Diagram ◽  
Bldc Motor ◽  
Trial And Error ◽  
Proportional Integral Derivative ◽  
Matlab Simulink ◽  
Proportional Integral ◽  
Parameter Values

Pemanfaatan teknologi alternatif dalam bidang otomotif maupun otomasi industri menggunakan motor Brushless Direct Current (BLDC) sudah banyak digunakan karena memiliki kelebihan dibanding dengan jenis mesin penggerak bertenaga elektrik lainnya. Namun motor BLDC masih memiliki beberapa kekurangan ketika menerima beban sehingga menyebabkan penurunan kecepatan putaran pada motor BLDC. Tujuan penelitian ini adalah untuk merancang dan mengaplikasikan sistem kendali kecepatan motor BLDC dengan kontrol Proportional Integral Derivative (PID) dan menentukan nilai parameter untuk mendapatkan persentase error steady state terkecil pada variasi  kecepatan dan beban motor BLDC. Metode pengambilan data diambil dengan cara memasukkan nilai parameter secara trial and error. Sebagai simulasi beban, motor BLDC dihubungkan dengan generator yang diberi beban berupa lampu yang divariasikan. Hasil pengujian mendapatkan pemodelan blok diagram PID dengan Matlab Simulink. Hasil parameter kontrol PID diperoleh nilai Kp = 1,5; Ki = 10,5 dan Kd = 0,04. Dengan nilai parameter tersebut motor BLDC dapat mempertahankan nilai set point dengan kestabilan yang tinggi (error steady state rendah).   The usage of alternative technology in the field of automotive and industrial automation using Brushless Direct Current (BLDC) has been widely used because it has advantages compared to other types of electric-powered drive engines. But the BLDC motor still has some disadvantages when receiving a load that causes a decrease in rotation speed on the BLDC motor. The purpose of the study is to design and apply a BLDC motor speed control system with a Proportional Integral Derivative (PID) control and determine the parameter value to obtain the smallest error steady state percentage at a speed variation and motor load the BLDC. The method of retrieving data was taken by entering parameter values by trial and error. As a load simulation, the BLDC motor was connected to a generator that was given the load in the form of a varied lamp. The test results gets the PID block diagram modeling with Matlab Simulink. The results of the PID control parameter are Kp = 1.5; Ki = 10.5 and Kd = 0.04. With these parameter values, the BLDC motor can maintain the setpoint value with high stability (low steady-state error).

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.

scholarly journals Position Tracking of ML System using CSA Based PID Controller

2019 ◽  
Vol 8 (11) ◽  
pp. 1956-1959
Keyword(s):  
Pid Controller ◽  
Magnetic Levitation ◽  
Search Algorithm ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Pid Controllers ◽  
Position Tracking ◽  
Proportional Integral Derivative ◽  
Proportional Integral ◽  
Simulation Results

The classical proportional integral derivative (PID) controllers are still use in various applications in industry. Magnetic levitation (ML) systems are rigidly nonlinear and sometimes unstable systems. Due to inbuilt nonlinearities of ML systems, tracking of position of ML Systems is still difficult. For the tracking purpose of position, PID controller parameters are found by choosing Cuckoo Search Algorithm (CSA) of optimization. The ranges of parameters are customized by z-n method of parameters. Simulation results show the tracking of position of ML systems using conventional and optimized parameters obtained with the CSA based controller.

Modelling and PID Control of a Quadrotor Aerial Robot

2014 ◽  
Vol 903 ◽  
pp. 327-331 ◽  
Author(s):  
Ismail Mohd Khairuddin ◽  
Anwar P.P.A. Majeed ◽  
Ann Lim ◽  
Jessnor Arif M. Jizat ◽  
Abdul Aziz Jaafar
Keyword(s):  
Pid Control ◽  
Pitch Angle ◽  
Pid Controller ◽  
Pd Controller ◽  
Proportional Integral Derivative ◽  
Hovering Flight ◽  
Proportional Integral ◽  
Aircraft Model ◽  
Aerial Robot ◽  
Aerial Vehicle

This paper elucidates the modeling of a + quadrotor configuration aerial vehicle and the design of its attitude and altitude controllers. The aircraft model consists of four fixed pitch angle propeller, each driven by an electric DC motor. The hovering flight of the quadrotor is governed by the Newton-Euler formulation. The attitude and altitude controls of the aircraft were regulated using heuristically tuned (Proportional-Integral-Derivative) PID controller. It was numerically simulated via Simulink that a PID controller was sufficient to bring the aircraft to the required altitude whereas the attitude of the vehicle is adequately controlled by a PD controller.

The Parameterization of All Plants Stabilized by Proportional Controller Formultiple-Input/Multiple-Output Plant

2011 ◽  
Vol 497 ◽  
pp. 246-254
Author(s):  
Takaaki Hagiwara ◽  
Kou Yamada ◽  
Satoshi Aoyama ◽  
An Chinh Hoang
Keyword(s):  
Pid Controller ◽  
Multiple Input Multiple Output ◽  
Pid Controllers ◽  
Proportional Integral Derivative ◽  
Proportional Integral ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Proportional Controller

In this paper, we examine the parameterization of all plants stabilized by a proportionalcontroller for multiple-input/multiple-output plant. A proportional controller is a kind of Proportional-Integral-Derivative (PID) controllers. PID controller structure is the most widely used one in industrialapplications. Recently, if stabilizing PID controllers for the plant exist, the parameterization of allstabilizing PID controllers has been considered. However, no paper examines the parameterizationof all plants stabilized by a PID controller. In this paper, we clarify the parameterization of all plantsstabilized by a proportional controller for multiple-input/multiple-output plant. In addition, we presentthe parameterization of all stabilizing proportional controllers for the plant stabilized by a proportionalcontroller.

scholarly journals Diabetics blood glucose control based on GA-FOPID technique

2021 ◽  
Vol 10 (1) ◽  
pp. 516-523
Author(s):  
Wesam M. Jasim ◽  
Yousif I. Al Mashhadany
Keyword(s):  
Glucose Level ◽  
Pid Controller ◽  
Insulin Pump ◽  
Optimization Technique ◽  
Blood Glucose Control ◽  
The Other ◽  
Optimal Controller ◽  
Pid Controllers ◽  
Diabetic Patients ◽  
Proportional Integral Derivative

In this paper, an optimized Fractional Order Proportional, Integral, Derivative based Genetic Algorithm GA-FOPID optimization technique is proposed for glucose level normalization of diabetic patients. The insulin pump with diabetic patient system used in the simulation is the Bergman minimal model, which is used to simulate the overall system. The main purpose is to obtain the optimal controller parameters that regulate the system smoothly to the desired level using GA optimization to find the FOPID parameters. The next step is to obtain the FOPID controller parameters and the traditional PID controller parameters normally. Then, the simulation output results of using the proposed GA-FOPID controller was compared with that of using the normal FOPID and the traditional PID controllers. The comparison shows that all the three controllers can regulate the glucose level but the use of GA-FOPID controller was outperform the use of the other two controllers in terms of speed of normalization and the overshoot value.

scholarly journals Speed Response Optimisation of a Bldc Motor Drive with Ga-Based Classical Controller Tunning

2020 ◽  
Vol 9 (3) ◽  
pp. 2167-2172
Keyword(s):  
Pid Controller ◽  
Pid Controllers ◽  
Bldc Motor ◽  
Genetic Operators ◽  
Transition Mechanism ◽  
Controlled Structure ◽  
Compact Design ◽  
Crossover And Mutation ◽  
Speed Response

The paper addresses the improvement of performance and quality of engines such as BLDC. Better performance, lower maintenance, higher cost, quiet activity, and compact design define a DC motor brushless drive. PI operator, PID controller, fuzzy logic, genetic algorithms, neural networks, PWM power, and less sensor command, there are several methods for regulating the speed of the motor. The GA-based PI and GA-based PID controllers are used for the speed control of BLDC motor. These motors are used in applications such as automobiles, aviation, health, instrumentation, machine tools, robots, and actuation, because of their desirable electrical and mechanical properties. The main gain of the recommended technique is that there is no need for an accurate model of the controlled structure, so it is useful in many industrial processes that do not have an apparent or sophisticated design. Therefore, this method allows determining the best PID values for a given overrun, a rising period, a settling time, and steady-state failure. The algorithm works on three essential selection, crossover, and mutation genetic operators. GA has many variations, such as Real coded GA, Binary coded GA, depending on the forms of these operators. Such variables have a significant influence on the control system's reliability and efficiency. This paper focuses on binary-coded GA & considers crossover quality, PID controller mutation, and computational analysis were conducted. The transition mechanism was studied with MATLAB in the process. With the GA-based PI and PID operator, the BLDC motor is modeled, and the simulation tests are collected. The results obtained through the application of the GA-based algorithm are efficient and satisfy the control characteristics defined.

Switching Gain-Scheduled Proportional–Integral–Derivative Electronic Throttle Control for Automotive Engines

2018 ◽  
Vol 140 (7) ◽  
Author(s):  
Arman Zandi Nia ◽  
Ryozo Nagamune
Keyword(s):  
Pid Controller ◽  
Controller Design ◽  
Pid Controllers ◽  
Proportional Integral Derivative ◽  
Battery Voltage ◽  
Electronic Throttle ◽  
Automotive Engines ◽  
Throttle Valve ◽  
Pid Controller Design ◽  
Gain Scheduled

This paper proposes an application of the switching gain-scheduled (S-GS) proportional–integral–derivative (PID) control technique to the electronic throttle control (ETC) problem in automotive engines. For the S-GS PID controller design, a published linear parameter-varying (LPV) model of the electronic throttle valve (ETV) is adopted whose dynamics change with both the throttle valve velocity variation and the battery voltage fluctuation. The designed controller consists of multiple GS PID controllers assigned to local subregions defined for varying throttle valve velocity and battery voltage. Hysteresis switching logic is employed for switching between local GS PID controllers based on the operating point. The S-GS PID controller design problem is formulated as a nonconvex optimization problem and tackled by solving its convex subproblems iteratively. Experimental results demonstrate overall superiority of the S-GS PID controller to conventional controllers in reference tracking performance of the throttle valve under various scenarios.

The Parameterization of All Plants Stabilizied by a PID Controller for Multiple-Input/Multiple-Output Plants

2013 ◽  
Vol 596 ◽  
pp. 158-167
Author(s):  
Takaaki Hagiwara ◽  
Kou Yamada ◽  
An Chinh Hoang ◽  
Satoshi Aoyama ◽  
Huo Hui
Keyword(s):  
Pid Controller ◽  
Multiple Input Multiple Output ◽  
Pid Controllers ◽  
Proportional Integral Derivative ◽  
Proportional Integral ◽  
Multiple Input ◽  
Input Multiple Output

In this paper, we examine the parameterization of all plants that can be stabilized bya Proportional–Integral–Derivative (PID) controller for multiple-input/multiple-output plants.The PID controller structure is the most widely used controller structure in industrial appli-cations. Recently, if stabilizing PID controllers for the plant exist, the parameterization of allstabilizing PID controllers was considered. However, the parameterization of all plants that canbe stabilized by a PID controller for multiple-input/multiple-output plants has not been exam-ined. In this paper, we clarify this question. In addition, we present the parameterization of allstabilizing PID controllers for multiple-input/multiple-output plants that can be stabilized bya PID controller.

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