Hybrid GWO-PSO Based Optimal PID Controller for Brushless PMDC Motor

PurposeThe purpose of this study is to stabilize the rotating speed of the permanent magnet direct current (PMDC) motor driven by a DC-DC boost converter under mismatched disturbances (i.e.) under varying load circumstances like constant, frictional, fan type, propeller and undefined torques.Design/methodology/approachThis manuscript proposes a higher order sliding mode control to elevate the dynamic behavior of the speed controller and the robustness of the PMDC motor. A second order classical sliding surface and proportional-integral-derivative sliding surface (PIDSS) are designed and compared.FindingsFor the boost converter with PMDC motor, both simulation and experimentation are exploited. The prototype is built for an 18 W PMDC motor with field programmable gate arrays. The suggested sliding mode with second order improves the robustness of the arrangement under disturbances with a wide range of control. Both the simulation and experimental setup shows satisfactory results.Originality/valueAccording to software-generated mathematical design and experimental findings, PIDSS exhibits excellent performance with respect to settling speed, steady-state error and peak overshoot.

This paper discusses the design and low-cost implementation of direction and speed controller for an electric wheelchair actuated using a permanent magnet direct current (PMDC) motor. Most of the works are performed either with the simulation of PMDC motor control with various techniques or studied the performance of a single type of controller in real-time with the wheelchair. In this work, the authors simulated the control of PMDC motor with three different controllers and tuned the parameters for real-time implementation of electric wheelchair control using PMDC motor. The authors attempted the simple solution using push button-based interface as well as a graphical user interface for the direction and speed control of electric wheelchair. The signal processing path of the controller, decode the user command input for the direction and desired speed. The controller generates necessary pulse width modulated signals to the H-bridge driver for directions forward, backward, left, and right direction as well as speed control of wheelchair. The user speed control commands low, slightly medium, medium, high, and very high speed are sensed to limit the speed of wheelchair. The performance capability of the intelligent neural network and fuzzy logic controller is studied and compared with proportional-integral-derivative (PID) controller with variations in speed. The PID, neural network and fuzzy logic controller are designed using Matlab-Simulink for PMDC motor and controller parameters are tuned for driving the wheelchair in the real-time implementation using the ATmega 328P microcontroller. The fuzzy logic controller in the electric wheelchair demonstrated the improved performance with less peak overshoot and faster settling with less oscillation compared to PID and neural network controller.

Permanent Magnet Direct Current (PMDC) motors have been broadly used in mechanical and electrical fields that integrate several applications. This type of motor is subjected to disturbances or sudden changes in loads, and motor speed control is necessary under these conditions. In this paper, we have implemented traditional controllers’ Proportional Integral Derivative (PID) and advanced controllers Super-Twisting Sliding Mode Control (STSMC) and Sliding Mode Control (SMC) through tuning Particle Swarm Optimization (PSO) that used to control the speed of the PMDC motor. According to the results that appeared in the simulations in the MATLAB\Simulink software, STSMC has superiority compared to other controllers in improving the performance of the speed control for PMDC motors. An experimental setup for PMDC motor by proposed controllers to validate the simulated results in the real environment based on the Arduino UNO interface device. Experimental results confirmed the advantages of employing the STSMC technique over other controllers in improving the performance of speed control for PMDC motors to attain the required speed in the least amount of time and rapid rejection of disturbances in the load.

In this study, it was aimed to compare PI (Proportional–Integral) and PID (Proportional–Integral–Derivative) controllers for speed control of Permanent Magnet Direct Current (PMDC) motor under both load and without load. For this purpose, firstly, the mathematical model was obtained from the dynamic equations of the PMDC motor and the obtained mathematical model was transferred to the simulation environment and modeled using Matlab/SIMULINK. Following the modeling process, PI and PID controller structures were formed, respectively. Secondly, after these structures were formed, the PMDC motor was run without any controller. Then, the control of the PMDC motor with no load was provided by using PI and PID controllers. Finally, the PMDC motor were loaded under the constant load (TL = 3 N.m.) for each condition and selected time period (t = 3 s). The obtained result for each control operations was comparatively given by observing effects of loading process on systems. When the obtained results were evaluated for each condition, it was observed that PID controller have the best performance with respect to PI controller.

This paper presents the optimal tuning of PID controller gains based on Particle Swarm Optimization (PSO) technique. The PSO based PID controller tuning is implemented using Integral Time Squared Error (ITSE) performance index. The efficacy of proposed controller is tested with tri-loop error driven Permanent Magnet Direct Current (PMDC) motor with different transient conditions. The simulation results, generated for each transient, show that the performance of PMDC motor is enhanced for both tracking and disturbance rejection.

In this study, the effect of the material characteristics of electrical steel sheet on permanent magnet direct current (PMDC) motors is investigated using finite-element analysis. The motor design and test results are examined and verified through fabrication. The characterizations of brushless direct current (BLDC) motors according to the materials used in their cores have been actively studied. On the other hand, the effect of material characteristics on a PMDC motor consisting of brushes and commutators has not been studied as much. In the case of the PMDC motors, electrical steel sheets are infrequently used because this motor is relatively smaller than the BLDC motor. However, the iron loss characteristics, which are proportional to the frequency and the magnetic flux density, affect the efficiency even in small motors. Further, the output of the motor changes owing to saturation due to iron loss. The outcome presented in this study provides core materials selection guidelines to improve motor efficiency.

This article discusses a new robust control technique that enables the DC-DC boost converter driving a permanent magnet direct current (PMDC) motor to operate in high static and dynamic performances. The new technique is based on the design of a both linear quadratic regulator (LQR) and linear quadratic regulator-proportional integral (LQR-PI) type controllers, which have the advantage of eliminating oscillations, overshoots and fluctuations on different characteristics in steady-state system operation. In order to increase the output voltage, the LQR regulator is combined with a first-order system represented in the form of a closed-loop transfer function, the latter raising the output voltage to 24 volts, this voltage is enough to drive the permanent magnet direct current motor. The contribution of this paper is the creation of a robust control system represented in the form of a hybrid corrector able to regulate steady-state and transient disturbances and oscillations as well as to increase DC-DC boost converter output voltage for the PMDC motor to operate at rated voltage. The results of the three control techniques are validated by MATLAB Simulink.

In high precision control of DC drives, real-time error calculation is the most vital controlling parameter. Due to the time delay of the control circuit, mostly controlling action has been initiated based on the past error that may hamper the precision of the controller. In this regards, future error has to be estimated to initiate the controlling action based on real-time error. But due to the presence of uncertainty in load and also the presence of mechanical inertia in the system, it is difficult to estimate the future speed error based on the Permanent Magnet Direct Current (PMDC) motor system equation. In this paper, the speed error estimation of PMDC motor has been incorporated based on backward arc length of error graph itself. The proposed error estimation approach applied to PMDC motor speed error tracking will overcome the effect of processing time delay of the controller. This proposed speed error tracking method pointing towards the time delay control of PMDC motor. This technique will help to compensate the effect of processing delay time of used controller.

In power generation, renewable energy plays an important role. With the increase in the energy demand, there is a need for a renewable energy source that will fulfil the required demand and also which is environmental friendly. When sunlight falls on a Photovoltaic (PV) module, direct current (dc) is produced and little maintenance is required for PV modules. Maximum Power Point Tracker (MPPT) helps in ensuring that the maximum power is transferred to the load. Design, simulation and implementation of MPPT for PV module using PIC digital signal processor are mentioned in the presented work. A buck/stepdown dc-dc converter in conjunction with proper control is used to perform MPPT. Numerous methods of MPPT algorithm are available, one among them is “Perturb and Observe method (P&O)”, which operates by periodically incrementing or decrementing PV module terminal voltage or current and comparing. In P&O method present PV output power is compared with the previous set of perturbation cycle. For achieving maximum power point tracking, the P&O control algorithm for the adjustment of the step size of the duty ratio of the buck/stepdown dc-dc converter is made. Here Buck converter is used as starter as well as to meet voltage level required for driving Permanent Magnet Direct Current (PMDC) motor. Since both power and voltage variations are considered in this algorithm, it allows better performance of MPPT in driving PMDC motor.

This paper investigates the effects of reducing the number of rules in a fuzzy logic controller (FLC) for a permanent magnet direct current (PMDC) motor. The reliability of the resulting controller, with fewer rules, is also investigated. First, rule extraction is shown front typical transient responses of a PMDC motor when the reference speed changes in a step-like manner. Next, the total number of rules is reduced from 49 rules to 9 rules by eliminating similar fuzzy rules; their corresponding membership functions are then replaced by other already available membership functions. Finally, the FLC consisting of 9 rules has been chosen in this study to investigate the sensitivity of the controller. The values in the decision table are changed in the range of /spl plusmn/30%. It is found that these variations in the rule decision table do not cause any instability problem in the proposed FLC.

This paper explains mainly and plainly how to control the speed of a permanent magnet direct current (PMDC) motor with a PID control analysis at the educational level. While controlling, PMDC motor speed analysis has been made by changing the PID coefficients, parameters such as oscillation effect, maximum overshoot, rise time, and settling time have been examined in detail based. The most ideal state has been tried to be found by replacing PID coefficients. At the same time, PID tuning has been performed by using the particle swarm optimization (PSO) algorithm. PID coefficient correction has been performed in Matlab with some iterations and the subject has been examined from the perspective of comparing different combinations. In this way, it has been tried to contribute to the literature by observing the effect of the PSO algorithm on the PID tuning. It is thought that this study will guide the basics of automation and control projects in future studies on PMDC motor control characteristics.

In this work, an attempt has been made to identify the appropriate parameters of Permanent Magnet Direct Current (PMDC) motor for infusion pump. PMDC motor plays important role in medical devices. In this, selection of parameters such as rotor inertia, armature resistance, armature inductance and back electro motive force constant is crucial that help to achieve the required speed. The proposed work uses PID controller (Proportional Integral Derivative) and LQG (Linear-Quadratic Gaussian) control algorithm to evaluate the parameters for transient response of the PMDC motor. It is demonstrated that the chosen parameters are able to reach the required speed with quick rise time by 0.691 seconds by employing LQG.

In medical devices, permanent magnet direct current (PMDC) motor plays an important role, especially for infusion pumps. This paper makes an attempt to find the suitable parameters of PMDC motor. To attain the required speed for PMDC, the selection of parameters, for instance, rotor inertia, armature resistance, inductance and back electromotive force constant are essential. The work proposed utilizes linear quadratic regulator (LQR) control algorithm to evaluate the parameters. In order to achieve this, LQR parameters are simulated. The simulation results are carried out for medical grade; PMDC motor and the parameters chosen are able to achieve the required speed with quick rise time till 2.45 s.KeywordsLQRDC motorInfusion pumpOptimal control

<div class="htmlview paragraph">Electrical Computer Aided Engineering (CAE) is necessary and useful for the automotive industry [<span class="xref">1</span>,<span class="xref">2</span>]. It provides the user with necessary information that helps him/her make faster and more certain design decisions. CAE facilitates for the user options and the means to locate and choose optimums [<span class="xref">6</span>]. It requires models that best represent the actual system while avoiding unnecessary numerical overhead. Therefore, it is necessary to build the mathematical model in a systematic way that captures dynamics of the actual system [<span class="xref">3</span>]. Also, an optimal solution for the system parameters is required to increase the accuracy of the model and to make a correct decision while designing, testing, and validating [<span class="xref">3</span>,<span class="xref">6</span>]. This paper studies the CAE analysis of a PMDC motor. It develops a systematic approach to model, simulate and analyze PMDC motors with robust output. It enhances the accuracy of PMDC to a 6-Sigma level. A robust model minimizes the effort required in analyzing, predicting and validating the outcome of the motor. The uniqueness in this model is the use of Least Squares algorithm to solve for the optimal value of the motor parameters and the use for Recursive Least Squares (RLS) [<span class="xref">7</span> (page 70)] for On-Line learning. The use of learning overcomes a wide band of ambiguity and non-linearity included in the actual motor. The developed model introduces a procedure for calculating each of the motor parameters (e.g. R<sub>a</sub>, L<sub>a</sub>, K<sub>T</sub>, K<sub>v</sub>, J, D, T<sub>Loss</sub>). In this paper, simulation study uses a seat motor assembly that consists of three different motors as an example. The Saber simulator is used for running the simulation study. The actual data (experimental lab results) and the estimated data (Saber model) are then compared to assure the validity of the seat motor model compared to the physical seat motor.</div>

This paper introduces a nonlinear PI controller for improved speed regulation in permanent magnet direct current (PMDC) motor drive systems. The nonlinearity comes from the exponential (Exp) block placed in front of the classical PI controller, which uses a tunable exponential function to map the speed error nonlinearly. Such a configuration has not been studied till now, thus meriting further investigation. We consider an exponential PI (EXP-PI) controller and to attain the best performance from this controller, its parameters are optimized offline using salp swarm algorithm (SSA), which borrows its inspiration from the way of forage and navigation of salps living in deep oceans. To indicate the credibility of SSA tuned EXP-PI controller convincingly, numerous experiments on speed regulation in PMDC motor have been implemented using DSP of TMS320F28335. The results obtained are also compared to similar results in the literature. It is shown that the proposed approach performs well in practice by ensuring tight tracking of the speed reference and superb torque disturbance rejection for the closed loop control. Furthermore, superior performance is achieved by the proposed nonlinear PI controller with respect to a fixed-gain PI controller.