Solar PV Combined Efficient Torque Control of BLDC Motor Using Salp Swarm Optimization

Liquid level control in two tanks spherical interacting system with fractional order proportional integral derivative controller using hybrid technique: A hybrid technique

The main objective of this paper is to implement the Fractional Order Proportional Integral Derivative (FOPID) controller for output voltage control of DC - DC Zeta converter. Implementing a distinct control technique for DC-DC converters has also been introduced with the commercial availability of integrated circuits (ICs) to carry out this task. The simulation of Classical Proportional Integral Derivative (PID) and Fractional Order PID (FOPID) control techniques for the control of Zeta converter and its characteristics of a dc-dc converter, where aspects such as the output voltage, required peak overshoot and rise time specifications are investigated using MATLAB/ Simulink model. Through simulation it is confirmed that the propounded FOPID controller gives better the transient response of the feedback system by using a significantly smaller control effort (i.e., less on-off switches), the Internal Absolute Error (IAE) of the variations of the output voltage is minimized and improves the strength of the DC - DC ZETA converter to variations in the input voltage. Artificial Bee Colony (ABC) algorithm offers fine tuning the factors of the FOPID controller.

Direct Current (DC) motors are extensively used in various applications due to their versatile and precise control capabilities. However, they face operational challenges such as speed instability and sensitivity to load variations and external disturbances. This study compares the performance of several advanced control methods—Proportional Integral Derivative (PID), Fractional Order PID (FOPID), Integral State Feedback (ISF), Sliding Mode Control (SMC), and Fuzzy Logic Controller (FLC) for DC motor control. Particle Swarm Optimization (PSO) is employed to optimize the tuning parameters of PID, FOPID, ISF, and SMC controllers, while FLC is implemented without optimization. The simulation results indicate that the PSO-FOPID controller exhibits the best overall performance, characterized by the fastest rise and settling times and the lowest ITSE, despite a minor overshoot. The PSO-PID controller also performs well, with fast response times, although it is less efficient in terms of settling time and ITSE compared to PSO-FOPID. The OBL/HGSO-PID controller, while stable and overshoot-free, has a slower response. The PSO-ISF controller shows the highest stability with the lowest SSE values, making it suitable for applications requiring high stability. The PSO-SMC controller demonstrates good stability but is slightly slower than PSO-ISF. The FLC controller, however, performs the worst, with significant overshoot and long recovery times, making it unsuitable for fast and precise control applications. The robustness analysis under varying motor parameters further confirms the superiority of the PSO-FOPID controller, which outperforms OBL/HGSO and OBL-MRFO-SA optimizations across both PID and FOPID controllers, making it the most effective solution for applications requiring high precision and rapid response.

In this paper, an optimal Fractional Order Proportional Integral Derivative (FOPID) controller is applied in vehicle active suspension system to improve the ride comfort and vehicle stability without consideration of the actuator. The optimal values of the five gains of FOPID controller to minimize the objective function are tuned using a Multi-Objective Genetic Algorithm (MOGA). A half vehicle suspension system is modelled mathematically as 6 degrees-of-freedom mechanical system and then simulated using Matlab/Simulink software. The performance of the active suspension with FOPID controller is compared with passive suspension system under bump road excitation to show the efficiency of the proposed controller. The simulation results show that the active suspension system using the FOPID controller can offer a significant enhancement of ride comfort and vehicle stability.

A pressurized heavy water reactor (PHWR) is a nuclear power reactor,that commonly uses unenriched natural uranium as its fuel and heavy water as its coolant and moderator. The PHWR has become an important component of the present day power generation industry. Working of a PHWR may often require reduction of nuclear power within a small finite time interval in accordance to the varying load conditions. This phenomenon is referred to as step back condition. Therefore, for the efficient working of the PHWR it is very important to have a control algorithm that has the capability to handle the step back condition very precisely. The fractional order control strategy has emerged as one of the very versatile and accurate control strategies in the recent times. The fractional order PID (FOPID) controllers are known to give very robust performance both in nominal as well as varying operating conditions. However, most of the design techniques available for the FOPID controllers are mathematically very lengthy and complex. Therefore, in this paper an FOPID controller design technique has been suggested using the concept of internal model control (IMCFOPID) for the PHWR under step back conditions. Further, the performance of the proposed controller has been compared with the conventional FOPID controller using the various integral error criterions. The proposed IMC-FOPID controller is found to give an improved performance as compared to the conventional FOPID controller.

A fractional-order proportional integral derivative (FOPID)controller has replaced the classical PID controller used in industries for process control application. FOPID is less sensitive to the change of control parameters than PID Controller, due to which better results are obtained. The FOPID provides a robust and stable system for a higher-order system as of iso- damping property. This study aims to find a stable and controlled structure by tuning the FOPID controller with the Particle Swarm Optimization (PSO) algorithm, fuzzy-based logic approach, and Adaptive Neuro-fuzzy inference system (ANFIS). The tuning of FOPID is done to overcome deficits of PID controller using the different types of optimization method to overcome large overshoot and large settling time. This paper presented useful techniques based on PSO, fuzzy logic, and ANFIS to optimize FOPID controlled high-performance drilling machines. On the analysis and comparisons of simulation findings, it is observed that the FOPID-PSO approach provides better performance over the Ziegler-Nichols (ZN)-FOPID and the above-mentioned intelligent techniques in terms of less settling time (ts=0.823sec.) & optimized peak overshoot (Mp=2.44%) for the mentioned target.

This investigation presents an optimisation-driven fractional order PID (FOPID) controller design methodology for brushless direct current (BLDC) motor speed control for electric vehicle applications. Though the introduction of fractional terms provides additional flexibility, their optimal selection is important for achieving desired performance. For this purpose, this investigation uses two evolutionary optimisation approaches-real coded genetic algorithm (RGA) and bio-geography based optimisation (BBO). In order to illustrate the improvements provided by FOPID, its performance is compared with conventional PID controller. Our results demonstrate that the FOPID controller tuned by BBO algorithm provides up to 50% improvements in transient response over the PID controller.

Because of the benefits reduced size, cost and maintenance, noise, CO2 emissions and increased control flexibility and precision, to meet these expectations, electrical equipment increasingly utilize in modern aircraft systems and aerospace industry rather than conventional mechanic, hydraulic, and pneumatic power systems. Electric motor drives are capable of converting electrical power to drive actuators, pumps, compressors, and other subsystems at variable speeds. In the past decades, permanent magnet synchronous motor (PMSM) and brushless dc (BLDC) motor were investigated for aerospace applications such as aircraft actuators. In this paper, the fractional-order PID controller is used in the design of speed loop of PMSM speed control system. Having more parameters for tuning fractional order PID controller lead to good performance ratio to integer order. This good performance is shown by comparison fractional order PID controller with the conventional PI and tuned PID controller by Genetic algorithm in MATLAB soft wear.

The design of a controller for the conical tank system is a challenging problem, because of its non-linearity behavior. The Proportional-Integral-Derivative controllers have played a vital role in many process oriented industrial applications, for past few decades. This paper deals with design of Non-Integer order Proportional Integral Derivative or Fractional Order Proportional Integral Derivative (FOPID) controller for a level control process of single conical tank system. FOPID provides more flexibility in designing a controller than using standard Proportional Integral Derivative (PID) controllers, due to selection of five parameters instead of three. Though the tuning of FOPID is complex, it can guarantee the desired control performance and the robustness to the loop gain deviations. The comparison of various tuning methods using PID controller is simulated. FOPID controller has been designed for the same conical tank system and the performances of both the PID and FOPID controllers have been simulated and compared.

Electric vehicles are currently being developed with the concept of saving energy and environmentally responsible. Electric vehicles use electric motors as the main driving motor. The electric motor which is currently increasingly used is the Brushless Direct Current (BLDC) motor. The BLDC motor controller is more expensive than the price of the BLDC motor itself. The BLDC motor controller has a working temperature range when working. The purpose of this study was to analyze the effect of variations in load values and the speed of electric vehicles on the temperature of the BLDC motor controller. This research was conducted by the experimental method by giving a treatment, then evaluating the effect caused on an object of research. The results showed that there was an influence of load value variations on the BLDC motor controller temperature. Values that look significant are at speeds of 0.5 m/sec and 2.5 m/sec starting from 3 kg to 5 kg. There is no influence on the variation of speed values on the temperature of the BLDC motor controller. The temperature value is stable at 2 kg and 3 kg loads with speed variations from 0.5 m/sec to 2.5 m/sec. Simultaneously variations in load and speed values affect the temperature of the BLDC motor controller by 57.7% with the lowest temperature value at 0.5 m/s and a load of 1 kg with a temperature of 33.34℃ and the highest temperature value at a speed of 2.5 m/sec and a load of 5 kg with a temperature of 37.58℃. Keywords: Electric vehicles, controllers, BLDC motors, temperature.

This paper deals with the analysis, design and control of solar photovoltaic (SPV) array fed permanent magnet brushless DC (BLDC) motor drive for water pumping system which utilizes a canonical switching cell (CSC) converter as an intermediate DC-DC converter between the SPV array and the voltage source inverter (VSI). The CSC converter performs the functions of solar PV array power optimization and the safe starting of the BLDC motor by an adequate control. In addition to MPPT (Maximum Power Point Tracking) of SPV array, the CSC converter provides a variable output DC voltage for the electronic commutation of VSI facilitating its fundamental switching for reduction in its losses and an elimination of its current sensors. The detailed performance of the proposed water pumping system is demonstrated through simulated results obtained using MATLAB/Simulink based developed model subjected to various operating conditions such as the variations in the solar insolation level.

In an electric vehicle (EV) charger system, a two-stage conversion process is integrated and cascaded with a voltage source converter (VSC) and a Dual active bridge converter (DAB). These impedances VSC outputs impedance (ZoutVSC(s)) and DAB have input impedance (ZinDAB(s)) interact, leading to voltage fluctuation and power loss. To address the cascaded converter’s impedance interaction, the modified controller that combines an adaptive Neuro-fuzzy inference system (ANFIS) based fractional order proportional integral derivative (FOPID) controller is used with effective active damping (AD). The modified controller (ANFIS + FOPID + AD) uses ANFIS’s skills to capture and predict the system’s nonlinear behaviour, using its trained data to guide the FOPID’s parameter. The presence of AD ensures the sorting out of impedance interaction problems. Compared to the PID controller, the FOPID controller includes two more degrees of freedom and offers superior adaptability and performance. The effectiveness of the modified controller is tested via frequency response analysis and time domain simulations. Time domain simulations underscore the advantage of the modified controller (ANFIS + FOPID + AD), revealing a remarkable 30% settling time and a 25% overshoot compared to the (FOPID + AD) controller. It is better regarding flexibility, faster response time, and improved system stability. The system performance has been validated and compared by simulation process and HIL technique OPAL RT OP44512.

This paper presents a method for robust optimum tuning of Fractional-order Proportional Integral Derivative (FoPID) controller for Automatic Voltage Regulator (AVR) system. Optimal tuning of FoPID parameters for AVR system are accomplished by using Salp Swarm Algorithm (SSA) of optimization. The performance of the AVR system with FoPID controller tuned by SSA shows the robust performance against disturbances deliberated at the output of the system. To test the robustness of the system, in the presence of external disturbance $H_{\infty}$ norm is considered. AVR system with SSA tuned PID controller is also simulated with MATLAB platform. Results shows that the AVR system with SSA tuned FoPID controller outperform the SSA tuned PID controller in the presence of external disturbances at output of the system and shows its disturbance rejection capabilities.

Brushless DC motor drives supplied by PV power system based on Z-source inverter and FL-IC MPPT controller

<span>This paper proposes the fractional-order proportional integral derivative (FOPID) controller, as a speed controller for permanent magnet direct current (PMDC) motor, instead of the traditional integer-order PID controller. The FOPID controller is the general form of the integer-order PID controllers, which found wide applications in all engineering fields. In this work a hybrid M-file and SIMULINK program is developed to simulate the overall system, the FOPID controller has five associated parameters. The optimum values of those parameters are found out by using particle swarm optimization technique. Simulation results show excellent command speeds tracking and superior dynamic response in conjunction with that of the integer-order PID controller. The proposed controller shows a high ability to overcome any external disturbance the system may be exposed; also, it performs a high degree of robustness to control the system in motoring and regenerative operating modes.</span>