Neural Network-Based Monitoring of Critical Parameters in Drinking Water for Enhanced Quality Assurance
Monitoring and Improvement of PV Panel Efficiency Due to Thermal Effect
Model Predictive Control of a Serial Link Robot Manipulator
Direct Torque Control (DTC) and Three Phase Induction Motor Simulation in MATLAB/Simulink
IoT-Enabled Smart Water Tank Monitoring System with Android Application Control
Diagnosis of Air-Gap Eccentricity Fault for Inverter Driven Induction Motor Drives in the Transient Condition
Modelling and Simulation Study of a Helicopter with an External Slung Load System
Comparative Study of Single Phase Power Inverters Based on Efficiency and Harmonic Analysis
LabVIEW Based Design and Analysis of Fuzzy Logic, Sliding Mode and PID Controllers for Level Control in Split Range Plant
Trichotomous Exploratory Data Analysis [Tri–EDA]: A Post Hoc Visual Statistical Cumulative Data Analysis Instrument Designed to Present the Outcomes of Trichotomous Investigative Models
This paper presents three types of optimization techniques; Teaching Learned Based Optimization (TLBO), Harmony Search Algorithm (HSA), and Local Unimodal Sampling (LUS) which are used to tune the controller parameters in Automatic Voltage Regulator (AVR) system. AVR system is used to adjust the terminal voltage of synchronous generator. This paper presents two types of controllers: Proportional-Integral-Derivative (PID) and Proportional-Integral-Derivative- Acceleration (PIDA). Each controller is used with TLBO, HSA, and LUS. For PID controller, these techniques show better performance than Many Optimizing Liaisons (MOL), Gravitational Search Algorithm (GSA), Artificial Bee Colony (ABC), Particle Swarm Optimization (PSO), and Differential Evolution (DE) in previous works. For PIDA controller, these techniques show better performance than Bat Search (BAT), Current Search (CS), Tabu Search (TS), and Genetic Algorithm (GA) in previous works. By comparing both controllers, PIDA shows better response in overshoot and steady state error than PID.
In industries, continuous transportation of materials from one section to another includes conveyor belts. The use of conveyor belts is mostly for supply of raw materials for production. Generally, when a material is transported over the conveyor belt, it provides a way to control and monitor the operation, thereby handling the production. This paper intends to develop an approach to overcome the shortcoming of the time delay in observation and response, by utilizing Infrared sensors. It also provides a method to manage manufacturing from remote places. This is done by interfacing a controller module along with a sensor module in the device. This paper presents the creation of a prototype for an automatic monitoring and control system for probing objects on a conveyor belt. It also includes a method to control the production within the prescribed time by preventing the negligence caused by the operators.
The position of Brushless Direct Current (BLDC) rotor is determined by measuring the changes in the Back-EMF. Sensorless control method reduces the cost of the motor as it does not need sensors. This paper presents Bio-inspired optimization technique (Particle Swarm Optimization algorithm) and classical methods of tuning PID control parameters for the automatic speed tracking of BLDC motor. The BLDC is modelled in Simulink in Matlab and Back-EMF waveforms are modelled as a function of rotor position. The proposed methods are effective in reducing the steady state error, rise time, settling time, and peak overshoot. The classical methods such as Ziegler-Nichols (Z-N), Tyreus-Luyben (T-L) methods, and Particle Swarm Optimization (PSO) techniques based on effective objective function Integral Absolute Error (IAE) are proposed for the optimal tuning of PID controller parameters. The results obtained from Particle Swarm Optimization technique are compared with the classical methods.
In the last few decades, in all types of industries, approximately the most common types of controllers are PID controllers. They have found a huge acceptance and application in distinct industry. The most common types of controller used in process control are PID controllers due to their efficient response. Proper tuning rules are required for PID controller to give desired output and appropriate performance. There are progressive researches going on, to develop novel methods for PID tuning rules and designing. A large number of algorithms have been grown up by researchers and appropriate methods according to the application are approved by industries for PID tuning and designing. The authors aim to find out the way, which provides better tuning parameterization and better response. In this paper, the superiority of FOPID controller over conventional PID controller is discussed using MATLAB/SIMULINK. In recent years, FOPID controllers replaced all the PID controllers in many areas of engineering and science. The concept of FOPID controller was first invented by Podlubny in 1997.
Transmission system expansion in India has not been consistent with the growth of demand in the states, resulting in suboptimal utilization of generation capacity. It is therefore critical to ensure that the existing transmission assets are fully utilized by loading them much closer to their capacity. One of the major concerns, then, is the secure operation of the system because of the presence of low-frequency electromechanical oscillations typically in the range of 0.1–0.8 Hz. One primary way of tackling the problem is to improve the dynamic behavior of the system and thereby allowing system operation closer to the capacity, without compromising security. In this paper, the authors have explained about low frequency oscillations and how it can be addressed using FACTS self tuning controllers.
