Systematic Irrigation System Deploying Sensor Technology
Diagnostic and Therapeutic Device for Knee Injury
5-DoF Upper Limb Exoskeleton Controlled through Intelligent Semi-Automated Shared Tongue Control
Therapeutic Based Wearable Postural Control System for Low Back Pain
Transforming Organ Transplantation and Medical Education Advancements in 3D Printing Technology
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 study introduces the input decentralized control technique for a strongly coupled MIMO system in a simple and clear procedure through a numerical example based on a combination of both pole placement and linear quadratic regulator techniques. This system can be stabilized by a multilevel control, each decoupled subsystem can be stabilized separately by using local controllers, which can provide a desired degree of stability, while global controllers are applied to enhance the overall system stability through reducing the effect of the interconnections among subsystems. The possibility of using the predetermined ITAE poles at different frequency values is investigated, these pole locations may be deviated from its nominal placed values for each decoupled subsystem, which affect subsystem as well as overall system stability, or lead to a slow overall system eigenvalues. Linear, quadratic optimal technique can be applied over the subsystem level in order to shift the slowest obtained pole locations into a much more stable places, which in turn shift the slowest overall system eigenvalues and guarantee a higher stability degree. This procedure can be applied many times until all the undesired poles are shifted.
Nowadays Power system suffers from a lot of power flow problems. The main common problems are high power loss and overload of lines. The Distributed Generators (DGs) are considered as one of the efficient solutions for these problems. The DG can generate power at the location of load which helps in power loss problem. Also generation at load location will decrease the power flow in lines. This paper studies the DG sizing by new optimization techniques. Several cases studied in this work to select the suitable techno-economic strategy of DG sizing. Ranges of DG sizing in cases were studied are 40%, 60%, 80% and 100% of system loading. Studies consider trying to improve the voltage profile to certain limits by using the DGs. Finally, suggestion is concluded to which range of sizing is suitable and if the voltage limits consideration is economical or not in DG sizing.
In the present era, there is huge scarcity of energy and to carry out the daily activities, electricity is the major requirement. There is a need to produce electricity at a faster rate. In the basic applications, sound is converted into electrical signals to travel over the media for communication purposes. The application of sound energy as electrical energy can be much beneficial. It can be used to lighten the street lights by using the noise made by vehicles. This technology can also be used in industries, airports, runways. Conversion of sound energy into electrical energy appears to be one of the promising techniques to increase the production of energy without depleting natural resources. The objective of this work is to create a device that can convert the sound energy into electrical energy and harvest it for future need. Huge amount of noise is created in the surrounding by different means and this noise energy is generally let into the atmosphere which is not utilized and goes wasted. This work also describes the use of this conversion method in the surrounding to harvest energy from the vehicular noise, noise created by humans and industrial noise. By doing so, there is a reduction in pollution as well as the efficiency of the machines is increased. In today's world, a suitable method of power generation is required which could benefit the society. Thus, the concept of conversion of sound energy into electrical energy have been well discussed. Various applications based on the conversion have also been highlighted.
Road accidents are a major problem in today's world. The aim of this research is to provide a solution to prevent such accidents. This project is mainly focused on automatically controlling the speed of the vehicles in speed restricted zones, such as schools, hospitals, and speed limit zones. Currently, the system used for monitoring and controlling speed of vehicles in speed-limited zones is ineffective or non-existent. This work proposes a system for controlling the speed of the vehicles within certain limits in restricted zones without driver intervention, and also checks whether a particular vehicle owner has paid insurance or not. Then it provides an alerts to the owner and the traffic control room in case the payment is not done. In this work, an RF transceiver system is used to indicate the speed limited zones, and upon entering such zones, the speed control system installed in the vehicle automatically adjusts the speed accordingly. The same transceivers also monitor the insurance status of the vehicle, and send relevant messages to the owner of the vehicle.
This paper investigated Load Frequency Control (LFC) using an Artificial Intelligence (AI) technique called Adaptive Neuro-Fuzzy Inference System (ANFIS). ANFIS controller is simple to apply and at the same time it can handle system nonlinearities very effectively. ANFIS controller gives better dynamic response and it is faster than proposed controllers. Dynamic analysis was done without controller, with Proportional Integral Derivative controller (PID controller), Fuzzy controller, Linear Quadratic Regulator (LQR), and with Adaptive Neuro-Fuzzy Inference System (ANFIS) controller using Matlab/Simulink. The results of ANFIS controller was compared with results obtained from other controllers and it is observed that it has improved system performance in terms of steady state response and reduced oscillations and at the same time it is faster than above proposed controllers.
This paper presents a comprehensive approach for Coordinated Control (COC) of Series Vectorial Compensator (SVeC) and Power System Stabilizer (PSS) for damping Low Frequency Oscillations (LFO) in multimachine networks. SVeC is viewed as the most innovational series Flexible AC Transmission System (FACTS) device. Though PSS and SVeC devices have been incorporated separately in multi machine networks, optimal control strategy based on state feedback control for coordination of PSS and SVeC controllers under different loading conditions has not been developed. So, the Optimal State Feedback Controller (OSFC) for incorporating of PSS and SVeC controllers in COC manner has been developed in this paper. The performance of the aforesaid method is checked using eigen-value analysis and nonlinear time- domain simulation outcomes under numerous loading conditions together with nominal case. The comparison of performance of COC of SVeC and PSS in a Western System Coordinating Council (W.S.C.C) 3-machine, 9-bus system is investigated in this paper. The damping characteristics of the optimal controller for COC of SVeC and PSS are compared with COC, PSS and without control are analyzed. The outcomes of test system show that the proposed optimal control can improve the dynamic stability of test system significantly at different loading conditions.
