Browsing by Author "Kumarawadu, S"

Now showing 1 - 20 of 35

item: Conference-Abstract
A compact and high performance SC DC/DC buck converter
(2008) Baek, CJ; Kumarawadu, S
A novel paralleling interleaved discharging (PID) approach is presented to reduce the output ripple and continuous input current waveform in step-down switched capacitor (SC). Theoretical analysis and the computer simulation show that PID method can reduce output ripple by a factor of three and improve output power level by 8. 7%. The PID method can provide a large range of constant desired values of the output voltage for a given input voltage by paralleling.
item: Conference-Abstract
A novel active inrush suppression method for SC converter
(2008) Baek, CJ; Kumarawadu, S
A new type of Inrush suppression circuit in SC buck converter is proposed. The method is realized by the hybrid of passive and active circuits. It adapts PIC micro controller to generate multi pulse to drive multi switches. Computer simulation shows that this method suppresses inrush current drastically.
item: Conference-Abstract
A novel morphin-based obstacle avoidance control algorithm for USVs
(2008) Jayendra, G; Kumarawadu, S; Piyasinghe, L
This is an effort of employing good obstacle avoidance algorithms for unmanned surface vehicles (USV) which are already developed for unmanned ground vehicles (UGV). Previously developed Morphin algorithm is utilized for the obstacle avoidance ofUGV. Simulations were carried out using MatLab to prove the validity of the algorithms. Approach towards the results and results are presented. Other USV developers can employ these algorithms for their developments.
item: Conference-Abstract
Accurate attitude estimation of low-accelerating vehicles by the use of multiple low cost MEMS-Based IMUs
(2008) Dharmapriya, TDK; Kumarawadu, S; Piyasinghe, LP
Inertial sensors and inertial measurement units (IMUs) are widely used in navigation support systems, autonomous vehicle navigation, and vehicle motion control process. Inertial measurement based attitude determination and navigation systems are capable of sustaining their accurate operation with high resolution without subjecting to external jamming and noise conditions. The most vital equipment in inertial measurement system is the IMU. The required degree of accuracy, resolution and repeatability in angular velocities and accelerations mainly depend on the implementation technology of the gyroscopes and accelerometers. The paper presents a methodical approach to obtain better attitude determination for vehicles with low-cost, multiple MEMS-based IMU. The simulated results are based on the mathematical models of MEMS-based gyroscopes and accelerometers.
item: Conference-Abstract
An Active monocular platform for intelligent vehicles: Design and simulations
(2008) Piyasinghe, LP; Kumarawadu, S; Jayendra, G; Dharmapriya, K
Intelligent vehicles have to perceive their environment in order to navigate and avoid collision. This capability is also important in other applications such as mobile robot navigation, Automated Guided Vehicles (AGVs) for automated material handling, intelligent transportation systems, rescue operations in natural disasters, and wildlife observation. Since angular rotations of the moving vehicle deteriorate the quality of the image, cameras have to be mounted on a stabilized platform. Further control is required if the cameras are expected to keep looking at an object of interest irrespective of the vehicle's translational motion. This paper describes designing a monocular vision, system kinematics, and dynamics analysis. Simulation results are also presente
item: Article-Full-text
Deep learning based non-intrusive load monitoring for a three-phase system
(IEEE, 2023) Gowrienanthan, B; Kiruthihan, N; Rathnayake, KDIS; Kiruthikan, S; Logeeshan, V; Kumarawadu, S; Wanigasekara, C
Non-Intrusive Load Monitoring (NILM) is a method to determine the power consumption of individual appliances from the overall power consumption measured by a single measurement device, which is usually the main meter. Increase in the adoption of smart meters has facilitated large scale implementation of NILM, which can provide information about individual loads to the utilities and consumers. This will lead to significant energy savings as well as better demand-side management. Researchers have proposed several methods and have successfully implemented NILM for residential sectors that have a single-phase supply. However, NILM has not been successfully implemented for industrial and commercial buildings that have a three-phase supply, due to several challenges. These buildings consume significant amount of power and implementing NILM to these buildings has the potential to yield substantial benefits. In this paper, we propose a novel deep learning-based approach to address some of the key challenges in implementing NILM for buildings that have a three-phase supply. Our approach introduces an ensemble learning technique that does not require training of multiple neural network models, which reduces the computational requirements and makes it economically feasible. The model was tested on a three-phase system that consists of both three- phase loads and single-phase loads. The results show significant improvement in load disaggregation compared to the existing methods and indicate its applicability.
item: SRC-Report
Development of intelligent collision avoidance systems
(2006) Kumarawadu, S
Three research papers included : "A new paradigm for intelligent collision avoidance via interactive and interdependent generic maneuvers", "Cooperatively controlled collision evasive emergency manoeuvres" , "Prototype realization of vehicles for performance analysis of emergency intervention algorithms", and "Interactive collision avoidance controller - design and realization"
item: Thesis-Full-text
Development platform for motor controls
Dayananda, PRD; Kumarawadu, S
Speed control of induction motor has become a famous topic in the industrial automation field during the past decade. Due to the rapid growth in power electronics, this field has been grown for a great extent. There are many algorithms currently available for speed control of induction motors, while every algorithm has its relative merits over other. In different situations, it's desirable to use different algorithms. In normal inverters available in the market, most of the time one algorithm is implemented, which is hard-coded in the circuit. This project is about design of a programmable induction motor drive which is capable of implementing different algorithms in one system. Currently it has been developed as a test bench for machines laboratory where different algorithms such as Six Step, Sinusoidal PWM and Constant VIf control are available in the same system with user selectable mode. The system is reprogrammable, so it's possible to include some new algorithms such as trapezoidal PWM in future as further development of this project. Two types of microcontrollers are used in order to produce the control signals for the inverter. One is Object Oriented PIC (OOPic) and other is PIC16F767, in which there are 3 inbuilt hardware PWM modules with 10-bit resolution available. Six step algorithm is implemented using the OOPic & the sinusoidal PWM with Vlf control in implemented using PIC16F767. There is a new speed sensor designed using Hall IC which is very cheap & accurate in operation. This is designed as a low cost alternate method of speed sensing instead of 'Using high cost encoder or photo electric sensors. The sensor feedback signal processing & display of speed also implemented in OOPic. A driver circuit was very' much needed in between the controller and the inverter for several reasons. One is to provide optical isolation from logical ground and the power ground. Other one is to provide a sufficient dead time in upper & lower switch signals. Also a voltage which is capable of switching on an IGBT was needed from the driver circuit. An IGBT module-which consists of converter & inverter circuit is used as the main switching device to produce variable frequency, variable voltage sinusoidal output. Many challenges were faced while carrying on the project, which gave us a valuable experience by having hands on experience with different ICs, power electronic devices & microcontroller programming. The major issues and challenges faced and the solutions are included in this report. Also a detailed discussion about various components & functionalities is included with the test results. This project report will be a very useful document to anybody interested in designing control systems and power electronic circuit design.
item: Article-Full-text
Discrete-time neuroadaptive control using dynamic state feedback with application to vehicle motion control for intelligent vehicle highway systems
(John Wiley & Sons Inc., 2010) Fernando, M; Kumarawadu, S
Discrete time neuro-compensated dynamic state feedback control system for lateral and longitudinal control of intelligent vehicle highway systems (IVHS) is developed. A discrete time counterpart of the continuous time non-linear IHVS model is obtained in state-space form and the controller is analysed in three stages, with and without compensation mechanisms resulting in an implementation from low to high complexity. Gain parameters of the dynamic state feedback control are optimised with respect to a minimisation of a linear quadratic cost function. The weight convergence of the neuro-compensation algorithm is established in discrete time Lyapunov sense via a graphical method. The performance enhancement of each design stage of the controller is presented and compared with the aid of computer simulations.
item: Thesis-Abstract
Distribution system reliability modeling and analysis
(2015-02-22) Gamage, MD; Kumarawadu, S; De Silva, PSN
With the background of imposing new electricity act and the regulatory regime for electricity industry, utilities have to be concerned not only the cost of the electricity but also the quality of the supply. As the cost of electricity is embedded to the electricity tariff, cost of reliability will also be added to the tariff in near future. Hence, utilities need to have a reliability study model to enhance the reliability of power supply at optimum level. Aim of this research is to formulate methodology to calculate supply reliability to end user by component reliability. Past three years outage data of Lanka Electricity Company (LECO) had been analysed to calculate reliability of critical path components of the distribution network. Two reliability models named direct restoration method and step restoration method had been applied to calculate sustained end user reliability indices such as SAIDI and SAIFI. End user reliability indices had been calculated using the derived component reliability for the selected distribution network portion of LECO for this purpose. Finally, the results had been compared with the absolute data for the same network as a measure of model validation. The result from the direct restoration model is deviated from the recorded results. It is noted that the results calculated by step restoration model comply with the recorded data. There were instances of deviation caused due to the non conformity of step restoration Markovian model of the network portion. Considering the validation of results, it was identified that LECO distribution network reliability shall be modeled using step restoration model. It is also noted that due to the statistical nature of component reliability, the results are also statistically distributed. The requirement of utilities to incorporate reliability criteria into their planning objectives is a requirement today in view of the regulatory governance of the electricity sector. The tariff when comes cost reflective essentially needs to incorporate cost of reliability as well.
item: Thesis-Full-text
Estimating state of charge of small scale battery storage
Amarasinghe, ND; Kumarawadu, S
Lead-acid batteries are often used as the energy storage component for small-scale photo-voltaic(PV), systems in the developing world, allowing electricity to be supplied when generation is not occurring. Batteries often account for a significant fraction of the capital cost of the system and also have the shortest lifetime when compared to solar panels ect. In simple systems, the management of the battery sub-system is often crude, with the battery charged directly via a solar panel through a simple reverse-blocking diode and supplying an inverter incorporating a simple under-voltage cut-out in an attempt to avoid over-discharge. This leads to frequent over-charging (and over-discharging if the voltage cut-out is set incorrectly) of batteries and early failure, necessitating costly refurbishment or replacement. Also when several batteries are in series or parallel the extractable energy from the whole battery is limited by the capability of the weakest battery in the group. But if the SOC(State of Charge) batteries in a group, can be determined in advance, to determine the point of cut-off for charging or discharging, the extractable energy can be increased without sacrificing the life of batteries. This paper discuss different techniques that are used today in determining the SOC of batteries in the lines of its applicability of the particular case of group of batteries. This thesis thoroughly investigate the applicability of state variable approach proposed by John Chiasson and Baskar Vairamohan in “Estimating the State of Charge of a Battery” for the case of more than one battery, where it considers only terminal voltage and current of the battery for estimating the SOC. In this approach a non-linear time varying system is simplified to a linear time varying system with some reasonable assumptions. This approach was verified for different types of batteries at different state of health. It was also verified that the same method is applicable to find out the week battery in a string of series of batteries. The paper in its final chapter proposes a technique which is general and applicable for determining the discharge cut-off point based on rate of change of terminal voltage.
item: Conference-Abstract
Fuzzy logic-based navigation of a boat
(2008) Jayendra, G; Kumarawadu, S; Piyasinghe, L
This paper mainly describes designing and simulating a fuzzy logic-based navigational controller for unmanned surface vehicles. The controller considered in this study is consists a fuzzy based systems. MatLab framework with Fuzzy Logic toolbox was used to design and implementing the whole system. MatLab programs were used for the navigational controller simulation. The basic design procedure and the simulation procedure were included in the paper in detail. The results including the desired and actual paths are plotted.
item: Article-Abstract
High-Performance Object Tracking and Fixation With an Online Neural Estimator
Kumarawadu, S; Watanabe, K; Lee, TT
Vision-based target tracking and fixation to keep objects that move in three dimensions in view is important for many tasks in several fields including intelligent transportation systems and robotics. Much of the visual control literature has focused on the kinematics of visual control and ignored a number of significant dynamic control issues that limit performance. In line with this, this paper presents a neural network (NN)-based binocular tracking scheme for high-performance target tracking and fixation with minimum sensory information. The procedure allows the designer to take into account the physical (Lagrangian dynamics) properties of the vision system in the control law. The design objective is to synthesize a binocular tracking controller that explicitly takes the systems dynamics into account, yet needs no knowledge of dynamic nonlinearities and joint velocity sensory information. The combined neurocontroller–observer scheme can guarantee the uniform ultimate bounds of the tracking, observer, and NN weight estimation errors under fairly general conditions on the controller–observer gains. The controller is tested and verified via simulation tests in the presence of severe target motion changes
item: Conference-Abstract
Interactive collision avoidance controller- design and realization
(2008) Kumarawadu, S; Ransara, SHK; Dissanayake, ASJ; Ranasinghe, N; Azmil, MM
This paper mainly discusses about the design and realization aspects of collision avoidance (CA) controller which has the capability of interaction. ln other words, the controllers can talk with each other while operating in the field. Both static collisions and dynamic collisions scenarios were addressed. The key feature of the control algorithm is that the vehicles on course of an imminent collision communicate with each other and cooperatively takes collision evasive maneuvers using a simple master slave mechanism and dynamically changing the roles of master and slave as per the requirement.
item: Thesis-Abstract
Modeling and control of a surface vessel for "ITS for the Sea" applications
Kumara, KJC; Kumarawadu, S; De Silva, PSN
In the emerging field of intelligent transportation systems (ITS), ''TS for the sea'' refers to the area of maritime traffic. Automated vehicle control systems are a key technology for ITS. An autonomous surface vessel (ASV) can be defined as a vehicle controlling its own steering and speed for Navigation, dynamic positioning, motion stabilization and obstacle detection and avoidance. The scope of the research is defined by two main objectives viz. developing complete mathematical model of a surface vessel by analyzing hydrodynamic forces and main other effects arising when manoeuvring in the ocean, and design online-learning adaptive controller for path tracking and speed control using real control inputs; propeller thrust and steering angle. The vessel moves in a hydrodynamic environment where many uncertainties, non-linear and non-predictive behaviours always appear. The ocean vehicle is modelled mathematically using first principles and derivations wherever possible. In this work, the problem of control with guaranteed sway and yaw stability for automated surface vessel operation is addressed with special emphasis on speed control. A control scheme to solve this problem without simplifying the dynamics is proposed and extensively studied using formative mathematical analyses and simulations. The main academic motivation of this research was to study and synthesis the power of artificial intelligence techniques in controlling of non-linear dynamical systems with online-learning and adaptive capabilities. A model-based neural network adaptive controller is developed blending a self adaptive neural network module and a classical Proportional plus Derivative (PD)-like control to obtain optimum control performance by complementing each other. The adaptive neural module counteracts for inherent model discrepancies, strong nonlinearities and coupling effects.
item: Thesis-Full-text
Moisture control in fiber board manufacturing
Udakandage, T; Munasingha, R; Kumarawadu, S
In fiber board industry, the moisture content (the moisture level) of fiber, perhaps the most critical parameter of fiber board manufacturing, works as the medium of heat transfer across the fiber mat while subjected to pressing in the hot press. The high moisture content splits (delaminates) the wood panel when decompressing due to the release of high steam pressure develops inside it where as the low moisture content split the panel as a result of low heat transfer causing a low level curing of resin inside the panel. So controlling moisture is the most critical issue of the wood refiner operators which is a highly skill job that cannot be easily absorbed until having long time practice on it. The fiber moisture content is controlled inside the dryer by adjusting the dryer outlet temperature set point. This set point is automatically maintained by the valve position of the steam PRV (Pressure Regulating Valve) of the heat exchanger, the only energy source of the dryer. In very cool climate conditions the air and the environment get cold where the dryer outlet temperature cannot reach the required set point even though the PRV is at its 100% open condition. In 100% valve open condition the system is supplied with maximum heat energy that can be given and the only way to further increase the outlet temperature is to make a change in the process. This change is done by using three parameters namely the blow valve position, the refiner feed screw speed and the differential pressure. The mistakes in putting the correct set points and forgetting to put it on right time are human errors usually happen. This makes a heavy loss in the profit and restricts the consistency of the process. To avoid this problem, the process of controlling moisture is fully automated with the four parameters mentioned, using a cascaded PID system coupled with a multistage controller. The cascaded PID takes moisture as the reference set point that controls the outlet temperature and this in turn controls the steam PRV. At the time when the PRV is at 100% open position the other three parameters work together as a multi stage controller in increasing the outlet temperature.
item: Article-Abstract
Neural network-based optimal adaptive tracking using genetic algorithms
Kumarawadu, S; Watanabe, K; Kazuo, K; Izumi, K
This paper presents the use of neural networks (NNs) and genetic algorithms (GAs) to enhance the output tracking performance of partly known robotic systems. Two of the most potential approaches of adaptive control, i.e., the concept of variable structure control (VSC) and NN-based adaptive control, are ingeniously combined using GAs to achieve high-performance output tracking. GA is used to make the maximum use of different performance characteristics of two self-adaptive NN modules by finding the switching function which best combines them. The method will be valid for any rigid revolute robot system. Computer simulations on our active binocular head are included for illustration and verification.
item: Article-Abstract
Neuroadaptive Combined Lateral and Longitudinal Control of Highway Vehicles Using RBF Networks
Kumarawadu, S; Lee, TT
A neural network (NN) adaptive model-based combined lateral and longitudinal vehicle control algorithm for highway applications is presented in this paper. The controller is synthesized using a proportional plus derivative control coupled with an online adaptive neural module that acts as a dynamic compensator to counteract inherent model discrepancies, strong nonlinearities, and coupling effects. The closed-loop stability issues of this combined control scheme are analyzed using a Lyapunov-based method. The neurocontrol approach can guarantee the uniform ultimate bounds of the tracking errors and bounds of NN weights. A complex nonlinear three-degreeof- freedom dynamic model of a passenger wagon is developed to simulate the vehicle motion and for controller design. The controller is tested and verified via computer simulations in the presence of parametric uncertainties and severe driving conditions
item: Article-Abstract
Neuroadaptive Output Tracking of Fully Autonomous Road Vehicles With an Observer
Kumarawadu, S; Lee, TT
Automated vehicle control systems are a key technology for intelligent vehicle highway systems (IVHSs). This paper presents an automated vehicle control algorithm for combined longitudinal and lateral motion control of highway vehicles, with special emphasis on front-wheel-steered four-wheel road vehicles. The controller is synthesized using an online neural-estimator-based control law that works in combination with a lateral velocity observer. The online adaptive neural-estimator-based design approach enables the controller to counteract for inherent model discrepancies, strong nonlinearities, and coupling effects. The neurocontrol approach can guarantee the uniform ultimate bounds (UUBs) of the tracking and observer errors and the bounds of the neural weights. The key design features are 1) inherent coupling effects will be taken into account as a result of combining of the two control issues, viz., lateral and longitudinal control; 2) rather ad hoc numerical approximations of lateral velocity will be avoided via a combined controller–observer design; and 3) closed-loop stability issues of the overall system will be established. The algorithm is validated via a formative mathematical analysis based on a Lyapunov approach and numerical simulations in the presence of parametric uncertainties, as well as severe and adverse driving conditions
item: Thesis-Full-text
Obstacle avoidance for unmanned surface vehicles: simulations and experiments
Jayendra, RG; Kumarawadu, S
Sri Lanka ports authority and many other organizations are increasingly interested in the use of Unmanned Surface Vehicles (USV) for harbor security and surveillance applications. USVs can be used to collect information, samples and perform experiments inside a harbor or outside by. Navigating through ships and other objects. This research study is focused on finding algorithms for obstacle avoidance (OA) of USVs. The initial paradigm that is used to establish the solution was the OA of Unmanned Ground Vehicles (UGV). The algorithms developed for UGV were implemented practically with the limitations of hardware. Then, effort is taken to apply those algorithms to the surface vehicles with some modifications. In this study, a novel OA algorithm is proposed for static obstacles based on the Morphin algorithm. This proposed algorithm and the previous algorithm which is developed based on ground vehicles are compared with the potential field method. Static OA without dynamic OA is not helpful for unmanned vehicles on sea. A lot of researches have been carried out to avoid dynamic objects, but have failed to find an optimum solution although comparatively good approaches have been presented. Intelligent techniques have been rarely applied for dynamic obstacle avoidance. In this research, the effectiveness of applying intelligent or mathematical techniques for path prediction of dynamic obstacles is discussed with simulations to pick the best for a given situation. Then a noval projected dynamic obstacle area method is presented to avoid dynamic obstacles effectively. Comparative results are presented at the end to prove the strength "of the noval dynamic obstacle area method.