Traffic light dispersion control based on deep reinforcement learning

The current traffic light controls are ineffective and causes a handful of problems such as congestion and pollution. This study investigates the application of deep reinforcement learning on traffic control systems to minimize congestion at traffic intersection. The traffic data from Pulai Perdana, Skudai, Johor Intersection was extracted, analysed and simulated based on the Poisson Distribution, using a simulator, Simulation of Urban Mobility (SUMO). In this research, we proposed a deep reinforcement learning model, which combines the capabilities of convolutional neural networks and reinforcement learning to control the traffic lights to increase the effectiveness of the traffic control system. The paper explains the method we used to quantify the traffic scenario into different matrices which fed to the model as states which reduces the load of computing as compared to images. After 2000 iterations of training, our deep reinforcement learning model was able to reduce the cumulative waiting time of all the vehicles at the Pulai Perdana intersection by 47.31% as compared to a fixed time algorithm and can perform even when the traffic is skewed in a different direction. When the traffic is scaled down to 50% and 20 %, the agent continues to improve the waiting time by 69.5% and 68.36 % respectively. It is proven in the experiment that a deep reinforcement learning model was able to reduce the cumulative waiting time at Pulai Perdana by 47.31%

Automatic Initialization System for Home-based Robotics Service Environment

芝浦工業大学201

Investigation of the Effect Temperature on Photovoltaic (PV) Panel Output Performance

The main limit of PV systems is the low conversion efficiency of PV panels, which is strongly influenced by their operating temperature. Lack of accuracy in consideration through PV panel temperature increases the financial risk of system installation. This present study investigates the effects of operating temperature on monocrystalline PV panel at Perlis, Malaysia. A selected model of PV panel firstly was simulated using PVSYST software in order to evaluate its output performance. Meanwhile, PROVA 200 used to measure and record all electrical data for outdoor experimental during the sunniest day. Besides, the thermal distribution was analysed through PV panel temperatures and thermal imaging. Simulation results implied that the output power of PV panel decreases with increasing of its working temperature followed by the efficiency. The experimental results obviously show that the STC parameters do not represent the real operating conditions of PV panel for outdoor conditions. Less output power was produced affected by the atmospheric factors such as solar irradiance and ambient temperature. These both factors strongly affected the PV panel temperature distribution. In short, the elevating of PV panel temperature contributed to the negative impact on output performance of the panel

Temperature Distribution of Three-Dimensional Photovoltaic Panel by Using Finite Element Simulation

The low electricity performance of a photovoltaic (PV) panel has been concerned in the PV application system. The effect of environmental and operating condition was affected the performance of the PV panel. In this research work, the main objective is to perform a three-dimensional geometry model of monocrystalline silicon PV panel with and without cooling system by using finite element method. In the case of a cooling system, the effect of the Direct Current (DC) fan flow rate on the temperature distribution of PV panel was investigated. The electrical behaviour of this PV panel is obtained based on the average temperature of the PV panel obtained and average solar irradiance from site location. According to the experimental results, PV panel with cooling system can be significant to provide better performance than the PV panel without cooling system in the same environmental condition. For the effect of flow rate of DC fan in the PV panel with cooling system, the performance of this PV panel has been improved as increasing in flow rate of DC fan

Cooling on Photovoltaic Panel Using Forced Air Convection Induced by DC Fan

Photovoltaic (PV) panel is the heart of solar system generally has a low energy conversion efficiency available in the market. PV panel temperature control is the main key to keeping the PV panel operate efficiently. This paper presented the great influenced of the cooling system in reduced PV panel temperature. A cooling system has been developed based on forced convection induced by DC fan as cooling mechanism. DC fan was attached at the back side of PV panel will extract the heat energy distributed and cool down the PV panel. The working operation of DC fan controlled by PIC18F4550 microcontroller which depending on the average value of PV panel temperature. Experiments were performed with and without cooling mechanism attached at the backside PV panel. The whole PV system was subsequently evaluated in outdoor weather conditions. As a result, it is concluded that there is an optimum number of DC fans required as cooling mechanism in producing efficient electrical output from a PV panel. The study clearly shows how cooling mechanism improves the performance of PV panel at the hot climatic weather. In short, the reduction of PV panel temperature is very important to keep its performance operated efficiently

Analysis Air Cooling Mechanism for Photovoltaic Panel by Solar Simulator

Measurement the outdoor efficiency of photovoltaic (PV) panels is essential, but it is not likely an exceptional circumstance at any given moment is always repeating itself. A solar simulator was designed and fabricated for the purpose of analyzing the performance of PV panel with and without an air cooling mechanism in indoor test. Twenty units of 500 W halogen lamps with build-in reflector support by the steel structure holder act as a natural sunlight. The uniformity of the solar radiation was measured in the test area. Two units of PV panel with same characteristics were experimental in three sets of uniformity of solar radiation, which are 620, 821 and 1016 W/m². The operating temperature of PV panel with an air cooling mechanism can be decreased 2-3 ˚C compared to PV panel reference. The PV panel with an air cooling mechanism can be increased in 3-7 % of maximum power output based on solar radiation. An overall method and procedure of the measurement by the solar simulator are discussed and proposed

Intelligent cuckoo search algorithm of PID and skyhook controller for semi-active suspension system using magneto-rheological damper

This article introduces the application of the Cuckoo Search (CS) Algorithm to tune Proportional-Integral-Derivative (PID) and Skyhook controller for the semi-active (SA) suspension system further to improve the vehicle's ride comfort and stability. Meanwhile, the PID-CSA and Skyhook-CSA intelligent approaches have been compared to the passive suspension system. The performance of the PID controller and Skyhook controller are optimised by Cuckoo Search (CS) Algorithm, respectively. The system's mean square error (MSE) is defined as the objective function for optimising the proposed controllers. The performance of the proposed PID-CSA and Skyhook-CSA controllers are evaluated with the passive suspension system in the form of body acceleration, body displacement, and tire acceleration. The sinusoidal road profile is set as the disturbance of this system. The percentage improvement for body acceleration and body displacement achieved about 25% for the PID-CSA controller and 1-4% for Skyhook-CSA. These simulated results reflect that the proposed controllers outperformed other considered methods to obtain the most effective vehicle stability and ride comfort

Semi-active suspension system using MR damper with PSO skyhook and sensitivity analysis of PID controller

This paper introduces the use of Particle Swarm Optimization (PSO) algorithm to tune Skyhook controller & Sensitivity Analysis method to tune PID controller for semi-active suspension system in furtherance of increasing and enhancing the ride comfort and vehicle stability. The performance of skyhook and PID controller are optimized by PSO and Sensitivity Analysis respectively. The mean square error (MSE) of the system is set as an objective function for optimization process of the proposed controller. The performances of proposed controllers are compared with the passive system in terms of sprung displacement & sprung acceleration. The bump & hole and random road profile is set as a disturbance of the system. The simulated results reflect that the proposed controllers offer a significant improvement in ride comfort and vehicle stability

Synthesis and characterization of nickel boride nanoparticles for energy conversion catalyst materials – the effect of annealing temperature

In the recent technology development, fuel cell has been widely used in many applications, including transportation and industry. Platinum catalysts are used to catalyst the reaction at the oxygen electrode, but they are expensive and has limited supply. A nickel-boron nanoparticle catalyst is proposed as a substitute for fuel cell catalyst material. The objectives are to evaluate the effect of the annealing process and to determine the characteristics of the annealed nanoparticles using scanning electron microscopy - energy dispersive X-ray (SEM-EDS), inductively coupled plasma optical emission spectroscopy (ICP-OES) analysis, total organic carbon (TOC) analysis and X-ray diffraction (XRD). A wet chemical method was used to synthesize nickel-boron nanoparticles by chemical reduction (co-reduction) of nickel chloride and sodium borohydride. As-synthesized nickel-boron nanoparticles were annealed at temperatures of 200, 300, 400, 500, and 700 °C in an argon atmosphere for 2 h. From the experimental results, nickel-boron nanoparticles annealed at 300 °C with equal dispersion of crystalline Ni and crystalline Ni3B showed the highest catalyst performance. The yield of nickel-boron nanoparticles sized 1.1364 nm was smaller than in the literature (37 nm). The size of Ni-B nanoparticles was calculated by using the Scherrer equation with the values of full width half maximum (FWHM) obtained by peak fitting following the Gaussian model. Smaller Ni-B nanoparticles have a higher surface-area-to-volume ratio, which increases the exposure of the active sites (crystalline Ni and crystalline Ni3B phase) to the reactants (methanol) and improves catalytic activity

Vibration suppression of hard disk drive mechanism using intelligent active force control

One of the key performances of a Hard Disk Drive (HDD) system is its ability to control or suppress the vibration occurred. This paper focuses on the implementation of an intelligent active force control (IAFC) technique applied to the HDD dynamics in order to suppress the vibration induced in the system via a simulation study using MATLAB and Simulink. The performance of the IAFC system incorporating a fuzzy logic (FL) component is compared to the traditional proportional-integralderivative (PID) control system in terms of tracking performance and system robustness in countering the disturbances. The results from the study affirm the superiority of the proposed technique over its counterpart