Aidil Azwin Zainul Abidin

Image processing of an agriculture produce: Determination of size and ripeness of a banana

Over the last several decades, customers’ lifestyles and needs have gone through tremendous changes. These changes are new challenges for the farmers whose produce has to meet the customers’ demands. The ability to classify agriculture produce based on size and quality is not only going to help the farmer but also the customer. This will help the farmer to grade the fruit, the seller to price it optimally and the customer value for money. Bananas are classified according to sizes, shapes, textures, colors and taste. The process of getting the size and ripeness of a banana is done from its image using the Image Processing Toolbox in MATLAB. These features are important to determine the optimal size and ripeness. From the size, the grade and type of the banana can be determined. The percentage of ripeness can be determined by evaluating the individual pixels of the image.

Agricultural produce Sorting and Grading using Support Vector Machines and Fuzzy Logic

Agriculture sector was accorded a very different treatment in the Ninth Malaysia Plan (9MP) where this sector is being revitalized to become a part of the economic growth engine. The Information and Communication Technology (ICT) application is going to be implemented as a solution in improving the status of the agriculture sector. The idea of integrating ICT with agriculture sector motivates the development of an automated system for sorting and grading of agriculture produce. Currently, the grading is done based on observations and through experience. The developed system starts the grading process by capturing the fruits image using a regular digital camera or mobile phone camera. Then, the image is transmitted to the processing level where feature extraction, classification and grading is done using MATLAB. In this paper, the focus is more on agricultural produce Sorting and Grading technique. The agricultural produce is classified based on fruit shape and size using Support Vector Machines (SVMs) and its grade is determined using Fuzzy Logic (FL) approach. The results obtained are very promising.

DSP based overcurrent relay using fuzzy bang–bang controller

Abstract Overcurrent relays are very important protection component that require high reliability to maintain high security in power systems. With the new numerical relay technology using digital signal processor (DSP), it is possible to improve the performance of the relay significantly. However, application of DSP in numerical overcurrent relays is limited especially in coordination among the group of relays. The relay must work proficiently to coordinate with the networks in order to avoid mal-operation. Therefore, in this paper, an implementation of overcurrent relay with improved coordination on a DSP, TMS320F2812 is described. The fuzzy bang–bang controller is used as the control strategy for the relay to provide efficient control for overcurrent protection. The performance evaluation of the proposed system is based on steady state analysis, transient state analysis, coordination and lastly the execution time of the DSP. The results obtained using this new proposed controller is very promising.

DSP based fuzzy and conventional overcurrent relay controller comparisons

Abstract Fuzzy logic control uses linguistic approach to solve complicated rules and ambiguous systems. This control strategy can be used to improve the overall performance of an overcurrent relay for power system protection compared to conventional relay. It is essential for a relay to work efficiently to trip the circuit breakers in the presence of faults and at the same time proficient to coordinate well with the networks to avoid mal-operation. There are two different types of fuzzy logic control strategies proposed for the relay, the Fuzzy Logic Controller (FLC) and Fuzzy Bang-Bang Controller (FBBC). The FBBC is the same as the conventional FLC except that the defuzzification method uses largest of maxima (LOM). Comparisons between the fuzzy controllers and conventional relay are based on IEC 255-3 standard. These relays are implemented on a DSP TMS320F2812 and their performance is evaluated which is based on operation time, DSP’s execution time and grading margin. The results obtained show a significant performance improvement compared to conventional relay.

Modelling of overcurrent relay using digital signal processor

Protective relays are used to detect any abnormalities in a power system and isolate the faulty section of the system in the shortest time, in order to minimize disturbances caused by failure in the system to ensure continuous power delivery. Protective relays for overcurrent protection are the most widely used relays in a power system. The implementation of overcurrent relay on digital signal processor (DSP) proficient to mitigate problems such as lack of memory capacity, lower speed and functionality, compared to conventional approach using microprocessor. The modelling of overcurrent relay for inverse definite minimum time (IDMT) type using DSP board TMS320F2812 will be discussed in the paper. Simulation results of the overcurrent relay from MATLAB/ Simulink and execution on TMS320F2812 will be presented.

Tuning of a new fuzzy bang?bang relay controller for attitude control system

A new fuzzy bang-bang relay controller (FBBRC) is introduced in this paper. The new controller is inherently optimal due to its bang-bang property. The controller has fuzzy decision-making capability in its inputs and have two fixed levels bang-bang output. Consequently, the tuning of FBBRC is restricted to input parameters only in comparison to standard fuzzy logic controller (FLC) where the output parameters can also be tuned. The stability of new controller stems from well-established bang-bang sliding mode control theory. The work presented here demonstrates that tuning the inputs of the proposed FBBRC is more effective and simpler than tuning all the parameters of standard FLC. The two controllers are tuned online with gradient descent optimisation method and tested for regulator and tracking mode control. Simulation result shows that new controller has faster response time and is capable of controlling the system under adverse initial conditions.

Determination of overcurrent time delay using fuzzy logic relays

The inverse definite minimum time relay has been used in the power distribution system in order to protect the system from power system faults.[1] These relays will function after a certain time delay when the current going through the relay exceeds a predefined set point. This time delay depends on the ratio of the fault current flowing through the relay with the setpoint current defined by the protection engineer[2]. The basic problem with these relays is that the relays will have a longer time delay for a less severe fault[3]. Another problem that these relays would face is when the impedence between the backup relay and the main relay is much smaller than the impedence between the fault and the main relay. In this paper, the possibility of using a fuzzy logic controller(FLC) is studied in order to determine the time delay of the overcurrent relay.

Digital Signal Processor Based Over-current Relay Using Fuzzy Logic Controller

Abstract Protection and control are important aspects in real-time applications. Protection and control are required to ensure that safety and security of the system is achieved. In a power system, protection relays are used to minimize the disturbances caused by failure in the system to ensure continuous power delivery. Protection relays, such as over-current relays, are required to improve their reliability, since the power system is seriously affected by the faults either caused by internal or external sources. The relay must work efficiently to trip the circuit breakers if there are faults present. In this article, an over-current relay is designed based on fuzzy logic control to improve the overall performance of the relay. The over-current relay is implemented on a digital signal processor (TMS320F2812, Texas Instruments, Dallas, Texas, USA). The relay performance was compared with the IEC standard, and the results obtained are promising.

A novel hybrid method of LSSVM-GA with multiple stage optimization for electricity price forecasting

Predicting price has now become an important task in the operation of electrical power system. Day-ahead prediction provides forecast prices for a day ahead that is useful for daily operation and decision-making. The main challenge for day ahead price forecasting is the accuracy and efficiency. Lower accuracy is produced due to the nature of electricity price that is highly volatile compared to load series. Hence, some researchers have developed complex procedures to produce accurate forecast while considering significant features and optimum parameters. Therefore, a multistage optimization for hybrid Least Square Support Vector Machine (LSSVM) and Genetic Algorithm (GA) model is developed in this study to provide an accurate price forecast with optimized parameters and input features. So far, no literature has been found on multistage feature and parameter selections using the methods of LSSVM-GA for day-ahead price prediction. All the models are examined on the Ontario power market; which is reported as among the most volatile market worldwide. A huge number of features are selected by two stages of optimization to avoid from missing any important features. The developed LSSVM-GA shows higher forecast accuracy with lower complexity than the existing models.

Cross phase polarization algorithm for fault direction determination using zero crossing method to determine phase difference

Power systems are usually connected in a condition where there is more than one power supply or voltage source supplying a load. These systems will have protection relays to protect various equipment connected to the system. However in isolating a fault, the direction of the fault needs to be known in order to limit the amount of loss load. This paper shall describe a possible algorithm that could be used in order to perform cross phase polarization. The possible faults that could be detected using this technique include the single phase to ground fault, the phase to phase fault and the double phase to ground fault. Three phase faults require the memory polarization technique that will not be discussed in this paper. The algorithm shall be implemented and tested using the sim power system tool box present in MATLAB.