Pembelajaran sistem pangkalan peraturan kabur menggunakan algoritma genetik mempunyai masa depan yang cerah bagi menyelesaikan beberapa masalah. Lojik kabur menawarkan cara sederhana bagi menyimpulkan maklumat input yang kasar, kabur, cacat atau tidak jelas. Model lojik kabur adalah berasaskan kaedah–kaedah empirik bergantung kepada pengalaman operator berbanding dengan pengetahuan teknikal daripada sistem. Dalam metod lojik kabur, sebarang input yang munasabah dapat diproses dan sebilangan output dapat dijana meskipun penakrifan pangkalan peraturan secara cepat dapat menjadi rumit sekiranya terlalu banyak input dan output yang dipilih untuk sebuah penggunaan. Bergantung kepada sistem, semakin rumit input dan output yang ingin diselesaikan oleh sistem, maka akan semakin banyak jumlah bilangan peraturan dan kerumitan tetapi juga akan menambah mutu kawalan dari sistem. Banyak kaedah telah dicadangkan bagi menjana peraturan kabur. Idea asas daripada penyelidikan ini adalah untuk mempelajari serta menjana peraturan paling optimum yang diperlukan bagi mengawal input tanpa mengurangi mutu kawalan. Kertas kerja ini yang mencadangkan penjanaan peraturan kabur menggunakan penggugusan subtraktif pada lojik kabur Takasi–Sugeno–Kang (TSK) bagi kegunaan kawalan lampu isyarat lalu lintas. Kata kunci: Lojik kabur TSK, sistem pangkalan peraturan kabur, teknik penggugusan subtraktif Learning fuzzy rule–based systems with genetic algorithms can lead to very useful descriptions of several problems. Fuzzy logic (FL) provides a simple way to arrive at a definite conclusion based upon vague, ambiguous, imprecise, noisy or missing input information. The FL model is empirically based, relying on an operator’s experience rather than their technical understanding of the system. In the FL method, any reasonable number of inputs can be processed and numerous outputs will be generated, although defining the rule–base quickly becomes complex if too many inputs and outputs are chosen for a single implementation since rules defining their interrelations must also be defined. This will increase the number of fuzzy rules and complexity but may also increase the quality of the control. Many methods were proposed to generate fuzzy rules–base. The basic idea is to study and generate the optimum rules needed to control the input without compromising the quality of control. The paper proposed the generation of fuzzy rule base by subtractive clustering technique in Takagi–Sugeno–Kang (TSK) fuzzy method for traffic signal control system. Key words: TSK fuzzy logic, fuzzy rule base system, subtractive clustering technique

This research was conducted to realize a nutrient solution concentration control system using web interface monitoring. The hydroponic system only relies on nutrient solutions whose nutrient levels must be maintained to anticipate the increase in acidic acid levels of the nutrient solutions. The provision of monitoring and recording changes in hydroponic system nutrition is very helpful in maintaining the quality of hydroponic agricultural production. The provision of data from electrical power measurements needs to be supported by information technology, especially remote data measurement technology. This remote data monitoring uses a wireless network system using a TDS (Total Dissolved Solids) sensor, Arduino DUE microcontroller, WiFi module and internet connection for the observation process. The TDS sensor used previously was characterized and calibrated. The data obtained by the sensor is used to exercise control before sending it to the thingspeak.com channel to be recorded and displayed in realtime. In testing the sensor TDS meter error of 2.88%. The results of the test for 2 hours obtained the results of the control system can increase the nutritional PPM from 213 PPM to 451 PPM within 30 seconds with a nutrient enhancer sample of 779 PPM, and decrease from 779 PPM to 431 PPM within 70 seconds with a water-enhancing sample of 213 PPM for the 445 PPM set point. In the second test result for 2 hours, the control system results can increase the nutritional PPM from 215 PPM to 814 PPM within 30 seconds with a nutrient enhancer sample of 956 PPM, and decrease from 956 PPM to 754 PPM within 40 seconds with a water-enhancing sample of 215 PPM for the 780 PPM set point. PPM value of nutrients can be affected by the presence of other solids such as sand which dissolves with water.

Real–time road traffic data analysis is the cornerstone for the modern transport system. The real–time adaptive traffic signal control system is an essential part for the system. This analysis is to describe a traffic scene in a way similar to that of a human reporting the traffic status and the extraction of traffic parameters such as vehicle queue length, traffic volume, lane occupancy and speed measurement. This paper proposed the application of two–stage neural network in real–time adaptive traffic signal control system capable of analysing the traffic scene detected by video camera, processing the data, determining the traffic parameters and using the parameters to decide the control strategies. The two–stage neural network is used to process the traffic scene and decide the traffic control methods: optimum priority or optimum locality. Based on simulation in the traffic laboratory and field testing, the proposed control system is able to recognise the traffic pattern and enhance the traffic parameters thus easing traffic congestion more effectively than existing control systems. Key words: Urban traffic control system, pattern recognition, two-stage neural network, adaptive control system

This paper presents the design process of a synchronous motor of crane system using vector control of line starting [1]. The preliminary design is d-q model armature rotor line start synchronous motor with vector control for decreasing a starting current and torque. The design allows the synchronous motor to operate at both starting and synchronous speed. The basic equations for park transformation of the rotor-stator for proposed vector control to synchronous motor are presented [2]. The starting performance of synchronous motor, for example in crane application, requires rapid dynamics and precise regulation; hence the need of direct control is becoming an urgent demand. This type of control providesanindependent vector control of torqueand current, whichis similar to a separatelyexcited synchronous motor and offersa number ofattractivefeatures. Synchronous motorhasahighstartingtorquewhileseparately synchronous motorcanoperate abovethebase low speedinthe line starting current [3]. This paper designs study and highlights the effectiveness of the  proposed vector control methods for a line starting performance of synchronous motor model parameter, using a fuzzy logic controller methods both simulation and manufacturers measured experimental data. Asteady state and transient analysis of the synchronous motor is performed belowand abovebase line starting current.

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