This study presents a speed controller design for a switched reluctance (SR) motor in order to achieve minimum torque ripple and high control performance. First of all, SR motor convertor designed for soft chopping is chosen. This converter as well as producing less torque ripple, provides more degrees of freedom for SR motor drive controller. A PID, Fuzzy PID, Neural Networks controller and a switching algorithm for turn-on and turn-off degree of each phase of motor form speed control loop of SR motor drive. The primary parameters of controller are achieved by trial and error. But eventually an optimization algorithm to reach the goals and constraints in different set points is defined and its parameters are optimized with a Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Ant colony Optimization (ACSO). This algorithm optimized the turn-on and turn-off degrees of each phase, the parameters of PID controller in transient state, and parameters of PID controller that considered for reducing the torque ripple in steady state. An Comparative study of the all the models and best among the controllers is proposed. The proposed control algorithm was simulated using MATLAB / Simulink software package and an application example of 6/4 SRM to validate the performance of designed algorithm.
This Paper presents a particle swarm optimization (PSO) method for determining the optimal proportional-integral derivative (PID) controller parameters, for speed control of a linear brushless DC motor. The proposed approach has superior features, including easy implementation, stable convergence characteristic and good computational efficiency. The brushless DC motor is modeled in Simulink and the PSO algorithm is implemented in MATLAB. Comparing with Genetic Algorithm (GA) and Linear quadratic regulator (LQR) method, the proposed method was more efficient in improving the step response characteristics such as, reducing the steady-states error; rise time, settling time and maximum overshoot in speed control of a linear brushless DC motor. The ACSA approach has superior features, including easy implementation, stable convergence characteristic and good computational efficiency. The brushless DC motor is modeled in Simulink and the ACSA is implemented in MATLAB. Comparing with Genetic Algorithm (GA) and Linear quadratic regulator (LQR) method, the proposed method was more efficient in improving the step response characteristics such as, reducing the steady-states error; rise time, settling time and maximum overshoot in speed control of a linear brushless DC motor.
This paper deals with speed control of motor using two soft computing techniques. PMSM widely used in high performance motion control applications. The field-oriented or vector control is used in the design of PMSM to achieve smooth starting and acceleration. In practical application lead to degradation of the performance due to electromechanical parameter variations and external load disturbances. To improve performance of the PMSM, Fuzzy-PID with ACO and PSO based advanced control technique with methods are proposed. The proposed approach is to enhance the control effort of PMSM using soft computing techniques. Artificial intelligence techniques have been incorporated in the controller architecture to overcome the maximum settling time and rise time problems.
Indonesia is a country that a lot of valleys, hills and volcanoes. So every year, Indonesia many natural disasters landslides. A landslide is the movement of slope-forming materials such as rocks, debris material, soil, or a mixture of materials, moving down or off the slopes. This research tries to build an early warning system of landslides using microcontroller ATMEGA8535. At ground shifted over 4 cm then this system will sound sirens and danger will contact the village to evacuate its citizens. The results showed that for a landslide early warning system based on microcontroller ATMEGA8535 work well with a resolution of 2 mm shift ground.
The purpose of this paper is to analyze the fact that a learning group is a combination of different types of learners and a teacher should first find out each learners individual style of learning and then mold his teaching style according. A group of 200 students were selected through random sampling for purpose of this research. The questionnaire used (VAK Learning Styles Self-Assessment Questionnaire by Chislett and Chapman, 2005) consisted of 30 objective type questions. The purpose of this questionnaire was to find out the ratio of auditory, visual, kinesthetic or a combination style learners in a degree level class room. The data of the questionnaire was analyzed through MS Excel by calculating the percentage for the frequency counts in respect of each category of the responses i.e auditory, visual or kinesthetic.
This paper proposes evaluation model for building Learning Content Management System (LCMS) in Riyadh City universities. A literature and a practical survey of web development methodologies have been conducted to identify LCMS readiness in Riyadh city universities. The framework is evaluated by e-learning AHP evaluation model, which is proposed by Francesco Colace in 2006. The evaluation model is evaluating four main features (management, collaborative approach, Management of interactive learning objects and Adaptation of learning path). Every feature involves, in their determination, some sub-features. The results of evaluation model are outlined as follows: Total weights of the proposed framework in management feature is 16.7/25, in collaborative feature is 9/10, in adaption learning path is 5.5/10 and in interactive learning object is 5/5. The total weights of all features are 36.2/50. In this study an evaluation model was applied on Riyadh City universities like KSU, IMAMU, NAUSS, YU, KFU and PSU. Then, the results were compared with each other. The total weighs of each of KSU and PSU was 41. While the total weights of KFU, IMAMU, YU and NAUSS was 40, 37,36 and 32, respectively. Evaluation process shows that the proposed framework satisfied the objectives and the required functions of this work.
The development of Wireless Body Area Networks (WBANs) has significantly improved the quality of personal health care whilst enhancing the quality of life. A critical factor in the acceptance of WBANs is providing appropriate security and privacy protection of the wireless communication. It is a challenge to implement traditional security infrastructures in these types of lightweight networks, since they are by design limited in both computational and communication resources. \n In this paper, we propose to use the QRS Complex to generate and distribute securely and efficiently symmetric session keys to constituent sensors in WBAN with very high fidelity of key recoverability.
More personal software is our permanent goal. This means that more people should be\nconcerned with cryptography. We think that the encoding of cryptographic algorithms is an\nimportant step in it.\nIn this paper, our choice is encoding operation “Point doubling” on an Elliptic curve, over\nfinite field Fp (E(FP)), where p is odd prime, in order to intensify interest in ECC-Ellipse\ncurve cryptography.