20 research outputs found
DESAIN SENSOR KECEPATAN BERBASIS DIODE MENGGUNAKAN FILTER KALMAN UNTUK ESTIMASI KECEPATAN DAN POSISI KAPAL
No full textMakalah ini membahas design sensor kecepatan dengan menggunakan diode 1N4001 untuk mengestimasi kecepatan dan posisi kapal. Rangkaian seri dua diode dipanaskan oleh heater dan kecepatan angin akan mendinginkan diode. Perubahan karakteristik tegangan diode terhadap suhu akan dimanfaatkan sebagai sensor kecepatan. Output sensor selanjutnya akan diperbaiki linearitasnya dengan analog signal processing circuit. Untuk mengatasi noise yang timbul dalam proses pengukuran dan meningkatkan kehandalan sensor serta untuk estimasi kecepatan dan posisi kapal digunakan filter Kalman. Hasilnya menunjukkan bahwa filter Kalman dapat mengestimasi kecepatan dan posisi kapal dengan cukup akurat. Karena menggunakan diode standar 1N4001 (bukan diode thermal), maka kemampuan sensor hanya sampai kecepatan 10 m/s atau 36 km/jam
Implementasi Metode PSO-LDW untuk Optimasi Kontroler PID
No full textKontroler PID adalah kontroler yang paling populer abad ini karena efektifitasnya luar biasa, implementasinya sederhana dan aplikasinya sangat luas. Namun, dalam prakteknya tuning kontroler PID merupakan suatu persoalan tersendiri yang tidak mudah dan umumnya masih dilakukan secara manual yang memerlukan cukup waktu, terlebih untuk sistem atau plant orde tinggi. Makalah ini membahas teknik tuning kontroler PID menggunakan metode PSO-LDW (Particle Swarm Optimization-Linear Decreased Weight), yaitu metode PSO yang dimodifikasi (Modified PSO) , dimana parameter bobot inersia dibuat menurun secara linear. Metode PSO-LDW memiliki beberapa keunggulan dibandingkan metode PSO standar, yaitu konvergensinya lebih cepat dan total performansi indeksnya lebih baik. Sistem atau plant orde tinggi dimodelkan dalam Simulink dan algoritma PSO-LDW diimplemenntasikan dalam MATLAB. Hasil simulasi menunjukkan bahwa metode PSO-LDW menghasilkan performansi sistem yang lebih baik dibandingkan dengan metode PSO standar maupun metode sebelumnya
A MODIFIED PARTICLE SWARM OPTIMIZATION WITH RANDOM ACTIVATION FOR INCREASING EXPLORATION
No full textParticle Swarm Optimization (PSO) is a popular optimization technique which is inspired by the social behavior of birds flocking or fishes schooling for finding food. It is a new metaheuristic search algorithm developed by Eberhart and Kennedy in 1995. However, the standard PSO has a shortcoming, i.e., premature convergence and easy to get stack or fall into local optimum. Inertia weight is an important parameter in PSO, which significantly affect the performance of PSO. There are many variations of inertia weight strategies have been proposed in order to overcome the shortcoming. In this paper, a new modified PSO with random activation to increase exploration ability, help trapped particles for jumping-out from local optimum and avoid premature convergence is proposed. In the proposed method, an inertia weight is decreased linearly until half of iteration, and then a random number for an inertia weight is applied until the end of iteration. To emphasis the role of this new inertia weight adjustment, the modified PSO paradigm is named Modified PSO with random activation (MPSO-RA). The experiments with three famous benchmark functions show that the accuracy and success rate of the proposed MPSO-RA increase of 43.23% and 32.95% compared with the standard PSO.</jats:p
Research of intelligent self-tuning PID control using enhanced particle swarm optimization for ultrasonic motor
No full textResearch of intelligent self-tuning PID control using enhanced particle swarm optimization for ultrasonic motor
No full text博士(工学)山口大学Yamaguchi Universit
Sistem Pendaratan Otomatis pada Quadcopter menggunakan Sliding Mode Controller
No full textA quadcopter has a very nonlinear system characteristic that is influenced by unexpected disturbances such as the influence of wind that reflected off the ground when taking off or landing. Therefore, a robust control strategy is needed to improve the quadcopter performance. In this study, the control strategy is used to resolve outdoor automatic landing problems in a stable manner using the Sliding Mode Control (SMC) algorithm. The quadcopter has six degrees of freedom (6-DoF) with only four independent inputs, this makes it impossible to control 6-DoF directly and simultaneously. To handle this, the proposed structure is a multilevel control structure, inner loop dan outer loop controller. The Inner loop controls the rotational dynamics subsystem (3-DoF), while the outer loop controls the translational dynamics subsystem (3-DoF) which is designed in conjunction with the generation of attitude angle set-point. With the concept of automatics landing can reduce the risk of accidents on a quadcopter. The SMC technique on an automatics quadcopter landing shows the results with an error in roll of ± 0.05 radians, pitch ± 0.03 radians, yaw less than 0.3 radians, and translational movements the z-axis is ± 0.2 meters
A MODIFIED PARTICLE SWARM OPTIMIZATION WITH RANDOM ACTIVATION FOR INCREASING EXPLORATION
No full textParticle Swarm Optimization (PSO) is a popular optimization technique which is
inspired by the social behavior of birds flocking or fishes schooling for finding food.
It is a new metaheuristic search algorithm developed by Eberhart and Kennedy in
1995. However, the standard PSO has a shortcoming, i.e., premature convergence
and easy to get stack or fall into local optimum. Inertia weight is an important
parameter in PSO, which significantly affect the performance of PSO. There are
many variations of inertia weight strategies have been proposed in order to overcome
the shortcoming. In this paper, a new modified PSO with random activation to
increase exploration ability, help trapped particles for jumping-out from local
optimum and avoid premature convergence is proposed. In the proposed method, an
inertia weight is decreased linearly until half of iteration, and then a random number
for an inertia weight is applied until the end of iteration. To emphasis the role of this
new inertia weight adjustment, the modified PSO paradigm is named Modified PSO
with random activation (MPSO-RA). The experiments with three famous benchmark
functions show that the accuracy and success rate of the proposed MPSO-RA increase
of 43.23% and 32.95% compared with the standard PSO
DESAIN SENSOR KECEPATAN ANGIN DENGAN KONTROL ADAPTIF UNTUK ANEMOMETER TIPE THERMAL
No full textThermal anemometer merupakan alat ukur kecepatan angin yang sering digunakan oleh BMKG, used this instrument to measure the wind speed environment. Thermal Anemometer have been made by arif harianto ( 2005) using series with diode and heater, this configuraton take no account of the influence of wind temperature in measurement process ( type CTA). this Appliance Weakness is wind temperature very influencing process in measurement of wind speed also have the low measure boundary. The problems overcome by using two censor of temperature LM 35. The First sensor to measure the wind speed and secondly as kompensator temperature of environment, so that the instrument can adapt to change of temperature environment. Maximum limit this measurement system is 6.9 m / s because its limitation wind source of available. While to increase respon time system at measurement proccess used Integral Proposional ( PI) Controller. Without controller (open Loop) approach the result of knowable new measurement after 50 second, by using PI controller after 15 second. Data process have done by mikrokontroller ATMEGA 16. Measurement result of this instrument is appeare in LCD character. Keyword: Thermal Anemometer, sensor of temperature LM35, ATMEGA 16, PI Controlle
Frequency prediction of maximum radiated emission due to ground-bounce from resonance resistances of PCB power-ground planes
No full textModified Particle Swarm Optimization using Nonlinear Decreased Inertia Weight
No full textParticle Swarm Optimization (PSO) has demonstrated great performance in various optimization problems. However, PSO has weaknesses, namely premature convergence and easy to get stuck or fall into local optima for complex multimodal problems. One of the causes of these weaknesses is unbalance between exploration and exploitation ability in PSO. This paper proposes a Modified Particle Swarm Optimization (MPSO) using nonlinearly decreased inertia weight called MPSO-NDW to improve the balance. The key idea of the proposed method is to control the period and decreasing rate of exploration-exploitation ability. The investigation with three famous benchmark functions shows that the accuracy, success rate, and convergence speed of the proposed MPSO-NDW is better than the common used PSO with linearly decreased inertia weight or called PSO-LDW
Keywords: particle swarm optimization (PSO), premature convergence, local optima, exploration ability, exploitation ability
