25 research outputs found
Nature-inspired algorithms for vibration control of flexible plate structures
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Smart Semi-active PID-ACO control strategy for tower vibration reduction in Wind Turbines with MR damper
No full textWind turbine technology is well known around the globe as an eco-friendly and effective renewable power source. However, this technology often faces reliability problems due to structural vibration. This study proposes a smart semi-active vibration control system using Magnetorheological (MR) dampers where feedback controllers are optimized with nature-inspired algorithms. Proportional integral derivative (PID) and Proportional integral (PI) controllers are designed to achieve the optimal desired force and current input for MR the damper. PID control parameters are optimized using an Ant colony optimization (ACO) algorithm. The effectiveness of the ACO algorithm is validated by comparing its performance with Ziegler-Nichols (Z-N) and particle swarm optimization (PSO). The placement of the MR damper on the tower is also investigated to ensure structural balance and optimal desired force from the MR damper. The simulation results show that the proposed semi-active PID-ACO control strategy can significantly reduce vibration on the wind turbine tower under different frequencies (i.e., 67%, 73%, 79% and 34.4% at 2 Hz, 3 Hz, 4.6 Hz and 6 Hz, respectively) and amplitudes (i.e. 50%, 58% and 67% for 50 N, 80 N, and 100 N, respectively). In this study, the simulation model is validated with an experimental study in terms of natural frequency, mode shape and uncontrolled response at the 1st mode. The proposed PID-ACO control strategy and optimal MR damper position is also implemented on a lab-scaled wind turbine tower model. The results show that the vibration reduction rate is 66% and 73% in the experimental and simulation study, respectively, at the 1st mode. © 2019, Institute of Engineering Mechanics, China Earthquake Administration
Effectiveness of Nature-Inspired Algorithms using ANFIS for Blade Design Optimization and Wind Turbine Efficiency
No full textBlade design of the horizontal axis wind turbine (HAWT) is an important parameter that determines the reliability and efficiency of a wind turbine. It is important to optimize the capture of the energy in the wind that can be correlated to the power coefficient ( C p ) of HAWT system. In this paper, nature-inspired algorithms, e.g., ant colony optimization (ACO), artificial bee colony (ABC), and particle swarm optimization (PSO) are used to search for the blade parameters that can give the maximum value of C p for HAWT. The parameters are tip speed ratio, blade radius, lift to drag ratio, solidity ratio, and chord length. The performance of these three algorithms in obtaining the optimal blade design based on the C p are investigated and compared. In addition, an adaptive neuro-fuzzy interface (ANFIS) approach is implemented to predict the C p of wind turbine blades for investigation of algorithm performance based on the coefficient determination (R2) and root mean square error (RMSE). The optimized blade design parameters are validated with experimental results from the National Renewable Energy Laboratory (NREL). It was found that the optimized blade design parameters were obtained using an ABC algorithm with the maximum value power coefficient higher than ACO and PSO. The predicted C p using ANFIS-ABC also outperformed the ANFIS-ACO and ANFIS-PSO. The difference between optimized and predicted is very small which implies the effectiveness of nature-inspired algorithms in this application. In addition, the value of RMSE and R2 of the ABC-ANFIS algorithm were lower (indicating that the result obtained is more accurate) than the ACO and PSO algorithms
IQRA' : Bil 7 : Julai 2017 / Perpustakaan Tun Abdul Razak, UiTM
Get PDFAntara isi kandungan: 1. Seminar kepustakawanan 2017 kelestarian kecemerlangan, 2. Pameran penjagaan persekitaran kita amalan mulia, 3. Kumpulan inovatif kreatif (KIK) i-Team, 4. Lawatan kerja wakil dari German Malaysian Institute (GMI) @ PTAR, 5. Majlis sambutan hari raya aidilfitri PTAR 2017, 6. Taklimat lawatan kepada pelajar Universitas Airlanggar (UNAIR), Surabaya, Indonesia, 7. Bengkel penyediaan dokumen ISO 9001:2015, 7. Program pengenalan amalan persekitaran berkualiti melalui amalan 5S dan amalan 3R, 8. Lawatan kerja ke unit penjanaan kewangan, Perpustakaan Tun Sri Lanang, Universiti Kebangsaan Malaysia (UKM), 9. Taklimat pengurusan arkib dan rekod di unit arkib UiTM Cawangan Zon Utara, 10. Majlis sambutan raya, hari lahir dan persaraan Staf, 11. Pameran sukan untuk kesihatan, 12. Promosi: Library bingo, 13. Taklimat arkib ke perpustakaan Dato' Jaafar Hassan, UiTM Cawangan Perlis, 14. Gotong royong majlis hari raya aidilfitri 2017 Perpustakaan Tun Abdul Razak (PTAR) Pulau Pinang, 15. Bengkel pangkalan data 2017, Perpustakaan Tun Abdul Razak (PTAR) Cawangan Perak, 16. Majlis sambutan aidilfitri perdana peringkat UiTM Cawangan Negeri Sembilan 2017 (1438H), 17. Sesi townhall pusat perancangan strategik (CSPI) bersama warga UiTM Cawangan Negeri Sembilan, 18. Taklimat Perpustakaan bagi sesi interim 2017 di Kampus Rembau, 19. Pameran social environment & brand architechture in advertising, 20. Majlis bacaan yasin dan kenduri kesyukuran, 21. Program library information (INTERIM), 22. Majlis kesyukuran sempena syawal 2017/1438H, 23. Lawatan mesra Prof. Madya Sabariah Hj Mahat, Rektor UiTM Cawangan Melaka ke Perpustakaan Kampus Jasin, 24. Lawatan dari Sekolah Menengah Kebangsaan Tun Teja, Melaka, 25. Majlis doa selamat dan kesyukuran, 26. Interim di Perpustakaan Al-Bukhari 2017, 27. Lawatan akademik dari UNITAR – KFORCE ke Perpustakaan Cendekiawan, UiTM Cawangan Terengganu, 28. Sambutan hari raya perdana UiTM Cawangan Terengganu 2017, 30. Sambutan hari raya peringkat UiTM Cawangan Johor, 31. Program sambutan hari raya UiTM Cawangan Sabah, 32. Minggu Interim bagi pelajar diploma (second intake), 33. Majlis jamuan hari raya aidilfitri PTAR 2017, 34. Pengesahan ke dalam perkhidmatan, 35. Majlis ramah tamah aidilfitri & pengawa' gawai 2017 UiTM Cawangan Sarawak, 36. Lawatan majlis perwakilan pelajar UiTM Johor, 37. Bengkel pangkalan data atas talian (PDAT) emerald premium, 38. Taklimat lifesaver, 39. Pameran Sarawak ibu pertiwi, 40. Majlis sambutan hari raya aidilfitri 2017 Perpustakaan Sultan Badlishah, 41. Lawatan delegasi akademik ASEAN, 42. Lawatan maahad tahfiz profesional Sungai Petani, 43. Majlis sambutan hari raya 2017 UiTM Cawangan Kedah, 44. Taklimat pengurusan arkib dan rekod oleh Jabatan Arkib Universiti
A review of advances in magnetorheological dampers: their design optimization and applications
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Mechanical Properties Comparison of Isotropic vs. Anisotropic Hybrid Magnetorheological Elastomer-Fluid
No full textMagnetorheological (MR) materials are smart materials that can change their rheological characteristics when exposed to a magnetic field. Such rheological properties include viscosity and dynamic modulus. MR materials have emerged as one of the most efficient smart materials that can modify mechanical and viscoelastic characteristics. Depending on the medium used, MR materials can be classified into two types: magnetorheological fluids (MRFs) and magnetorheological elastomers (MREs). MREs are classified as isotropic or anisotropic based on CIP distribution inside the elastomer matrix. A unique hybrid material incorporating MRE and MRF is constructed in this work to investigate, compare, and the dynamic properties of isotropic, anisotropic, hybrid isotropic, and hybrid anisotropic MREs under various magnetic fields (0, 104, and 160.2 mT). The created samples are subjected to extensive testing, including static and dynamic evaluations. In the static tests, experiments use a compression linear displacement mode with a fixed maximum gap change of 3 mm. The temperature is maintained at a constant level of 24 °C throughout the 40 s test duration for each test, and the magnetic field is incrementally increased by varying the number of magnets, ranging from 0 to 160.2 mT for dynamic qualities using compression oscillations on a dynamic mechanical analyzer (DMA), including frequency and strain-dependent data. These experiments, carried out using sinusoidal shear movements, include an excitation frequency range of 0.1 Hz to 15 Hz while preserving, with a fixed shear strain of 2%
A Comparative Study of Activation Functions of NAR and NARX Neural Network for Long-Term Wind Speed Forecasting in Malaysia
No full textSince wind power is directly influenced by wind speed, long-term wind speed forecasting (WSF) plays an important role for wind farm installation. WSF is essential for controlling, energy management and scheduled wind power generation in wind farm. The proposed investigation in this paper provides 30-days-ahead WSF. Nonlinear Autoregressive (NAR) and Nonlinear Autoregressive Exogenous (NARX) Neural Network (NN) with different network settings have been used to facilitate the wind power generation. The essence of this study is that it compares the effect of activation functions (namely, tansig and logsig) in the performance of time series forecasting since activation function is the core element of any artificial neural network model. A set of wind speed data was collected from different meteorological stations in Malaysia, situated in Kuala Lumpur, Kuantan, and Melaka. The proposed activation functions tansig of NARNN and NARXNN resulted in promising outcomes in terms of very small error between actual and predicted wind speed as well as the comparison for the logsig transfer function results. © 2019 Rasel Sarkar et al
