Neurocontrol design for an aerodynamics system: simple backpropagation approach
This paper proposes a Neurocontrol (NNC) for a Twin Rotor Aerodynamics System (TRAS) by a simple backpropagation approach to improve the pitch position accuracy. A concept known as gradient descent method is applied to adjust the weights adaptively. The approach has several notable merits namely low...
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2019
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| Online Access: | http://eprints.utm.my/id/eprint/92789/1/NorMohdHaziqNorsahperi2019_NeurocontrolDesignforanAerodynamicsSystem.pdf http://eprints.utm.my/id/eprint/92789/ http://dx.doi.org/10.1007/978-981-13-6447-1_1 |
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my.utm.927892021-10-28T10:17:37Z http://eprints.utm.my/id/eprint/92789/ Neurocontrol design for an aerodynamics system: simple backpropagation approach Norsahperi, N. H. H. Danapalasingam, K. A. TK Electrical engineering. Electronics Nuclear engineering This paper proposes a Neurocontrol (NNC) for a Twin Rotor Aerodynamics System (TRAS) by a simple backpropagation approach to improve the pitch position accuracy. A concept known as gradient descent method is applied to adjust the weights adaptively. The approach has several notable merits namely low computational cost, simple and promising controller. The viability of NNC is verified by using MATLAB to analyze the tracking performance and control effort. PID control is benchmarked against the proposed NNC to determine the effectiveness of the controller. From the simulation work, it was discovered that NNC was superior then PID controller by reducing about 14%, 23% and 97% in the value of the overshoot, settling time and steady-state error respectively. The promising part of NNC was the improvement shown in the controller effort by significantly eliminating the fluctuation and chattering in the control signal. By looking into the future, this work will be a foundation for future improvement due to the fact that there are numerous types of approaches could be embedded in the Neural Network algorithm. 2019 Conference or Workshop Item PeerReviewed application/pdf en http://eprints.utm.my/id/eprint/92789/1/NorMohdHaziqNorsahperi2019_NeurocontrolDesignforanAerodynamicsSystem.pdf Norsahperi, N. H. H. and Danapalasingam, K. A. (2019) Neurocontrol design for an aerodynamics system: simple backpropagation approach. In: 0th International Conference on Robotic, Vision, Signal Processing and Power Applications, ROVISP 2018, 14-15 Aug 2018, Pulau Pinang, Malaysia. http://dx.doi.org/10.1007/978-981-13-6447-1_1 |
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TK Electrical engineering. Electronics Nuclear engineering Norsahperi, N. H. H. Danapalasingam, K. A. Neurocontrol design for an aerodynamics system: simple backpropagation approach |
| description |
This paper proposes a Neurocontrol (NNC) for a Twin Rotor Aerodynamics System (TRAS) by a simple backpropagation approach to improve the pitch position accuracy. A concept known as gradient descent method is applied to adjust the weights adaptively. The approach has several notable merits namely low computational cost, simple and promising controller. The viability of NNC is verified by using MATLAB to analyze the tracking performance and control effort. PID control is benchmarked against the proposed NNC to determine the effectiveness of the controller. From the simulation work, it was discovered that NNC was superior then PID controller by reducing about 14%, 23% and 97% in the value of the overshoot, settling time and steady-state error respectively. The promising part of NNC was the improvement shown in the controller effort by significantly eliminating the fluctuation and chattering in the control signal. By looking into the future, this work will be a foundation for future improvement due to the fact that there are numerous types of approaches could be embedded in the Neural Network algorithm. |
| format |
Conference or Workshop Item |
| author |
Norsahperi, N. H. H. Danapalasingam, K. A. |
| author_facet |
Norsahperi, N. H. H. Danapalasingam, K. A. |
| author_sort |
Norsahperi, N. H. H. |
| title |
Neurocontrol design for an aerodynamics system: simple backpropagation approach |
| title_short |
Neurocontrol design for an aerodynamics system: simple backpropagation approach |
| title_full |
Neurocontrol design for an aerodynamics system: simple backpropagation approach |
| title_fullStr |
Neurocontrol design for an aerodynamics system: simple backpropagation approach |
| title_full_unstemmed |
Neurocontrol design for an aerodynamics system: simple backpropagation approach |
| title_sort |
neurocontrol design for an aerodynamics system: simple backpropagation approach |
| publishDate |
2019 |
| url |
http://eprints.utm.my/id/eprint/92789/1/NorMohdHaziqNorsahperi2019_NeurocontrolDesignforanAerodynamicsSystem.pdf http://eprints.utm.my/id/eprint/92789/ http://dx.doi.org/10.1007/978-981-13-6447-1_1 |
| _version_ |
1715189690263404544 |
| score |
13.244369 |