Investigation of Sliding Mode Controller Operation in Quadcopter Attitude Control; Journal of Robotics and Control (JRC); Vol. 6, iss. 5
| Parent link: | Journal of Robotics and Control (JRC).— .— Yogyakarta: UMY Electrical Engineering Vol. 6, iss. 5.— 2025.— P. 2581-2591 |
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| Other Authors: | , , , |
| Summary: | Title screen Smooth control of the tilt angles of the quadcopter is critically important for video surveillance tasks but is hindered by vibrations and noise. To ensure smooth trajectories under such conditions, a hybrid control scheme is proposed, combining a proportional-derivative (PD) controller and an angular velocity controller based on sliding mode control (SMC). The scientific contribution lies in the modification of the two-loop structure by adding a sequential integrating element with a rate limiter, which ensures the compatibility of the SMC output with the motor electronic speed controller (ESC). To suppress noise, a Kalman filter is implemented, taking into account the control signal at the equilibrium point. A comparative analysis of the performance of the PID-PID-I controller and results obtained in other authors' studies was conducted. It was found that the "chattering" effect does not affect the operation of the proposed PD-SMC-I scheme. The experimental results show a reduction in the mean squared error by a factor of 9.5, improvements in integral metrics: integral of absolute error (IAE) by a factor of 9.8, integral of squared error (ISE) by a factor of 1.43, and integral of time absolute error (ITAE) by a factor of 11.6, as well as a decrease in energy consumption according to the control signal energy (CSE) by a factor of 20, control signal amplitude (CSA) by a factor of 2.6, and an increase in energy efficiency (CE) by a factor of 5.3. In the experiment, an increase in settling time of 20% is acceptable for ensuring the stability and smoothness of the trajectory, rather than responsiveness. The optimal tuning of the covariance matrices of the Kalman filter requires a balance between the uncertainty of the dynamic model and the level of measurement noise, where a low ratio improves control smoothness but introduces bias in the estimation of angular velocity. The results of the simulations were confirmed by experimental data. The proposed approach makes the system particularly suitable for monitoring natural phenomena and video surveillance and can be applied in systems operating under conditions of parametric uncertainty and noise Текстовый файл |
| Language: | English |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://doi.org/10.18196/jrc.v6i5.27297 |
| Format: | Electronic Book Chapter |
| KOHA link: | https://koha.lib.tpu.ru/cgi-bin/koha/opac-detail.pl?biblionumber=685642 |
| Summary: | Title screen Smooth control of the tilt angles of the quadcopter is critically important for video surveillance tasks but is hindered by vibrations and noise. To ensure smooth trajectories under such conditions, a hybrid control scheme is proposed, combining a proportional-derivative (PD) controller and an angular velocity controller based on sliding mode control (SMC). The scientific contribution lies in the modification of the two-loop structure by adding a sequential integrating element with a rate limiter, which ensures the compatibility of the SMC output with the motor electronic speed controller (ESC). To suppress noise, a Kalman filter is implemented, taking into account the control signal at the equilibrium point. A comparative analysis of the performance of the PID-PID-I controller and results obtained in other authors' studies was conducted. It was found that the "chattering" effect does not affect the operation of the proposed PD-SMC-I scheme. The experimental results show a reduction in the mean squared error by a factor of 9.5, improvements in integral metrics: integral of absolute error (IAE) by a factor of 9.8, integral of squared error (ISE) by a factor of 1.43, and integral of time absolute error (ITAE) by a factor of 11.6, as well as a decrease in energy consumption according to the control signal energy (CSE) by a factor of 20, control signal amplitude (CSA) by a factor of 2.6, and an increase in energy efficiency (CE) by a factor of 5.3. In the experiment, an increase in settling time of 20% is acceptable for ensuring the stability and smoothness of the trajectory, rather than responsiveness. The optimal tuning of the covariance matrices of the Kalman filter requires a balance between the uncertainty of the dynamic model and the level of measurement noise, where a low ratio improves control smoothness but introduces bias in the estimation of angular velocity. The results of the simulations were confirmed by experimental data. The proposed approach makes the system particularly suitable for monitoring natural phenomena and video surveillance and can be applied in systems operating under conditions of parametric uncertainty and noise Текстовый файл |
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| DOI: | 10.18196/jrc.v6i5.27297 |