How Much Energy Do We Need to Fly with Greater Agility? Energy Consumption and Performance of an Attitude Stabilization Controller in a Quadcopter Drone: A Modified MPC vs. PID

Okulski, Michał; Ławryńczuk, Maciej

doi:10.3390/en15041380

Cited by 9 publications

(8 citation statements)

References 25 publications

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“…The acceptable THD value for generators is below 25%, while the best THD value for generators is below 10%. Based on Table 5 and according to [24], the THD value for both states are considered acceptable which is below 25% for the MPC. This proves that the generators are working efficiently when in a 20 kHz sampling rate.…”

Section: Resultsmentioning

confidence: 99%

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Battery Energy Storage System (BESS) Modeling for Microgrid

Zulkifly

Yusoff

Tumeran

et al. 2023

IIUMEJ

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In the age of technology, microgrids have become well known because of their capability to back up the grid when an unpleasant event is about to occur or during power disruptions, at any time. However, the microgrid will not function well during power disruptions if the controller does not respond fast enough and the BESS will be affected. Many types of controllers can be used for microgrid systems. The controllers may take the form of Maximum Power Point Tracking (MPPT) Controller, Proportional Integral Derivative (PID) Controller, and Model Predictive Controller (MPC). Each of the controllers stated has its functions for the microgrid. However, two controllers that must be considered are PID and MPC. Both controllers will be compared based on their efficiency results which can be obtained through simulations by observing both graphs in charging and discharging states. Most researchers implied that MPC is better than PID because of several factors such as MPC is more robust and stable because of its complexity. Other than that, MPC can handle more inputs and outputs than PID which can cater to one input and output only. Although MPC has many benefits over the PID, still it is not ideal due to its complex algorithm. This work proposed an algorithm of simulations for the MPC to operate to get the best output for microgrid and BESS and compare the performance of MPC with PID. Using Simulink and MATLAB as the main simulation software is a very ideal way to simulate the dynamic performance of MPC. Furthermore, with Simulink, unpredictable variables such as Renewable Energy (RE) sources input and loads demands that are related to MPC can be measured easily. The algorithm of MPC is a cost function. Then the performance of the MPC is calculated using Fast-Fourier Transform (FFT) and Total Harmonic Distortion (THD). Lower THD means a higher power factor, this results in higher efficiency. This paper recorded THD of 9.57% and 12.77% in charging states and 16.51% and 18.15% in discharging states of MPC. Besides, PID recorded THD of 22.10% and 29.73% in charging states and 84.29% and 85.58% in discharging states. All of the recorded THD is below 25% in MPC and it shows a good efficiency while PID’s THD is above 25% shows its inefficiency. ABSTRAK: Pada zaman teknologi, mikrogrid menjadi terkenal kerana keupayaannya untuk menjana kuasa grid apabila kejadian yang tidak menyenangkan bakal berlaku atau ketika terjadinya gangguan kuasa, pada bila-bila masa. Walau bagaimanapun, mikrogrid tidak dapat berfungsi dengan baik semasa gangguan kuasa jika alat kawalan tidak bertindak balas dengan cukup pantas dan BESS akan terjejas. Banyak alat kawalan (pengawal) boleh digunakan bagi keseluruhan sistem mikrogrid. Setiap pengawal adalah berbeza seperti Pengawal Penjejakan Titik Kuasa Maksimum (MPPT), Pengawal Berkadar Terbitan Kamilan (PID) dan Pengawal Model Ramalan (MPC). Setiap pengawal yang dinyatakan mempunyai fungsinya yang tersendiri bagi mikrogrid. Walau bagaimanapun, dua pengawal yang perlu dipertimbangkan adalah PID dan MPC. Kedua-dua pengawal ini akan dibandingkan berdasarkan keputusan kecekapan yang boleh didapati melalui simulasi dengan memerhati kedua-dua graf pada keadaan pengecasan dan nyahcas. Ramai penyelidik menganggap bahawa MPC adalah lebih baik berbanding PID kerana beberapa faktor seperti MPC lebih teguh dan stabil kerana kerumitannya. Selain itu, MPC dapat mengendalikan lebih banyak input dan output berbanding PID yang hanya dapat menyediakan satu input dan output sahaja. Walaupun MPC mempunyai banyak faedah berbanding PID, ianya masih tidak sesuai kerana algoritma yang kompleks. Kajian ini mencadangkan algoritma simulasi bagi MPC beroperasi mendapatkan output terbaik untuk mikrogrid dan BESS dan membandingkan prestasi MPC dengan PID. Perisian simulasi utama yang sangat ideal bagi mensimulasi prestasi dinamik MPC adalah dengan menggunakan Simulink dan MATLAB. Tambahan, dengan Simulink, pembolehubah yang tidak terjangka seperti sumber Tenaga Boleh Diperbaharui (RE) dan permintaan beban yang berkaitan MPC boleh diukur dengan mudah. Algoritma MPC adalah satu fungsi kos. Kemudian prestasi MPC dikira menggunakan Penjelmaan Fourier Pantas (FFT) dan Total Pengherotan Harmonik (THD). THD yang lebih rendah bermakna faktor kuasa meningkat, ini menghasilkan kecekapan yang lebih tinggi. Kajian ini mencatatkan THD sebanyak 9.57% dan 12.77% dalam keadaan mengecas dan 16.51% dan 18.15% dalam keadaan nyahcas oleh MPC. Selain itu, PID mencatatkan THD sebanyak 22.10% dan 29.73% dalam keadaan mengecas dan 84.29% dan 85.58% dalam keadaan nyahcas. Semua THD yang direkodkan adalah di bawah 25% bagi MPC dan ia menunjukkan kecekapan yang baik manakala THD bagi PID adalah melebihi 25% menunjukkan ketidakcekapan.

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Section: Resultsmentioning

confidence: 99%

“…However, the most used controller is the MPC. [23] states that the MPC has a better performance than the PID in terms of vehicle control and the enhanced MPC has the fastest response in the drone's movement control [24]. Besides, [25] remarks that the MPC is more robust and stable because of its complexity.…”

Section: Introductionmentioning

confidence: 99%

Battery Energy Storage System (BESS) Modeling for Microgrid

Zulkifly

Yusoff

Tumeran

et al. 2023

IIUMEJ

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“…The energy efficiency of a drone was discussed e.g. in 16 , which presented a detailed study of the relationship between energy costs and the stabilisation of the altitude and the flight speed, which were characteristic of flight in formation, but again without considering the impact of collision avoidance.…”

Section: Literature Reviewmentioning

confidence: 99%

Multivariate linear regression model based on cross-entropy for estimating disorganisation in drone formations

Gackowska,

Cofta,

Śrutek

et al. 2023

Sci Rep

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Static formations of swarms of rotorcraft drones, used for example in disaster management, are subject to intrusions, and must bear the cost of holding the formation while avoiding collisions which leads to their increased energy consumption. While the behaviour of the intruder is unpredictable, the formation can have its parameters set to try to balance the cost of avoidance with its functionality. The novel model presented in this paper assists in the selection of parameter values. It is based on multivariate linear regression, and provides an estimate of the average disturbance caused by an intruder as a function of the values of the parameters of a formation. Cross-entropy is used as a metric for the disturbance, and the data based are generated through simulations. The model explains up to 54.4% of the variability in the value of the cross-entropy, providing results that are twice as good as the baseline estimator of the mean cross-entropy.

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“…Although the original diagram mentions a Feed-Forward (FF) component, it was eventually disabled in our build of the ArduCopter software. We investigated the overall agility of the attitude controller and eventually implemented a novel variant of the Model Predictive Controller (MPC) [44,45] as described in [46]. The control law of the attitude PID controller (see Figure 23) is simple enough that the embedded microcontroller can compute it efficiently in the main control loop at 400 Hz.…”

Section: Flight Controller Softwarementioning

confidence: 99%

“…A series of initial tests was performed in a custom-made limited-freedom test harness, which allows tilting the drone in a single axis only while holding it firmly and locking the remaining axes of rotation (Figure 24). Such a safe test environment was facilitative when we worked on the model identification and implementation of the attitude controllers [42,46]. The final Elka1Q mode was tested in this environment as well.…”

Section: Experiments With Limited Flight Freedommentioning

confidence: 99%

A Small UAV Optimized for Efficient Long-Range and VTOL Missions: An Experimental Tandem-Wing Quadplane Drone

Okulski

Ławryńczuk

2022

Applied Sciences

Self Cite

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Most types of Unmanned Aerial Vehicle (UAV, drone) missions requiring Vertical-Take-Off-and-Landing (VTOL) capability could benefit if a drone’s effective range could be extended. Example missions include Search-And-Rescue (SAR) operations, a remote inspection of distant objects, or parcel delivery. There are numerous research works on multi-rotor drones (e.g., quadcopters), fixed-wing drones, VTOL quadplanes, or tilt-motor/tilt-wing VTOLs. We propose a unique compact VTOL UAV optimized for long hover and long-range missions with great lifting capacity and manoeuvrability: a tandem-wing quadplane with fixed motors only. To the best of our knowledge, such a drone has not yet been researched. The drone was designed, built, and tested in flight. Construction details, its advantages, and issues are discussed in this research.

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How Much Energy Do We Need to Fly with Greater Agility? Energy Consumption and Performance of an Attitude Stabilization Controller in a Quadcopter Drone: A Modified MPC vs. PID

Cited by 9 publications

References 25 publications

Battery Energy Storage System (BESS) Modeling for Microgrid

Battery Energy Storage System (BESS) Modeling for Microgrid

Multivariate linear regression model based on cross-entropy for estimating disorganisation in drone formations

A Small UAV Optimized for Efficient Long-Range and VTOL Missions: An Experimental Tandem-Wing Quadplane Drone

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