Optimized PID Control of Quadrotor System Using Extremum Seeking Algorithm

Muhsen, Abdullah N.; Raafat, Safanah M.

doi:10.30684/etj.v39i6.1850

Cited by 7 publications

(6 citation statements)

References 17 publications

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“…Additionally, the incorporation of derivative action serves to reduce overshoot and increase the stability margin. Equation 14 [9], [10], [11], [31]denotes the standard PID controller. 𝑈(𝑡) 𝑃𝐼𝐷 = 𝐾 𝑃 𝑒(𝑡) + 𝐾 𝐼 ∫ 𝑒(𝑡) + 𝐾 𝐷 𝑑𝑒(𝑡) 𝑑𝑡 (14) Where the three gains determine the effects of proportional, integral, and derivative actions 𝐾 𝑃 , 𝐾 𝐼 , and 𝐾 𝐷 , respectively.…”

Section: Classical Pid Controllermentioning

confidence: 99%

“…Both linear and nonlinear control techniques are utilized. The authors in [7], [9], [10], [11] derived the quadcopter mathematical model and employed a linearized optimal Proportional-Integral-Derivative (PID) controller to track the desired trajectory, while both of the authors in [12], [13] used a Linear Quadratic Regulator (LQR) controller. The authors in [14], [15], [16], [17] utilized the optimal nonlinear Backstepping Controller (BSC), and the authors in [18], [19], [20]proposed an optimal Integral Backstepping Controller (IBSC) to control the attitude and altitude of the quadcopter.…”

Section: Introductionmentioning

confidence: 99%

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Optimal Trajectory Tracking: A Comparative Study of Autonomous Quadcopter Controllers

2024

jjmie

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The quadcopter controller plays a significant role in autonomous vehicle trajectory tracking and has been extensively examined in the literature because it is a highly nonlinear and under-actuated system. This article contributes by methodically comparing PID, BSC, IBSC, SMC, and ISMC control algorithms under standardized conditions. The study involves implementing these algorithms and optimizing their parameters using a hybrid Flower Pollination Algorithm -Genetic Algorithm (FPA-GA). Robust testing scenarios, including mass uncertainty and time-varying disturbances, are employed to assess algorithmic performance. The research centers on trajectory tracking-control approaches for highly maneuverable Unmanned Aerial Vehicles (UAVs) equipped with four heave thrusters, emphasizing controller stability through Lyapunov functions. Theoretical exploration precedes comprehensive numerical simulations, enabling a detailed comparison of the efficacy and resilience of the proposed approaches. Results from exhaustive testing reveal the consistent superiority of the BSC controller, demonstrating notably low Integral of Time-weighted Squared Error (ITSE) values of 0.1253 and 0.5262 from two simulation tests. These findings underscore the practical advantages of the BSC controller in highly dynamic UAV trajectory tracking scenarios.

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Section: Classical Pid Controllermentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Optimal Trajectory Tracking: A Comparative Study of Autonomous Quadcopter Controllers

2024

jjmie

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“…), respectively. The linear velocity of the system is represented by Α = [𝑢 𝑣 𝑤] 𝑇 ∈ 𝑅 3 and angular velocity is represented by 𝜍 = [𝑝 𝑞 𝑟] 𝑇 ∈ 𝑅 3 . Both of the velocities are derived in the mobile frame Rm.…”

Section: Kinematic Model Of a Foldable Quadrotormentioning

confidence: 99%

“…These applications include search and rescue, surveillance, photography, and delivery [1]. Consequently, numerous studies have been conducted to enhance the stability of quadrotors during flight [2,3] and to improve their utility in delivery applications [4,5]. However, conventional quadrotor designs are not well-suited for navigating small spaces and irregular surfaces, owing to their inherent stability.…”

Section: Introductionmentioning

confidence: 99%

Advanced Hybrid Nonlinear Control for Morphing Quadrotors

Ghane,

Hassan

2023

MMEP

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This paper presents a novel nonlinear control strategy tailored for foldable quadrotors capable of altering their morphology in-flight. By changing the quadrotor's shape through servo motors, these adaptive systems can effectively overcome various challenges, including diverse environmental conditions, such as obstacles and climate variations. The proposed control approach utilizes a double-loop control method to enhance the robustness and performance of the folding quadrotor during flight. The outer loop consists of a nonlinear PID controller responsible for regulating motion in the X and Y directions, while the inner loop features a sliding mode controller for altitude control in the Z direction and attitude stabilization. This dual-loop structure ensures the quadrotor's stability even during arm folding. The firefly algorithm is employed to optimize the parameters of both controllers, minimizing position errors using the Root Mean Square Error (RMSE) as a performance metric. Our results demonstrate a significant improvement in the quadrotor's performance and adaptability to various proposed morphologies, with error rates reduced to near-negligible levels for all shapes. Specifically, the X position error was reduced by 100% for all morphologies, the Y position error by 95% for the X shape, 97% for the T shape, 98% for the H shape, and 99% for the O shape, and the Z position error by 99% for all morphologies.

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“…Given that dynamic systems contain many variables, notably many mathematical models, it is hard to adopt a complex mathematical form, since the system works in real time. Additionally, memory capacity requirements must be fulfilled, and quick and reliable results must be obtained based on system design Juneja and Nagar (2015); Al-doraiee and Al-Qaraawi (2013); Muhsen and Raafat (2021). Therefore, over the past few years, heuristic techniques have been widely employed in the literature to achieve optimal performance regarding the obstacles posed by MIMO controller configurations Hassanzadeh and Mobayen (2011); Lones (2014).…”

Section: Introductionmentioning

confidence: 99%

Reduction of Large Scale Linear Dynamic MIMO Systems Using ACO-PID Controller

Alkhasraji,

Shneen,

Sulttan

2024

Ing. Inv.

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The MIMO technique is an essential element in the standards of communication systems (IEEE 802.11n, IEEE 802.11ac, WiMAX, and LTE) because it helps to increase their capacity. This paper employs a model order reduction (MOR) technique with a PID controller, an ACO algorithm, and the ITAE fitness function to reduce the large-scale linearity of the MIMO technique. The numerator and denominator parameters are set by minimizing the ITAE fitness function between the transient responses of the original and the reduced model. The objectives are achieved with the PID controller and the ACO algorithm for the unit step input. The simulation results show a good system performance. The controller performance is presented with regard to the dynamic response in terms of rising time, settling time, and overshoot/undershoot. Moreover, the results of the proposed method are compared with four literature reports for validation purposes. Evaluating the parameters within the time frame and the error values with and without the PID controller and ACO algorithm allowed validating the functioning of the proposed method. Furthermore, the simulation results revealed that the proposed scheme exhibited sufficient robustness and demonstrated a reduction in the time-domain response and error values.

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Optimized PID Control of Quadrotor System Using Extremum Seeking Algorithm

Cited by 7 publications

References 17 publications

Optimal Trajectory Tracking: A Comparative Study of Autonomous Quadcopter Controllers

Optimal Trajectory Tracking: A Comparative Study of Autonomous Quadcopter Controllers

Advanced Hybrid Nonlinear Control for Morphing Quadrotors

Reduction of Large Scale Linear Dynamic MIMO Systems Using ACO-PID Controller

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