Quadrotor Navigation Using the PID and Neural Network Controller

Lower, Michał; Tarnawski, Wojciech

doi:10.1007/978-3-319-19216-1_25

Cited by 5 publications

(5 citation statements)

References 17 publications

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“…Using the Newton-Euler method [23,24] the rotational formulas of motion are generated in the body field shown in equation (1).…”

Section: Quadcopter Equationsmentioning

confidence: 99%

“…In recent years, quadrotors (UAV, quadcopter) emerged widely in commercial and army areas [1,2,3]. There are many applications of quadcopter UAVs, such as life-saving operations, surveillance, aerial photography for mapping, an inspection of power lines, traffic monitoring in city areas, crop monitoring and spraying, border patrol, search operations for missing persons and natural disasters [4,5,6,7].…”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

“…Most quadcopters apply the classical control method, so they are driven by proportional-integral-derivative-PID controllers [1][2][3][4][5][6][7][8][9][10]. PID controller method and its usability in different systems are well described in many research papers [1][2][3][4][5][6][7][8][9][10]. There are several other algorithms that control quadcopters, such as LQR, Backstepping, Sliding mode, Linearized Feedback, Fuzzy logic, Optimal, L1, H∞, and Adaptive control.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Quadcopter Stabilization using Neural Network Model from Collected Data of PID Controller

Gotov

Tengis

Choimaa

et al. 2022

The journal invites submissions from across the world.

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There are a lot of methods for the stabilization of quadcopters and the newest are based on AI. A neural network is a simplified model that imitates the human brain's processes. In the research paper, we present a neural network control model for quadcopter stabilization. A single hidden layer network model was estimated to investigate the dynamics of the UAV. A control system with a classical PID controller was used to train the neural network model. This method is used for examining how the neural network imitates the stabilization of the quadcopter in real flight mode. The novelty of the work was to design of small size 3 layers NN model that runs in real-time in a quadcopter. The PID and machine learning controllers' operation results were compared to each other andshown in the experiment.

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“…Using the Newton-Euler method [23,24] the rotational formulas of motion are generated in the body field shown in equation (1).…”

Section: Quadcopter Equationsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Quadcopter Stabilization using Neural Network Model from Collected Data of PID Controller

Gotov

Tengis

Choimaa

et al. 2022

The journal invites submissions from across the world.

View full text Add to dashboard Cite

show abstract

“…The dynamics of the quadcopter are nonlinear, each quadcopter having six degrees of freedom: three rotational and three translational. A conventional helicopter has two rotors, while a quadcopter has four rotors which enable the takeoff, hover and landing; in order to control all six degrees of freedom, four propeller are present [12]. Quadcopter can move both in prismatic as well as in revolute motion.…”

Section: Introductionmentioning

confidence: 99%

PID Controller Tuning Optimization with Genetic Algorithms for a Quadcopter

Khuwaja

Lighari

Ţarcă

et al. 2018

RIiM

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Abstract-This paper is focused on the dynamic of mathematical modeling, stability, nonlinear gain control by using Genetic algorithm, utilizing MATLAB tool of a quadcopter. Previously many researchers have been work on several linear controllers such as LQ method; sliding mode and classical PID are used to stabilize the Linear Model. Quadcopter has a nonlinear dynamics and unstable system. In order to maintain their stability, we use nonlinear gain controllers; classical PID controller provides linear gain controller rather than nonlinear gain controller; here we are using modified PID control to improve stability and accuracy. The stability is the state of being resistant to any change. The task is to maintain the quadcopter stability by improving the performance of a PID controller in term of time domain specification. The goal of PID controller design is to determine a set of gains: Kp, Ki, and Kd, so as to improve the transient response and steady state response of a system as: by reducing the overshoot; by shortening the settling time; by decrease the rise time of the system. Modified PID is the combination of classical PID in addition to Genetic Algorithm. Genetic algorithm consists of three steps: selection, crossover, and mutation. By using Genetic algorithm we correct the behavior of quadcopter.

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Design a Neural Controller to Control Rescue Quadcopter in Hang Status

Hoang

Huy

2020

Advances in Computational Collective Intelligence

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Quadrotor Navigation Using the PID and Neural Network Controller

Cited by 5 publications

References 17 publications

Quadcopter Stabilization using Neural Network Model from Collected Data of PID Controller

Quadcopter Stabilization using Neural Network Model from Collected Data of PID Controller

PID Controller Tuning Optimization with Genetic Algorithms for a Quadcopter

Design a Neural Controller to Control Rescue Quadcopter in Hang Status

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