Adaptive Trajectory Tracking for Quadrotor Systems in Unknown Wind Environments Using Particle Swarm Optimization-Based Strictly Negative Imaginary Controllers

Tran, Vu Phi; Santoso, Fendy; Garratt, Matthew A.

doi:10.1109/taes.2020.3048778

Cited by 23 publications

(10 citation statements)

References 31 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In terms of channel model innovation, it puts forward two directions: (1) Pay attention to customer experience and customer value; promote the transformation from "competition orientation" to "customer orientation" and from "transaction orientation" to "relationship orientation". (2) Pay attention to strategic channel partnership, focus on cultivating customer loyalty, and promote long-term cooperation and multiple transactions [2].…”

Section: Literature Reviewmentioning

confidence: 99%

Precision Marketing and Brand Communication Model Using Particle Swarm Optimization Algorithm

Xue

2022

Mobile Information Systems

View full text Add to dashboard Cite

In order to deeply study the macroenvironment, current situation, and the core elements affecting the operation of the product brand system, this paper further improves the product brand communication system from the perspective of precision marketing. Taking JR company’s big cake products as the research object, this study proposes an accurate positioning optimization algorithm based on particle swarm optimization algorithm. Through the experiment of increasing the number of nodes of different algorithms, it is found that the average positioning error will decrease with the increase of the number of nodes under different algorithms. Compared with WSSPCO positioning algorithm, the average error of PSO positioning algorithm is reduced by about 30% due to the number of nodes, and the impact of node density on positioning accuracy is also reduced by about 40%. This algorithm can better achieve accurate positioning. Therefore, it is concluded that product brand communication based on precision marketing should pay attention to accurate positioning, further integrate brand communication channels, and build personalized communication channels.

show abstract

Section: Literature Reviewmentioning

confidence: 99%

Precision Marketing and Brand Communication Model Using Particle Swarm Optimization Algorithm

Xue

2022

Mobile Information Systems

View full text Add to dashboard Cite

show abstract

“…This arises as a result of the plant's basic settings. The following WPs are accomplished by establishing the appropriate heading and yaw and then proceeding at a determined speed to a specified distance [1,2,[27][28][29][30].…”

Section: Simulation Resultsmentioning

confidence: 99%

“…It is an under-actuated, lively vehicle with four input militaries and six output organizes. Quadrotor, calm of four rotors with proportionally preparation where two slanting motors (1 and 2) are consecutively in the same way while the others (3 and 4) in the other way to remove the anti-torque [1][2][3][4][5].The technique used in the quadcopter system, controller design, implementation of PSO algorithm [5][6][7], and procedure for achieving the best tuning. Also, the mathematical model and analysis of PSO algorithms are explained.…”

Section: Introductionmentioning

confidence: 99%

Quadcopter Vehicle Proportional-Integral-Derivative Controller (PIDC) Tuning by Particle-Swarm Optimization (PSO)

Gizi

2022

EAI Endorsed Trans Creat Tech

View full text Add to dashboard Cite

Inspection of the faults and damages in high voltage transmission lines is not only unsafe and costly but also a very time-consuming process. In addition, it demands highly skilled manpower for the operation at tens of meters above the ground on cables carrying thousands of Volts. Meanwhile, the Quadcopter Aerial Vehicle (QAV) system became a popular alternative for aerial photography applications due to its low cost, ease of usage, and fast response wherein the proportional-integral-derivative controller (PIDC) is used. The PID controller compares the expected location of the drone with the actual measured position thereby can accurately detect the faults in the transmission lines. Based on these factors, in this study, the flight simulation is done according to the desired flight path, and drone imagery is used for (insulator, power line, and porcelain) flaw identification. Furthermore, three movements (roll, pitch, and yaw) of the quadcopter were controlled by different PIDC that were optimized using the particle swarm optimization (PSO). The MATLAB/Simulink application was used to develop the system and simulate the results (R2021b). This clearly suggested that the quadcopter continues to fly on a trajectory with minimum inaccuracy, wherein the PIDC operated as a closed-loop adaptive controller. Finally, the PSO-PIDC outperformed the PIDC due to the critical nature of manual gain modification for quadcopter flight stability.

show abstract

“…Using the Barbalat's lemma [37], the result in (25) implies that for bounded desired trajectories, and considering that the input for the quadrotors u is bounded,V is bounded, and, therefore,V is uniformly continuous, which implies in asymptotically stable velocity tracking. In other words, ν → 0, which also implies thatẋ,x → 0 asymptotically.…”

Section: B Stability Analysismentioning

confidence: 99%

Cooperative Load Transportation With Two Quadrotors Using Adaptive Control

et al. 2021

View full text Add to dashboard Cite

The problem of carrying a bar-shaped payload suspended by flexible cables attached to two quadrotors is analyzed in this work. The aerial vehicles and the load are dealt with as a single system, whose kinematics is described as a multi-robot formation using the virtual structure approach. The dynamic effects caused by the tethered load over the quadrotors, as well as those caused by each quadrotor over the other, are treated by an adaptive dynamic compensator. To validate the proposal, experiments were run testing the system in adverse conditions: transportation far from quasi-static motion, high payload-to-quadrotor weight ratio, 20% of error in the robot model parameters, transportation under wind disturbances, and payload weight changes during flight. The good performance of the proposed control system in all these tests allows concluding that the proposed system is able to accomplish payload positioning, orientation, and trajectory tracking under adverse conditions, with accelerations up to 1.6 m/s 2 .

show abstract

Adaptive Trajectory Tracking for Quadrotor Systems in Unknown Wind Environments Using Particle Swarm Optimization-Based Strictly Negative Imaginary Controllers

Cited by 23 publications

References 31 publications

Precision Marketing and Brand Communication Model Using Particle Swarm Optimization Algorithm

Precision Marketing and Brand Communication Model Using Particle Swarm Optimization Algorithm

Quadcopter Vehicle Proportional-Integral-Derivative Controller (PIDC) Tuning by Particle-Swarm Optimization (PSO)

Cooperative Load Transportation With Two Quadrotors Using Adaptive Control

Contact Info

Product

Resources

About