scholarly journals Robust linearization scheme by structural state feedback for a quadrotor

2021 ◽  
pp. 13-21
Author(s):  
Luis Ángel Blas-Sánchez ◽  
Margarita Galindo-Mentle ◽  
Adolfo Quiroz-Rodríguez ◽  
Marlon Licona-González
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Dynamic Model ◽  
Feedback Linearization ◽  
State Feedback ◽  
Circular Trajectory ◽  
Linearization Technique ◽  
Aerial Vehicles ◽  
State Observers ◽  
Control Scheme ◽  
Change Of Variable

In this work a feedback linearization technique is proposed, to carry it out to linearize the dynamic model of the quadrotor, a change of variable is introduced that maps the nonlinearities of the system into a nonlinear uncertainty signal contained in the domain of the action of control and is applied to the dynamic model of the quadrotor. To estimate the nonlinear uncertainty signal, the Beard-Jones filter is used, which is based on standard state observers. To verify the effectiveness of the proposed control scheme, experiments are carried out outdoors to follow a circular trajectory in the (x,y) plane. This presented control scheme is suitable for unmanned aerial vehicles where it is important to reject not only non-linearities but also to seek the simplicity and effectiveness of the control scheme for its implementation.

scholarly journals Study on Composing Dense Formations in a Dynamic Environment of Multirotor UAVs by Distributed Control

2018 ◽  
Vol 2018 ◽  
pp. 1-8
Author(s):  
Shudao Zhou ◽  
Ao Shen ◽  
Min Wang ◽  
Shuling Peng ◽  
Zhanhua Liu
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Dynamic Model ◽  
Distributed Control ◽  
Distributed Algorithm ◽  
Search Algorithm ◽  
Dynamic Environment ◽  
Step Motion ◽  
Aerial Vehicles ◽  
Path Search ◽  
The Membership Function

In order to make multirotor unmanned aerial vehicles (UAV) compose a desired dense formation and improve the practicality of UAV formation, a distributed algorithm based on fuzzy logic was proposed. The airflow created by multirotor UAVs was analyzed according to the structure of the multirotor UAV and the characteristic equation of the fluid. This paper presented a dynamic model for the process of formation of and path search algorithm based on this model. The membership function in this model combines the factors of position, flow field, and movement. Integrating the dynamic model and its desired position in formations, each UAV evaluates the surrounding points and then selects the direction for step motion. Through simulation, this algorithm was improved by a by-step formation approach, and the effectiveness of this method in dense formation of multirotor UAVs was proved.

Fault-Tolerant Formation Control of Unmanned Aerial Vehicles in the Presence of Actuator Faults and Obstacles

2016 ◽  
Vol 04 (03) ◽  
pp. 197-211 ◽  
Author(s):  
Zhixiang Liu ◽  
Chi Yuan ◽  
Xiang Yu ◽  
Youmin Zhang
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Formation Control ◽  
Active Fault ◽  
Fault Tolerant ◽  
Actuator Faults ◽  
Outer Loop ◽  
Actuator Failures ◽  
Aerial Vehicles ◽  
Control Scheme ◽  
Multiple Unmanned Aerial Vehicles

This paper presents a leader-follower type of fault-tolerant formation control (FTFC) methodology with application to multiple unmanned aerial vehicles (UAVs) in the presence of actuator failures and potential collisions. The proposed FTFC scheme consists of both outer-loop and inner-loop controllers. First, a leader-follower control scheme with integration of a collision avoidance mechanism is designed as the outer-loop controller for guaranteeing UAVs to keep the desired formation while avoiding the approaching obstacles. Then, an active fault-tolerant control (FTC) strategy for counteracting the actuator failures and also for preventing the healthy actuators from saturation is synthesized as the inner-loop controller. Finally, a group of numerical simulations are carried out to verify the effectiveness of the proposed approach.

scholarly journals Application of Quadratic Linearization for the Control of Permanent Magnet Synchronous Motor

2011 ◽  
Vol 2011 ◽  
pp. 1-11
Author(s):  
Parvathy Ayalur Krishnamoorthy ◽  
Kamaraj Vijayarajan ◽  
Devanathan Rajagopalan
Keyword(s):  
Permanent Magnet ◽  
Dynamic Model ◽  
Feedback Linearization ◽  
Dynamic Models ◽  
Permanent Magnet Synchronous Motor ◽  
Synchronous Motor ◽  
Matlab Simulation ◽  
Linearization Technique ◽  
Approximate Linearization ◽  
State Models

Many of the existing control methods for the permanent magnet synchronous motor (PMSM) either deal with steady state models or consider dynamic models under particular cases. A dynamic model of the PM machine allows powerful control-theoretic techniques such as linearization to be applied to the system. Existing exact feedback linearization of dynamic model of PMSM suffers from singularity issues. In this paper, we propose a quadratic linearization approach for PMSM based on the approximate linearization technique which does not introduce singularities. A MATLAB simulation is used to verify the effectiveness of the linearization technique proposed. Also, to account for higher-order and unmodelled dynamics of PMSM, tuning of the linearizing transformation is proposed and verified using simulation.

scholarly journals Decentralized Mesh-Based Model Predictive Control for Swarms of UAVs

Sensors ◽  
2020 ◽  
Vol 20 (15) ◽  
pp. 4324
Author(s):  
Salvatore Rosario Bassolillo ◽  
Egidio D’Amato ◽  
Immacolata Notaro ◽  
Luciano Blasi ◽  
Massimiliano Mattei
Keyword(s):  
Model Predictive Control ◽  
Unmanned Aerial Vehicles ◽  
Predictive Control ◽  
Control Strategy ◽  
Target Area ◽  
Guidance And Control ◽  
Aerial Vehicles ◽  
Control Scheme ◽  
And Control ◽  
Numerical Simulator

This paper deals with the design of a decentralized guidance and control strategy for a swarm of unmanned aerial vehicles (UAVs), with the objective of maintaining a given connection topology with assigned mutual distances while flying to a target area. In the absence of obstacles, the assigned topology, based on an extended Delaunay triangulation concept, implements regular and connected formation shapes. In the presence of obstacles, this technique is combined with a model predictive control (MPC) that allows forming independent sub-swarms optimizing the formation spreading to avoid obstacles and collisions between neighboring vehicles. A custom numerical simulator was developed in a Matlab/Simulink environment to prove the effectiveness of the proposed guidance and control scheme in several 2D operational scenarios with obstacles of different sizes and increasing number of aircraft.

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