Tracking Formation Control for Multiple Quadrotors Based on FuzzyLogic Controller and Least Square Oriented by Genetic Algorithm

This paper studies the leader-follower formation control for multiple quadrotors. Two controllers are used. The first one is a proportional derivative controller used to ensure the tracking of the leader to the desired trajectory, while the second is based on fuzzy logic in order to achieve the desired formation in ! − ! plane with equal height (!) for all follower quadrotors. In order to ensure the speed time convergence of the formation shape, Genetic Algorithm is used online to tune the fuzzy logic controller parameters. This genetic algorithm is also used to predict the trajectory of the quadrotor leader in the case of communication failure between leader and follower quadrotors by online estimation of the least square coefficients. Proportional derivative controller is used again to keep the desired formation shape of the follower quadrotors. Finally, simulation results demonstrate the effectiveness of the proposed algorithms.

[1]  E.M. Atkins,et al.  A survey of consensus problems in multi-agent coordination , 2005, Proceedings of the 2005, American Control Conference, 2005..

[2]  Kamel Kara,et al.  Fuzzy Sliding Mode Control with Chattering Elimination for a Quadrotor Helicopter in Vertical Flight , 2012, HAIS.

[3]  Seth Stovack Kessler.  Piezoelectric-based in-situ damage detection of composite materials for structural health monitoring systems , 2002 .

[4]  Charles L. Karr,et al.  Genetic algorithm applied to least squares curve fitting , 1991 .

[5]  Zhu Qidan,et al.  Genetic Fuzzy Logic Control Technique for a Mobile Robot Tracking a Moving Target , 2013 .

[6]  Danwei Wang,et al.  Cooperative Control of Multiple UAVs for Source Seeking , 2013, J. Intell. Robotic Syst..

[7]  Vijay Kumar,et al.  Geometric control of cooperating multiple quadrotor UAVs with a suspended payload , 2013, 52nd IEEE Conference on Decision and Control.

[8]  Rafael Castro,et al.  Quadrotors flight formation control using a leader-follower approach , 2013, 2013 European Control Conference (ECC).

[9]  Qinghe Wu,et al.  Improved Leader Follower Formation controller for multiple Quadrotors based AFSA , 2015 .

[10]  Richard M. Murray,et al.  INFORMATION FLOW AND COOPERATIVE CONTROL OF VEHICLE FORMATIONS , 2002 .

[11]  Youdan Kim,et al.  Formation Geometry Center based Formation Controller Design using Lyapunov Stability Theorem , 2008 .

[12]  Tong Heng Lee,et al.  Design and implementation of a leader-follower cooperative control system for unmanned helicopters , 2010 .

[13]  Angus R. Simpson,et al.  Genetic algorithms compared to other techniques for pipe optimization , 1994 .

[14]  Kenzo Nonami,et al.  Circular Leader-Follower Formation Control of Quad-Rotor Aerial Vehicles , 2013, J. Robotics Mechatronics.

[15]  Cheolkeun Ha,et al.  of Advanced Robotic Systems Control of a Quadrotor Using a Smart Self-Tuning Fuzzy PID Controller , 2013 .

[16]  Chuntian Cheng,et al.  Long-Term Prediction of Discharges in Manwan Reservoir Using Artificial Neural Network Models , 2005, ISNN.

[17]  Fulvia Quagliotti,et al.  Linear Quadratic Control for Quadrotors UAVs Dynamics and Formation Flight , 2013, J. Intell. Robotic Syst..

[18]  Satoshi Tomioka,et al.  Nonlinear Least Square Regression by Adaptive Domain Method With Multiple Genetic Algorithms , 2007, IEEE Transactions on Evolutionary Computation.

[19]  H. Jin Kim,et al.  Feedback linearization vs. adaptive sliding mode control for a quadrotor helicopter , 2009 .

[20]  Rogelio Lozano,et al.  Mini Rotorcraft Flight Formation Control Using Bounded Inputs , 2012, J. Intell. Robotic Syst..

[21]  Rajandrea Sethi,et al.  Artificial neural network simulation of hourly groundwater levels in a coastal aquifer system of the Venice lagoon , 2012, Eng. Appl. Artif. Intell..