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Research On Flight Dynamics,Controller And Experiment Of A Small-Scale Unmanned Helicopter

Posted on:2017-11-18Degree:DoctorType:Dissertation
Country:ChinaCandidate:L DingFull Text:PDF
GTID:1312330536468288Subject:Mechanical and electrical engineering
Abstract/Summary:PDF Full Text Request
Small-scale unmanned helicopter has a peculiar flight feature of vertically take-off and landing,fixed position hovering,flying in low velocity,forward flight,rearward flight and so on.It has been mainly used for civilian and military field with the advantage of light weight,low price and small scale.However,the small-scale unmanned helicopter is a strong coupled,under actuated,multivariable,time varying,open-loop unstable,high order nonlinear system.It is a great challenge to realize the research of its autonomous flight.Therefore,this dissertation focuses on the research of the small-scale unmanned helicopter and aims at the research of dynamical modeling,flight control technology and path planning.The ultimate goal is to develop a fight control system which can guarantee the flight safety as well as maximizes the performance of the helicopter,and to prepare for design of intelligent aerial robotics in the future.The nonlinear flight dynamical model of the small-scale unmanned helicopter has been deduced at the inception of the dissertation.Meanwhile,the linearization method of the model also has been given.During the modeling,the kinematics and dynamics of rigid body are developed on the basis of the Newton-Euler equation.According to the classical momentum theory,the dynamical model and flapping motion of the simplified main rotor.Considering the yaw angular velocity feedback control system,the simplified yaw dynamics is derived.In addition,the whole dynamical model also contains fuselage drag force,force and torques of the vertical tail or horizontal tail.Aiming at the system identification for the linear model of small-scale unmanned helicopter in hover condition,a hybrid algorithm combined prediction error method with improved artificial bee colony algorithm(PEM-IABC)has been proposed.Firstly,the problem of system identification is turned into a multi-dimensional function optimization problem.And the search scope of the unknown parameters is arranged by PEM algorithm.Then,an adaptive search strategy is adopted to increase the speed of convergence in the stage of employed bee search.And in the stage of following bee search,the diversity of the population can be kept with a new probability of selection strategy.What's more,the Logistic chaotic search operator is applied to improve the ability of global search in the stage of scout bee search.Based on the PEM-IABC algorithm,the unknown parameters in the model are estimated through the flight data collected by airborne electronic equipment.Lastly,the effectiveness of the identified model has been validated and analyzed.The result shows that all the unknown parameters of the helicopter model can be estimated effectively.Furthermore,the main rotor time constant has been amended through the wind tunnel experiment.Based on the linear model of the unmanned helicopter,a static output-feedback control based on H-Infinity approach is used to realize the design of the wind resistance controller in hover condition.Firstly,the control method of linear time invariant systems using the H-Infinity approach is given.Then,this paper also proposes a numerically efficient solution algorithm to calculate the gain of the H-Infinity static output-feedback control.Lastly,we design the inner-loop and outer-loop controllers with the proposed control algorithm.And a series of simulations are presented to investigate the effectiveness of the controller.With the dynamic uncertainty of the nonlinear dynamical model of the unmanned helicopter and uncertainty of external disturbance,a multi-loop trajectory tracking controller based on linear active disturbance rejection control(LADRC)has been proposed.Firstly,the first-order,second-order and third-order LADRC controllers which are selected according to system order have been designed.And the trajectory tracking system is developed which has three control loops,i.e.,attitude loop,speed loop and position loop.Then,the unknown control parameters have been tuned based on glowworm swarm optimization.Lastly,with the perturbation of measurement noise and gust disturbance,the performance of the proposed trajectory tracking controller has been verified through a good climbing figure-eight trajectory tracking.The result shows that LADRC controller has higher control accuracy and stronger robustness than ADRC controller,and it can resist the disturbance effectively.In order to solve the problem of the unmanned air vehicle(UAV)flying in uncertain environment,an artificial bee colony algorithm based on cloud model has been proposed.Under the premise of detected flight area,we establish the planar model or three-dimensional models of planning space and develop the corresponding path cost model.Then,the problem of path planning had converted into the multi-dimensional functions optimization,and ABC algorithm has been used to search the optimal path with the strong search performance.Besides,a one-dimension normal cloud model is introduced to increase the speed of convergence and enhance the computational precision.Lastly,a series of simulations have been used to test the effectiveness and feasibility of our proposed algorithm.
Keywords/Search Tags:small scale unmanned helicopter, flight dynamical modeling, system Identification, wind tunnel experiment, H-Infinity static output feedback control, linear active disturbance rejection control, glowworm swarm optimization, path planning
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