A Linear Domain System Identification for Small Unmanned Aerial Rotorcraft Based on Adaptive Genetic Algorithm

This paper proposes a new adaptive linear domain system identification method for small unmanned aerial rotorcraft.Byusing the flash memory integrated into the micro guide navigation control module, system records the data sequences of flighttests as inputs (control signals for servos) and outputs (aircraft’s attitude and velocity information).After data preprocessing, thesystem constructs the horizontal and vertical dynamic model for the small unmanned aerial rotorcraft using adaptive geneticalgorithm.The identified model is verified by a series of simulations and tests.Comparison between flight data and the one-stepprediction data obtained from the identification model shows that the dynamic model has a good estimation for real unmannedaerial rotorcraft system.Based on the proposed dynamic model, the small unmanned aerial rotorcraft can perform hovering,turning, and straight flight tasks in real flight tests.

The Model Identification for Small Unmanned Aerial Rotorcraft Based on Adaptive Ant Colony Algorithm

This paper proposes a model identification method to get high performance dynamic model of a small unmanned aerial rotorcraft. With the analysis of flight characteristics, a linear dynamic model is constructed by the small perturbation theory. Using the micro guidance navigation and control module, the system can record the control signals of servos, the state infor- mation of attitude and velocity information in sequence. After the data preprocessing, an adaptive ant colony algorithm is proposed to get optimal parameters of the dynamic model. With the adaptive adjustment of the pheromone in the selection process, the proposed model identification method can escape from local minima traps and get the optimal solution quickly. Performance analysis and experiments are conducted to validate the effectiveness of the identified dynamic model. Compared with real flight data, the identified model generated by the proposed method has a better performance than the model generated by the adaptive genetic algorithm. Based on the identified dynamic model, the small unmanned aerial rotorcraft can generate suitable control parameters to realize stable hovering, turning, and straight flight.

Distributed velocity-free formation tracking control for clustered UAVs under virtual leader-follower framework

The collective formation control problem of a cluster of rotorcraft unmanned aerial vehicles(UAVs)is investigated in this article.The consensus tracking towards formation centroid with following UAVs forming a predefined configuration around the leader is considered as the objective.Unlike prior studies,the information of the central reference trajectory,which is deemed as a virtual leader in the leader-follower topology,is not directly accessible for partial nodes through the communication network.Therefore,a novel distributed formation tracking control scheme is promoted.Besides,a decentralized saturation observer is employed to estimate the reference acceleration signal of the virtual leader.In the absence of linear velocity measurement,two sliding manifolds are proposed by introducing the relative discrepancy terms of position and velocity.Then a smooth saturation operator in the form of a sigmoid function is applied to generate the command force input.Moreover,under the dilemma of constrained capabilities of the airborne sensors equipped on the rotorcrafts,the angular velocity is difficult to acquire.Two cascaded auxiliary attitude error systems are established on each rotorcraft system to synthesize the rotating torque with no need to require the angular velocity measurement.Due to the strong coupling and nonlinearity of the rotorcraft UAV system,the command angular velocity and the derivatives of command input are hard to obtain.Then a continuous nonlinear differentiator is proposed to work with the difficulties in deriving the explicit expression of system derivatives.Thereafter,a detailed stability analysis is conducted progressively on the angular control loop,reference trajectory observer loop,and the position control loop.A simulation scheme for a cluster of four rotorcraft UAVs tracking sinusoidal trajectory are presented and the formation control results are proven advantageous in comparison with the control protocol in previous literature.