This paper proposed a modified artificial physics(AP)method to solve the autonomous navigation problem for mobile robots in complex environments.The basic AP method tends to cause oscillations in the presence of obstacles and in narrow passages,which can result in time consumption.To alleviate oscillation,we modified the AP method using the Levenbery-Marquardt(LM)algorithm.In the modified AP method,we altered the original directions of AP forces to the Newton direction,and adjust the parameter by the LM algorithm.A series of comparative experimental results show that the modified AP method can achieve smoother trajectories with less time consumption.This demonstrates the feasibility and effectiveness of our proposed approach.
A novel network control method based on trophallaxis mechanism is applied to the formation flight problem for multiple unmanned aerial vehicles(UAVs).Firstly,the multiple UAVs formation flight system based on trophallaxis network control is given.Then,the model of leader-follower formation flight with a virtual leader based on trophallaxis network control is presented,and the influence of time delays on the network performance is analyzed.A particle swarm optimization(PSO)-based formation controller is proposed for solving the leader-follower formation flight system.The proposed method is applied to five UAVs for achieving a 'V' formation,and a series of experimental results show its feasibility and validity.The proposed control algorithm is also a promising control strategy for formation flight of multiple unmanned underwater vehicles(UUVs),unmanned ground vehicles(UGVs),missiles and satellites.
This paper describes a novel type of pendulum-like oscillation controller for micro air vehicle(MAV) hover and stare state in the presence of external disturbances,which is based on linear-quadratic regulator(LQR) and particle swarm optimization(PSO).A linear mathematical model of pendulum phenomenon based upon actual wind tunnel test data representing the hover mode is established,and a hybrid LQR and PSO approach is proposed to stabilize oscillation.PSO is applied to parameter optimization of the designed LQR controller.A series of comparative experiments are conducted,and the results have verified the feasibility,effectiveness and robustness of our proposed approach.
The controller design for hypersonic vehicle is critical and challenging because of the inherent couplings between the propulsion system and the airframe dynamics,as well as the presence of strong flexibility effects.Many researchers have investigated various strategies to mitigate the coupling by means of robust design methods.This paper reviews the recent research efforts to promote the capability of control design for hypersonic vehicle.Methodologies such as robust control,adaptive control,sliding mode control and other hybrid methods have made significant progresses in hypersonic control.Then,the main challenges of control approaches for hypersonic vehicle are systematically analyzed in detail.
This paper proposed an improved artificial physics(AP)method to solve the autonomous navigation problem for multiple unmanned aerial vehicles(UAVs)/unmanned ground vehicles(UGVs)heterogeneous coordination in the three-dimensional space.The basic AP method has a shortcoming of easily plunging into a local optimal solution,which can result in navigation fails.To avoid the local optimum,we improved the AP method with a random scheme.In the improved AP method,random forces are used to make heterogeneous multi-UAVs/UGVs escape from local optimum and achieve global optimum.Experimental results showed that the improved AP method can achieve smoother trajectories and smaller time consumption than the basic AP method and basic potential field method(PFM).
