| IN recent years,with the rapid improvement of microprocessor computing performance and the in-depth study of intelligent control methods,the flight capability of unmanned helicopter has been greatly optimized and began to be widely used in civil and military fields.Many researchers have participated in the research and development and control design of unmanned helicopter.The dynamic characteristics of single rotor unmanned helicopter,such as underactuation,highly coupling and nonlinearity,make the design of control strategy for unmanned helicopter full of challenges.Taking the unmanned helicopter as the research object,this dissertation investigates the attitude and position control design of small and nano unmanned helicopter.Based on iterative learning,reinforcement learning,fuzzy logic and other algorithms,a variety of nonlinear flight control algorithms are designed,and then the unmanned helicopter system is used as the experimental platform for gradual improvement:the numerical simulation of the unmanned helicopter is completed first,and then it is transferred to the hardwarein-loop platform experiment of small unmanned helicopter,and finally the six degreeof-freedom(DOF)experiment of the nano unmanned helicopter is completed.The main work of this dissertation is as follows:1.The nonlinear modeling problem of the nonlinear control design of the unmanned helicopter system is investigated.The dynamic properties of the unmanned helicopter are analyzed,and a complete dynamic system model of unmanned helicopter for control design is obtained.It lays the foundation for the subsequent control strategy design.2.Considering the underactuated properties of unmanned helicopter,the dynamic model of the unmanned helicopter system is divided into an attitude dynamic subsystem and a position dynamic subsystem.The controller based on iterative learning control is designed to realize the position and attitude tracking control of unmanned helicopter in the simulation environment.3.Because of the difference between the numerical simulation and the actual application,a hardware-in-loop(HIL)small unmanned helicopter experimental platform is built.The control problem of the small unmanned helicopter is investigated under the effects of unknown external disturbances and modeling uncertainties,a control strategy based on reinforcement learning and sliding mode control is designed.The attitude tracking control of the small unmanned helicopter is realized in the HIL experimental platform.4.Owing to the coupling relationship between the position subsystem and the attitude subsystem,a finite-time convergence position loop controller based on fuzzy logic and an exponential convergence attitude controller based on terminal sliding mode are designed.The virtual location information is added in the HIL experimental platform.The tracking control of the small unmanned helicopter is realized in the improved HIL experimental platform.5.Considering that the HIL platform restricts the flight movement of unmanned helicopter and cannot directly reflect the position state,a six DOF nano unmanned helicopter platform is built.The robust control problem of the position and attitude control of the nano unmanned helicopter is investigated.An adaptive terminal sliding mode control method based on the nano helicopter nonlinear dynamic model is designed in the position loop,and a nonlinear control strategy based on robust integral of the signum of the error(RISE)method is designed in the attitude loop.The position tracking of nano unmanned helicopter is realized in the six DOF platform.In this dissertation,for each control design,the stability of the closed-loop system is proved via Lyapunov based stability analysis.At the same time,the real-time flight experimental results are employed to validate the good performances of the proposed control schemes.Therefore,the effectiveness of all the control strategy in this dissertation is provided both in theory and in practice. |
