Study On Intelligent Identificationmodeling Of Small-Scale Unmanned Helicopter's Pose Channels

Unmanned aerial vehicle, in particular the small-scale helicopter, has wide useful foreground and gradually is paid attention to by the military, civil and scientific organizations. Relatively, the small-scale helicopter is a military colorific way of research and its core part of technique is unable to open, so we must develop the small-scale helicopter system independently. An accurate model can be used to evaluate the flight characters and design the controller of the small-scale helicopter etc. The small-scale helicopter is a complicated system, so it is difficult to gain an accurate model using Newton law and Ruler equation. Simply approximate physical models only suit the position controller of the small-scale helicopter in ideal situation. In order to guarantee the model precision and the model practicality, the identification method is fit for modeling of the small-scale helicopter. The traditional identification methods have some disadvantages in modeling of the small-scale helicopter, so the intelligent identifiers are used to gain the model of the small-scale helicopter system in this paper.Now the research of flight control of the small-scale helicopter focus on the position control, and the pose control is parried. The accurate position control depend on the pose control, so in this paper the key work is the small-scale helicopter's pose intelligent identification modeling. Finally the basal problems of the close-coupling multi-helicopter harmonious operation system were researched. The primary works and conclusions as following:(1) The structure and dynamics characteristics of the small-scale helicopter were analyzed detailedly, and than the coordinates and the transform between coordinates were introduced. Subsequently, the basic dynamic equation, aero-force and aero-moment acting on the fuselage of the small-scale helicopter were recommended. Finally, the basic steps of the small-scale helicopter's identification modeling were introduced.(2) The unreasonable simple model structure of the small-scale helicopter and the traditional identifier's rigorous requires for the identified system and the used data make the results imprecise. Through theory analyses, a kind of alterable transfer function is used to express the dynamic model set of the small-scale helicopter's pose channels. Subsequently, the transfer function's structure and parameters were gained synchronously using the proposed intelligent identification method; the resulted model can be used to design the pose controller of the small-scale helicopter. This method needn't transform between discrete and continuous transfer function, so the identification error is decreased and the identification performance in high frequency are good. The proposed identification method not only is used to model the small-scale helicopter, but also model the other system that cannot be sample the input–output signal inaccurately. The resulted model can provide input-output restriction to the proposed T-S fuzzy identifier.(3) A linear transfer function can't express the nonlinearity of pose channels, so the data is partitioned; the different section is expressed by different linear function. The T-S fuzzy model is used to express the mentioned structure above. Subsequently, the former member function parameters and the latter linear parameters of the T-S fuzzy rules are gained automatically using the neural network method. The whole fuzzy model structures of the small-scale helicopter are also taken into account. The resulted fuzzy model can be used to design the controller of the small-scale helicopter that have traditional and intelligent advantages.(4) The complicated structure and the flight environment of the small-scale helicopter bring the error with the collected input-output data, so a good flight data collected system was design through integrating up to data electronic, computer and sensor etc. technique. In order to guarantee the conveniences and safety of the experiments, a four free-degrees ground test bed is achieved to simulate the hovering mode and gather the flight attitude input-output data of the small-scale helicopter in this bed. Thereafter the collected data is preprocessed to attain the useful identification data. Finally the parameters of a kind of controller were confirmed through the resulted model before and the small-scale helicopter's attitude angles were controlled to referenced value successfully.(5) In this paper the particularity and practicality of harmony operations of close-coupling multiple helicopters were discussed firstly. Using the model that describes two hovering helicopters carrying one heavy load, an inertia coordinate system and body coordinate systems of each sub-system are established. A nonlinear force model is established too. The equilibrium computation results can be regarded as the reference control inputs of the flight control system under hovering or low-speed flight condition. After the establishment of a translation kinematics model and a posture kinematics model, a coupling dynamics model of the multiple helicopter system is set up. The results can also be regarded as the base to analyze stabilization and design a controller for a close-coupling multiple helicopters harmony operation system.