Control Allocation For Flying Wing Unmanned Aerial Vehicle With Nonlinear Characteristics Considered

Compared to conventional aircraft, flying wing aircraft with large ratio aspect has highlift-to-drag ratio, good stealth performance. Flying wing aircraft is optimal selection in highaltitude long endurance unmanned aerial vehicle (UAV) layout design. In order to improvethe system reliability, flying wing UAV generally has multiple control surfaces. How tocoordinate the control surfaces deflection in order to meet the flight safety, how to satisfy theposition constraints and rate constraints, these problems must be solved in flying wing UAVcontrol system design. Control allocation technique is an effective way to control the multiplecontrol surfaces flying wing UAV.Paper focus on the problems of flying wing UAV control allocation. These problems arethe couple between control moments and aerodynamic force, the monotonic andnon-monotonic nonlinear characteristics of control surfaces efficiency, the control surfaceefficiency is affected to elastic deformation. The main research work and innovations are asfollows:(1). Make analysis of the flying wing UAV effector characteristics. For large ratio aspectflying wing UAV effector characteristics, analyze the elevons and split rudder controlcharacteristics and usage of resistance. There are three characteristics as follows: the controlmoments and aerodynamic force are coupling, control surfaces efficiency have monotonic andnon-monotonic nonlinear characteristics, control surfaces efficiency is affected to elasticdeformation.(2). Applications of the linearized allocation methods on flying wing UAV is discussed.The model of effectors efficiency is linearized, so the linear model is obtained. Three kinds ofcontrol allocation method are applied on flying wing UAV. These methods are thecombination method, generalized inverse method and the fixed point method. Comparisonshows that the combination method with compensation, redistributed generalized inversemethod and the fixed point method can achieve the success of control moment commandsdistribution. In calculating time and the usage of effectors, three methods have their ownadvantages.(3). Control allocation methods considering the effect of cross coupling is presented.Analyses the cross coupling effect between the split rudder and the adjacent elevon. Twomethods considering the effect of cross coupling is given. The first method is a sequence oflinear programming method, the second method is based on the linear programming method with compensation. The accuracy of allocation, the calculating time and the usage of effectorsare compared. The results show that the two methods both can allocate control momentcommands accurately. The first method use less effectors than the second method, but thesecond method have less calculating time than the first method.(4). A control allocation method considering non-monotonic nonlinear characteristics ispresented. For the non-monotonic nonlinear problems exist, a control allocation method basedon sequential quadratic programming is proposed. Firstly, fitting method is used to get apolynomial function for effectors to control moments. Then, control allocation problemconsidering non-monotonic nonlinear characteristics is converted into standard sequentialquadratic programming problem. Finally, solve the problem with sequential quadraticprogramming algorithm. Compared to linear control allocation method, the simulation resultsshow that the control allocation method based on sequential quadratic programming can moreaccurately allocate control commands, effectively reduce the error distribution.(5). The multi-objective control allocation method based on main objective method ispresented. In different phases of flight conditions and tasks, to achieve different tasks needs,flying wing UAV effectors allocation must balance multiple objectives. Firstly, differentoptimization goals of flying wing UAV in different flight stages are discussed. Then, themulti-objective optimization problem is transformed into single objective optimizationproblem using main target method. Finally, the least drag, the maximum drag and themaximum lift multi-objective control allocation methods are given. Simulation analysis of thethree methods showed that three methods all can successfully achieve the optimization of aparticular target.(6). An open loop control allocation method considering the influences of elastic ispresented. Considering the influence of the elastic deformation, puts forward an open loopcontrol allocation method considering the influences of elastic. Specific steps are as follows,calculate control surface local angle of attack through elastic modal generalized coordinates,get the model of effectors efficiency under the current elastic deformation, control allocation.The open loop control allocation method considering the influences of elastic was validatedthrough simulation.(7). This paper proposes a closed loop control allocation method considering theinfluences of elastic. Considering the influence of the elastic deformation, a closed loopallocation method considering the influences of elastic is presented. This method requires theuse of inverse model method to calculate the actual control moments. The mathematicalderivation of the principle of the method is carried out and analyzed the stability condition of the method. Finally from the perspective of frequency domain characteristics, theperformance of the closed loop control allocate methods are analyzed. The close loop controlallocation method considering the influences of elastic was validated, and compared with theopen loop control allocation method.(8). Design the dynamic inversion control law based on extended state observer, andsimulate the entire flight control system. Firstly, the general design steps of dynamic inversecontrol based on extended state observer is given. Then, group state variables according to thetime scale. The dynamic inversion controllers based on extended state observer are designedfor fast and slow variables separately. The feasibility of the entire flight control system hasbeen verified in two ways. The first way is command tracking simulation, and the second wayis flight path simulation.