Lixin Wang

Bio: Lixin Wang is an academic researcher from Beihang University. The author has contributed to research in topics: Rudder & Wing configuration. The author has an hindex of 1, co-authored 1 publications receiving 7 citations.

Flying -Wing Aircraft Control Allocation

Abstract: Flying -wing configuration aircraft has multi -control -effector s redundant ly . Especially the innovative drag rudder s a re implemented on it . So the control allocation is s trongly nonlinear and multi -ax es coupl ing . The features and applicabilit y in different flight tasks of several typical control allocation methods were summarized . The multi -objective s optimiz ation method based on nonlinear programming was u tilized because of the new characteristic s of the control allocation for the flying wing configuration aircraft. The differences of control allocation results under different objectives were analyzed. And the attitude -tr acking flight control system based on nonlinear dynamic inverse theory was designed, and the d igital simulation using a six degree -of -freedom nonlinear model of certain flying -wing configuration aircraft was conducted, which demonstrate the applicability f or flying -wing configuration aircraft. The results also indicated that the impacts of different optimizing object ives on flight states were remarkable and different.

Minimum drag control allocation for the Innovative Control Effector aircraft: Optimal use of control redundancy on modern fighters

Abstract: The Innovative Control Effector model is a tailless delta-wing aircraft concept equipped with 11 control surfaces with overlapping functionality and two-directional thrust vectoring. The high level of redundancy makes it an interesting object for research on mission-specific control allocation. A (spline-based) incremental control allocation approach is proposed to deal with nonlinear input functions and aerodynamic interaction between multiple control surfaces. Two control allocation modes to minimize drag are proposed and assessed in a general flight scenario. With both modes the average drag is reduced by about 6.5% relative to a standard control allocation scheme. Sensitivity analysis points out that one mode is vulnerable to the choice of initial parameters, whereas the other is primarily sensitive to the accuracy of the onboard model. Improvement of the ICE aerodynamic model is necessary to substantiate the true potential of mission-specific control allocation for next generation aircraft.

Active control using control allocation for UAVs with seamless morphing wing

Abstract: In this paper, a small seamless morphing wing aircraft of MTOW=51 kg is investigated. The leading edge (LE) and trailing edge (TE) control surfaces are positioned in the wing section in span wise. Based on the studying results of aeroelastic wing characteristics, the controller should be designed depending on the flight speed. Compared with a wing of rigid hinged aileron, the morphing wing produces the rolling moment by deflecting the flexible TE and LE surfaces. An iteration method of pseudo-inverse allocation and quadratic programming allocation within the constraints of actuators have be investigated to solve the nonlinear control allocation caused by the aerodynamics of the effectors. The simulation results will show that the control method based on control allocation can achieve the control target.

The decision making algorithm based on inverse-design method and its application in the UAV autonomous flight control system design

Abstract: For Unmanned Air Vehicles (UAV) to flight autonomously, the decision making system must be developed to replace the remote control by the pilot. To shorten the learning time and increase the real-time response, the inverse-design (ID) method is presented to calculate the control input decision inversely by using the desired output and the predictor-corrector algorithm which uses the proportional-integral predicted initial value to compute the control inputs. In the mission description process, the quasi-uniform B-spline is used to generate the desired output by a succession of control points. The genetic algorithm (GA) is also implemented to compare the computing time and the development complexity with the ID method. Simulation shows the ID method based on the predictor-corrector algorithm can be validly and efficiency used in the autonomous flight control system decision making of the UAV, and the ID method is preponderant in online computing, development and computing time reducing than the GA. The analysis and ID method presented in this paper will produce a direct benefit in relation to the decision making method and the design of the UAV autonomous flight control system.