Research On Optimal Control Of UAV With Arms Based On Multi-machine Cooperative Competition And Manipulator Bi-quadratic Functional

With the rapid development of Unmanned Aerial Vehicle(UAV),it has been widely used in various fields such as industrial and commercial,household civil,party and government organs,national defense and military.In view of the characteristics of multi-input multi-output,nonlinearity and strong coupling in the flight control process of the armed unmanned aerial vehicle,how to achieve the comprehensive optimization of various performance indicators in the flight control process of the unmanned aerial vehicle,this paper proposes a Research strategy for optimal control of armed unmanned aerial vehicle with multi-machine cooperative competition and double quadratic functional robotic arm The research is mainly carried out from two aspects: multi-machine cooperative competition optimal control strategy and multi-joint mechanical arm quadratic functional optimal control,so as to achieve comprehensive optimal control of the unmanned aerial vehicle.(?)Research on Optimal Control Strategy of Multi-UAVs Target Tracking and Coordinated CompetitionIn order to study the optimal control strategy for multi-UAV target tracking and coordinated competition,this paper proposes a Winner-Take-All(WTA)optimal control strategy for multi-machine collaborative competition.In the process of cooperative competition flight,the UAV with the smallest control energy is found,so as to realize the multi-machine cooperative optimal control strategy.First,build a flight path planning algorithm.According to the local minimum value of the traditional artificial potential field algorithm,this paper combines the actual flight control situation of the UAV,improves the artificial potential field function and introduces fuzzy control decision-making power to achieve During the flight of the UAV,the aim of avoiding the local minimum flight control is achieved,and finally the dynamic trajectory tracking control during the cooperative flight of multiple UAVs is realized.Secondly,this paper designs a dual-closed-loop speed tracking controller with a finite-time convergence high-order differentiator to achieve speed control and tracking of the target tracking trajectory.Finally,in terms of collaborative competition,this paper designs a multiUAV collaborative competition strategy based on the WTA model,which is intended to find the minimum control energy from multiple UAVs,and ultimately achieve the optimal control strategy for UAV flight.Theoretical analysis and Simulink numerical simulation results show that the model proposed in this paper has the advantages of fast convergence,good tracking efficiency,high control accuracy,strong stability,good robustness,and the advantages of avoiding chattering.(?)Research on Optimal Control of Double Quadratic Functional Approximation for Manipulator's Adaptive RBF Neural NetworkIn order to solve the problem of optimal control in the nonlinear manipulator system,it is difficult to balance the proportion of control energy and control error,this paper proposes a double quadratic optimization based on adaptive radial basis function(RBF)neural network two-stage superposition optimization The functional optimal solution model,so as to achieve a comprehensive optimal control with a small control energy to maintain a small control error in a nonlinear mechanical arm control system.In the model proposed in this paper,first,a linear error function is designed to act on the nonlinear manipulator control equation,and an adaptive RBF network is used to approximate the uncertain terms in the nonlinear control equation to form a closed-loop feedback system.Optimal control of nonlinear systems.Secondly,the required parameters are compounded into the solution domain of the biquadratic functional,and a new type of recursive neural network is designed to solve the constrained biquadratic model to achieve fast convergence of the model solution and obtain its solution.Through theoretical analysis and Simulink numerical simulation examples,it is verified that the proposed model can effectively improve the control accuracy,stability,robustness and adaptability of the nonlinear system,so as to realize the comprehensive optimal control of the nonlinear mechanical arm system.In summary,in order to achieve the comprehensive and optimal performance indicators in the flight control process of the armed unmanned aerial vehicle,this paper conducts research from two aspects to jointly realize the comprehensive optimal control of the nonlinear armed unmanned aerial vehicle control process.