Transition control of a tail-sitter unmanned aerial vehicle with L1 neural network adaptive control

The main task of this work is to design a control system for a small tail-sitter Unmanned Aerial Vehicle(UAV)during the transition process.Although reasonable control performance can be obtained through a well-tuned single PID or cascade PID control architecture under nominal conditions,large or fast time-varying disturbances and a wide range of changes in the equilibrium point bring nonlinear characteristics to the transition control during the transition process,which leads to control precision degradation.Meanwhile,the PID controller’s tuning method relies on engineering experiences to a certain extent and the controller parameters need to be retuned under different working conditions,which limits the rapid deployment and preliminary validation.Based on the above issues,a novel control architecture of L1 neural network adaptive control associated with PID control is proposed to improve the compensation ability during the transition process and guarantee the security transition.The L1 neural network adaptive control is revised to solve the multi-input and multi-output problem of the tail-sitter UAV system in this study.Finally,the transition characteristics of the time setting difference between the desired transition speed and the desired transition pitch angle are analyzed.

A study of PID and L1 adaptive control for automatic balancing of a spacecraft three-axis simulator

Purpose–The three-axis simulator relies on the air film between the air bearing and the bearing seat to achieve weightlessness and the frictionless motion condition,which is essential for simulating the micro-disturbance torque of a satellite in outer space.However,at the beginning of the experiment,the disturbance torque caused by the misalignment between the center of gravity of the simulator and the center of rotation of the bearing is the most important factor restricting the use of the space three-axis simulator.In order to solve this problem,it is necessary to set the balance adjustment system on the simulator to compensate the disturbance torque caused by the eccentricity.The paper aims to discuss these issues.Design/methodology/approach–In this paper,a study of L1 adaptive automatic balancing control method for micro satellite with motor without other actuators is proposed.L1 adaptive control algorithm adds the low-pass filter to the control law,which in a certain sense to reduce the high-frequency signal and speed up the response time of the controlled system.At the same time,by estimating the adaptive parameter uncertainty in object,the output error of the state predictor and the controlled object can be stabilized under Lyapunov condition,and the robustness of the system is also improved.The automatic balancing method of PID is also studied in this paper.Findings–Through this automatic balancing mechanism,the gravity disturbance torque can be effectively reduced down to 10−6 Nm,and the automatic balancing time can be controlled within 7 s.Originality/value–This paper introduces an automatic balancing mechanism.The experimental results show that the mechanism can greatly improve the convergence speed while guaranteeing the control accuracy,and ensuring the feasibility of the large angle maneuver of spacecraft three-axis simulator.

L_1 adaptive control with sliding-mode based adaptive law

This paper presents an adaptive control scheme with an integration of sliding mode control into the L1 adaptive control architecture, which provides good tracking performance as well as robustness against matched uncertainties. Sliding mode control is used as an adaptive law in the L1 adaptive control architecture, which is considered as a virtual control of error dynamics between estimated states and real states. Low-pass filtering mechanism in the control law design prevents a discontinuous signal in the adaptive law from appearing in actual control signal while maintaining control accuracy. By using sliding mode control as a virtual control of error dynamics and introducing the low-pass filtered control signal, the chattering effect is eliminated. The performance bounds between the close-loop adaptive system and the closed-loop reference system are characterized in this paper. Numerical simulation is provided to demonstrate the performance of the presented adaptive control scheme.