Automatic landing system using neural networks and radio-technical subsystems

The paper focuses on the design of a new automatic landing system（ALS） in longitudinal plane; the new ALS controls the aircraft trajectory and longitudinal velocity. Aircraft control is achieved by means of a proportional-integral（PI） controller and the instrumental landing system– the first phase of landing（the glide slope） and a proportional-integral-derivative（PID） controller together with a radio-altimeter – the second phase of landing（the flare）; both controllers modify the reference model associated with aircraft pitch angle. The control of the pitch angle and longitudinal velocity is performed by a neural network adaptive control system, based on the dynamic inversion concept, having the following as components： a linear dynamic compensator, a linear observer, reference models, and a Pseudo control hedging（PCH） block. The theoretical results are software implemented and validated by complex numerical simulations; compared with other ALSs having the same radio-technical subsystems but with conventional or fuzzy controllers for the control of aircraft pitch angle and longitudinal velocity, the architecture designed in this paper is characterized by much smaller overshoots and stationary errors.

GUIDANCE AND CONTROL FOR AUTOMATIC LANDING OF UAV

A scheme of guidance and control is presented to meet the requirements for automatic landing of unmanned aerial vehicles (UAVs) based on the airborne digital flight control system and radio tracker on ground station. An automatic landing system is realized for an unmanned aerial vehicle. The results of real time simulation and flight test are given to illustrate the effectiveness and availability of the scheme. Results meet all the requirements for automatic landing of the unmanned aerial vehicle.

Automatic Carrier Landing Control for Unmanned Aerial Vehicles Based on Preview Control

For carrier-based unmanned aerial vehicles(UAVs),one of the important problems is the design of an automatic carrier landing system(ACLS)that would enable the UAVs to accomplish autolanding on the aircraft carrier.However,due to the movements of the flight deck with six degree-of-freedom,the autolanding becomes sophisticated.To solve this problem,an accurate and effective ACLS is developed,which is composed of an optimal preview control based flight control system and a Kalman filter based deck motion predictor.The preview control fuses the future information of the reference glide slope to improve landing precision.The reference glide slope is normally a straight line.However,the deck motion will change the position of the ideal landing point,and tracking the ideal straight glide slope may cause landing failure.Therefore,the predictive deck motion information from the deck motion predictor is used to correct the reference glide slope,which decreases the dispersion around the desired landing point.Finally,simulations are carried out to verify the performance of the designed ACLS based on a nonlinear UAV model.

Guidance and Control Techniques of Carrier-Based Aircraft for Automatic Carrier Landing

We summarize the guidance and control techniques of automatic carrier landing for carrier-based aircraft.First,we analyze the carrier landing operations of the manned fixed-wing aircraft,unmanned fixed-wing aircraft and helicopters.Second,we look into the navigation and guidance system and the flight control methods for current different aircraft.Finally,we draw several conclusions of the development prospects for aircraft carrier landing,including the precision landing control techniques,precision approach and landing guidance techniques,and adaptive,reconfigurable and intelligent flight control techniques.

H_∞ Preview Control for Automatic Carrier Landing

This paper focuses on the application of H_∞preview control in automatic carrier landing system(ACLS)for carrier-based aircraft.Due to the mutual movement between aircraft and carrier,the landing process becomes considerably more challenging compared to a conventional runway landing.ACLS systems mitigate this by predicting deck motion and generating ideal glide slope path for tracking.Although,this predicted glide slope information is available in advance,conventional control structures are still unable to use this future information.H_∞preview control has the ability to utilize this future information for improving tracking response and disturbance rejection.The process of incorporating preview information into ACLS framework and synthesizing the H_∞preview controller is presented.The methodology is verified using the example of F/A-18 automatic carrier landing problem and results are presented.

Iterative Model Predictive Control for Automatic Carrier Landing of Carrier-Based Aircrafts Under Complex Surroundings and Constraints

This paper considers the automatic carrier landing problem of carrier-based aircrafts subjected to constraints,deck motion,measurement noises,and unknown disturbances.The iterative model predictive control(MPC)strategy with constraints is proposed for automatic landing control of the aircraft.First,the long short-term memory(LSTM)neural network is used to calculate the adaptive reference trajectories of the aircraft.Then the Sage-Husa adaptive Kalman filter and the disturbance observer are introduced to design the composite compensator.Second,an iterative optimization algorithm is presented to fast solve the receding horizon optimal control problem of MPC based on the Lagrange’s theory.Moreover,some sufficient conditions are derived to guarantee the stability of the landing system in a closed loop with the MPC.Finally,the simulation results of F/A-18A aircraft show that compared with the conventional MPC,the presented MPC strategy improves the computational efficiency by nearly 56%and satisfies the control performance requirements of carrier landing.

MC-LRF based pose measurement system for shipborne aircraft automatic landing

Due to the portability and anti-interference ability,vision-based shipborne aircraft automatic landing systems have attracted the attention of researchers.In this paper,a Monocular Camera and Laser Range Finder(MC-LRF)-based pose measurement system is designed for shipborne aircraft automatic landing.First,the system represents the target ship using a set of sparse landmarks,and a two-stage model is adopted to detect landmarks on the target ship.The rough 6D pose is measured by solving a Perspective-n-Point problem.Then,once the rough pose is measured,a region-based pose refinement is used to continuously track the 6D pose in the subsequent image sequences.To address the low accuracy of monocular pose measurement in the depth direction,the designed system adopts a laser range finder to obtain an accurate range value.The measured rough pose is iteratively optimized using the accurate range measurement.Experimental results on synthetic and real images show that the system achieves robust and precise pose measurement of the target ship during automatic landing.The measurement means error is within 0.4in rotation,and 0.2%in translation,meeting the requirements for automatic fixed-wing aircraft landing.

Selection of a non-localized landing region for an unmanned helicopter based on an attention model

A new landing region selection algorithm for an unmanned helicopter is proposed based on an attention model.Different from the original attention model,some properties of the possible safe landing regions（e.g.,depth,regional color and motion features）are included in the selection algorithm.Furthermore,regional color and motion features are fused directly into the saliency map because these features do not have the ＂central-peripheral＂property.Experimental results validate the feasibility and efficiency of this approach.

An effective method for performance evaluation of ACLS based on improved grey analytic hierarchy

The performance evaluation of automatic carrier landing system(ACLS)is an important part in the field of carrier aircraft landing control.Combining grey analytic hierarchy theory and data normalization theory,an improved grey analytic hierarchy method is introduced to evaluate the performance of ACLS.A complete performance evaluation indicators system of ACLS is established,and the definition and calculation formula of each indicator are provided.The grey analytic hierarchy model is modified to improve the real-time performance of the algorithm,where traditional expert scoring sampling matrix is substituted by an indicator normalized sample matrix.Taking a certain ACLS as an example,the experimental simulation is carried out,and the simulation results verify the reliability and the accuracy of the improved grey analytic hierarchy method.