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.

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.

Quadcopter UAV Modeling and Automatic Flight Control Design

The mathematical model of quadcopter-unmanned aerial vehicle(UAV)is derived by using two approaches:One is the Newton-Euler approach which is formulated using classical mechanics;and other is the Euler-Lagrange approach which describes the model in terms of kinetic(translational and rotational)and potential energy.The proposed quadcopter′s non-linear model is incorporated with aero-dynamical forces generated by air resistance,which helps aircraft to exhibits more realistic behavior while hovering.Based on the obtained model,the suitable control strategy is developed,under which two effective flight control systems are developed.Each control system is created by cascading the proportional-derivative(PD)and T-S fuzzy controllers that are equipped with six and twelve feedback signals individually respectively to ensure better tracking,stabilization,and response.Both proposed flight control designs are then implemented with the quadcopter model respectively and multitudinous simulations are conducted using MATLAB/Simulink to analyze the tracking performance of the quadcopter model at various reference inputs and trajectories.

Winning Probability Estimation Based on Improved Bradley-Terry Model and Bayesian Network for Aircraft Carrier Battle

To provide a decision-making aid for aircraft carrier battle,the winning probability estimation based on Bradley-Terry model and Bayesian network is presented. Firstly,the armed forces units of aircraft carrier are classified into three types,which are aircraft,ship and submarine. Then,the attack ability value and defense ability value for each type of armed forces are estimated by using BP neural network,whose training results of sample data are consistent with the estimation results. Next,compared the assessment values through an improved Bradley-Terry model and constructed a Bayesian network to do the global assessment,the winning probabilities of both combat sides are obtained. Finally,the winning probability estimation for a navy battle is given to illustrate the validity of the proposed scheme.

Condition-based maintenance optimization for continuously monitored degrading systems under imperfect maintenance actions

Condition-based maintenance(CBM) is receiving increasing attention in various engineering systems because of its effectiveness. This paper formulates a new CBM optimization problem for continuously monitored degrading systems considering imperfect maintenance actions. In terms of maintenance actions,in practice, they scarcely restore the system to an as-good-as new state due to residual damage. According to up-to-data researches, imperfect maintenance actions are likely to speed up the degradation process. Regarding the developed CBM optimization strategy, it can balance the maintenance cost and the availability by the searching the optimal preventive maintenance threshold.The maximum number of maintenance is also considered, which is regarded as an availability constraint in the CBM optimization problem. A numerical example is introduced, and experimental results can demonstrate the novelty, feasibility and flexibility of the proposed CBM optimization strategy.

Intelligent Silent Zone for Source-Location Privacy Based on Context-Awareness in WSNs

In many wireless sensor networks(WSNs)applications,the preservation of source-location privacy plays a critical role in concealing context information,otherwise the monitored entities or subjects may be put in danger.Many traditional solutions have been proposed based on the creation of random routes,such as random walk and fake sources approach,which will lead to serious packet delay and high energy consumption.Instead of applying the routing in a blind way,this article proposes a novel solution for source location privacy in WSNs by utilizing sensor ability of perceiving the presence a mobile attacker nearby,for patient attackers in particular to increase the safety period and decrease the data delivery delay.The proposed strategy forms an intelligent silent zone(ISZ)by sacrificing only a minority of sensor nodes to entice patient attackers away from real packet routing path.The analysis and simulation results show that the proposed scheme,besides providing source location privacy energy efficiently,can significantly reduce real event reporting latency compared with the existing approaches.

Capacity Analysis on Distributed Antenna System with Imperfect CSI over Rayleigh Fading Channel

Considering that perfect channel state information(CSI)is hard to obtain in practice,the capacity of downlink distributed antennas system(DAS)with imperfect CSI is analyzed over Rayleigh fading channel.Based on the performance analysis,using the probability density function and numerical calculation,an accurate closedform expression of ergodic capacity of downlink DAS under imperfect CSI is derived.It includes the one under perfect CSI as a special case.This theoretical expression can provide good performance evaluation for downlink DAS for both perfect and imperfect CSI due to its accuracy.Simulation results indicate that the theoretical analysis agrees well with the corresponding simulation,and the capacity can be increased effectively by decreasing the estimation error and/or path loss.

Adaptive Energy Efficient Power Allocation Scheme for DAS with Multiple Receive Antennas

Energy efficiency(EE)of downlink distributed antenna system(DAS)with multiple receive antennas is investigated over composite Rayleigh fading channel that takes the path loss and lognormal shadow fading into account.Our aim is to maximize EE which is defined as the ratio of the transmission rate to the total consumed power under the constraints of the maximum transmit power of each remote antenna.According to the definition of EE,the optimized objective function is formulated with the help of Lagrangian method.By using the Karush-KuhnTucker(KKT)conditions and numerical calculation,considering both the static and dynamic circuit power consumptions,an adaptive energy efficient power allocation(PA)scheme is derived.This scheme is different from the conventional iterative PA schemes based on EE maximization since it can provide closed-form expression of PA coefficients.Moreover,it can obtain the EE performance close to the conventional iterative scheme and exhaustive search method while reducing the computation complexity greatly.Simulation results verify the effectiveness of the proposed scheme.

Energy Efficient Power Allocation Scheme for Distributed Antenna Systems with Target BER Constraint

The energy efficiency(EE) of distributed antenna system with quality of service(Qo S) requirement is investigated over composite Rayleigh fading channel,where the shadow fading,path loss and Rayleigh fading are all considered. Our aim is to maximize the EE which is defined as the ratio of the transmission rate to the total consumed power subject to the maximum transmit power of each remote antenna constraint and Qo S(target BER) requirement. According to the definition of EE and using the upper bound of average EE,the optimized objective function is provided. Based on this,utilizing Karush-KuhnTucker conditions and numerical calculation,a suboptimal energy efficient power allocation(PA) scheme is developed,and the closedform expression of PA coefficients is derived. The scheme may obtain the EE performance close to the existing optimal scheme. Moreover,it has relatively lower complexity than the existing scheme because only the statistic channel information and less iteration are required. Simulation results show the presented scheme is valid and can meet the target BER requirement,and the EE can be increased as target BER requirement decreases.