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Aiming at the drogue docking control problem in aerial recovery, this paper proposes a performance event-triggered control algorithm based on disturbance observer to stabilize the flexibly towed aerial recovery drogue subject to the unknown airflows, cable towing tensions, limited computation capacity, and actuating power resources with guaranteed transient performance. Firstly, the control-oriented 6 degrees of freedom (DOF) affine nonlinear dynamics of the flexible cable-towed drogue are formulated. Then, the event-triggered extended state observers (ETESO) are established for the trajectory and attitude subsystems by utilizing intermittently measured state, to accurately estimate the lumped disturbances caused by the unmeasurable cable tension and unknown airflow disturbance while reducing the computation cost from the sensor to the observer. Moreover, to constrain the trajectory tracking error within the guaranteed transient performance constraint with any small overshoot, an ETESO-based event-triggered control algorithm for drogue was established to ensure the specified transient performance; finally, the closed-loop stability is discussed using Lyapunov analysis. The simulation results confirmed that this method can not only constrain the drogue within the expected small error range but also effectively reduce computational costs and resource occupation, with the best control effect. [ABSTRACT FROM AUTHOR]

Aiming at the probe docking control problem in aerial recovery, this article proposes a neural-adaptive probe dynamics direct control algorithm with preassigned docking performance for the unmanned aerial vehicle (UAV) to be recovered, even under multiple ambient airflow disturbances and initial docking deviations. The affine nonlinear dynamics of the probe in the inertial axis are formulated, together with the UAV's 6-DOF dynamics, for the convenience of the direct nonlinear docking control design. To compensate UAV's unmeasurable nonlinear dynamics with better approximation property and lower computational burden, the minimal learning parameter (MLP) technique based echo state network (ESN) approximators are constructed by employing the system state approximation errors to adaptively update neural weights learning. Then, to guarantee the preassigned docking performance required by the recovery safety, a finite-time prescribed performance control algorithm incorporated backstepping control law is developed to achieve the desired docking. Both the docking trajectory and forward docking velocity are not only always constrained within the preassigned performance constraints but also finely controlled to achieve accurate rendezvous with the target drogue. The closed-loop stability is discussed with Lyapunov analysis. Numerical simulations are conducted to validate the performance of the docking control algorithm. [ABSTRACT FROM AUTHOR]

This article contrives a neural-adaptive constrained controller of the cable towed air–ground recovery system subject to terrain obstacles, unmeasurable cable tensions, trailing vortex, wind gust, and actuator saturation. In air–ground recovery system modeling, the towed vehicle's nominal 6 DOF affine nonlinear dynamics and the cable system's finite links-joints dynamics are formulated. To achieve accurate air–ground recovery under terrain obstacles, an asymmetric barrier Lyapunov function-based flight controller of the towed vehicle is proposed, by transforming the terrain obstacles into time-varying constraints on the vehicle's trajectory. Then, to approximate the towed vehicle's lumped unknown dynamics caused by the unmeasurable cable tensions and airflows, several echo state network (ESN) approximators are established for velocity and attitude subsystems. By using the state approximation errors-based neural weights learning strategy and minimal learning parameter technique, these ESNs possess better transient behaviors and lower online computational burden. Furthermore, the actuator saturation is automatically monitored and released, by incorporating a specially designed auxiliary compensating system into the angular rate control law for compensation. The stability of the closed-loop system is analyzed. Finally, numerical simulations under two air–ground recovery scenarios are performed to demonstrate the performance of the proposed controller. [ABSTRACT FROM AUTHOR]

In this article, considering the performance limitations of the sensors used in real missions, the cooperative dynamic fuzzy perimeter surveillance (CDFPS) problem and its fluid-based solution framework are proposed for the first time. First, the two-dimensional concentration diffusion distribution function is used to imitate an irregular dynamic perimeter. Then, according to the onboard sensor resolution ratio, a fuzzification process is applied for the perimeter area. On this basis, the detected fuzzy perimeter area is modeled with virtual obstacles (VOs). Considering an obstacle set composed of VOs, fixed obstacles and agents, we transform the CDFPS problem into a unified obstacle avoidance problem for the first time and a fluid-based path planning method is designed based on restrained interfered fluid dynamical system and Lyapunov guidance vector field. To quantify the surveillance effect, two indexes for the CDFPS problem are proposed: the perimeter neutrality index and the phase angle uniformity index. Around these proposed indexes, the attractive/repulsive effects and the multiagent cooperative mechanism are constructed. Finally, the receding horizon control is introduced to further improve the surveillance effect. Simulations show that the proposed framework can drive agents to persistently track the perimeter and establish relatively stable phase angle offsets between adjacent agents. [ABSTRACT FROM AUTHOR]

To enhance the mission success rate, the multi-agent system (MAS) often adopts a formation form to shuttle over complex terrain. Compared with obstacle avoidance in other multi-agent coordinated missions, multi-agent formation (MAF) obstacle avoidance is more challenging because agents must both avoid obstacles and subsequently return to their intended positions in the original formation at a uniform speed. Aiming at the three-dimensional complex obstacle environment, the fluid methodology is extended to the application of the formation issue for the first time. In this paper, an MAF obstacle avoidance framework built upon model-based interfered fluid dynamical system (MIFDS), which is the most representative algorithm in fluid methodology, is proposed. The proposed MIFDS is modified to be more in accordance with the kinematic performance of agents than traditional IFDS by introducing the kinematic model and constraints. Moreover, on the basis of MIFDS and the virtual leader formation structure, a novel original fluid speed adjustment strategy in MIFDS, which is the core to solve the formation issue, is designed to balance obstacle avoidance and formation reconfiguration. Finally, receding horizon control is introduced to further guarantee the performance of obstacle avoidance and motion safety. Simulations are used to demonstrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

In this study, two types of three-dimensional (3-D) flight-based energy management strategies for solar-powered unmanned aerial vehicle (SUAV) long-endurance target tracking are proposed. In SUAV dynamic modeling, we consider the influence of wind on SUAV kinematics. Aiming at the complexity of the long-endurance tracking, namely the long flight time and space spans, the influences of the wind, variations of temperature, air density and solar cell photovoltaic efficiency, and a finite battery capacity are considered in our modified SUAV energy model. Then, considering the mission flexibility, we design two types of energy management strategies that comprehensively utilize the solar energy, gravitational potential energy, and wind to address different situations. The proposed strategies can be divided into several stages in chronological order according to the solar irradiation conditions, electrical energy storage conditions, and relative motion relationships among the SUAV, target, and wind. We then design respective strategies for these stages. The core of our proposed energy management strategies is to design the corresponding objective functions in each stage and the switching conditions between adjacent stages. Finally, we verify our proposed strategies by comparison with the traditional 2-D tracking strategy in a 24-h target tracking mission, and the results show the validity of our proposed strategies. [ABSTRACT FROM AUTHOR]

In autonomous aerial refueling (AAR), the vibration of the flexible refueling hose caused by the receiver aircraft’s excessive closure speed should be suppressed once it appears. This paper proposed an active control strategy based on the permanent magnet synchronous motor (PMSM) angular control for the timely and accurate vibration suppression of the flexible refueling hose. A nonsingular fast terminal sliding-mode (NFTSM) control scheme with adaptive extended state observer (AESO) is proposed for PMSM take-up system under multiple disturbances. The states and the “total disturbance” of the PMSM system are firstly reconstituted using the AESO under the uncertainties and measurement noise. Then, a faster sliding variable with tracking error exponential term is proposed together with a special designed reaching law to enhance the global convergence speed and precision of the controller. The proposed control scheme provides a more comprehensive solution to rapidly suppress the flexible refueling hose vibration in AAR. Compared to other methods, the scheme can suppress the flexible hose vibration more fleetly and accurately even when the system is exposed to multiple disturbances and measurement noise. Simulation results show that the proposed scheme is competitive in accuracy, global rapidity, and robustness. [ABSTRACT FROM AUTHOR]

Nonlinear optimal control (NOC) problem with complex dynamic constraints (CDC) is difficult to compute even with direct method. In this paper, a hybrid two-stage approach integrating an improved backtracking search optimization algorithm (IBSA) with the hp-adaptive Gauss pseudo-spectral methods (hpGPM) is proposed. Firstly, BSA is improved to enhance its convergent speed and the global search ability, by adopting the harmony search strategy and an adaptive amplitude control factor with individual optimum fitness feedback. Then, at the beginning stage of the hybrid search process, an initialization generator is constructed using IBSA to find a near optimum solution. When the change in fitness function approaches to a predefined value which is small enough, the search process is replaced by hpGPM to accelerate the search process and find an accurate solution. By this way, the hybrid algorithm is able to find a global optimum more quickly and accurately. Two NOC problems with CDC are examined using the proposed algorithm, and the corresponding Monte Carlo simulations are conducted. The comparison results show the hybrid algorithm achieves better performance in convergent speed, accuracy and robustness. [ABSTRACT FROM AUTHOR]

The approach and landing (A&L) trajectory optimization is a critical problem for secure flight of reusable launch vehicle (RLV). In this paper, the A&L is divided into two sub-phases, glide phase and flare phase respectively. The flare phase is designed firstly based on the desired touchdown (TD) states. Then, the glide phase is optimized using a proposed novel robust hybrid algorithm that combines advantages of the gravitational search algorithm (GSA) and gauss pseudospectral method (GPM). In the proposed hybrid algorithm, an improved GSA (IGSA) is presented to enhance the convergence speed and the global search ability, by adopting the elite memory reservation strategy and an adaptive gravitational constant adaption with individual optimum fitness feedback. At the beginning stage of search process, an initialization generator is constructed to find an optimum solution with IGSA, due to its strong global search ability and robustness to the initial values. When the change in fitness value satisfies the predefined value, the IGSA is replaced by the GPM to accelerate the search process and to get an accurate optimum solution. Finally, the Monte Carlo simulation results are analyzed in detail, which demonstrate the proposed method is practicable. The comparison with GSA and GPM shows that the hybrid algorithm has better performance in terms of convergence speed, robustness and accuracy for solving the RLV A&L trajectory optimization problem. [ABSTRACT FROM AUTHOR]

We develop an optical injection locking (OIL) based local oscillator (LO) regeneration for continuous variable quantum key distribution (CVQKD) by sending a weak polarization multiplexed pilot carrier from the transmitter. The OIL at the receiver has superior performance in terms of minimum input power and noise level at offset frequencies to the erbium-doped fiber amplifier (EDFA)-based scheme. The weak pilot carrier is recovered both in power and phase via the OIL while incurring little excess noise to the CVQKD system. The phase-locked LO enables heterodyne detection of a Gaussian modulated quantum signal with a simple data-aided phase recovery without pilot tone. The obtained parameters are compatible with a raw key rate of 0.83 Mbit/s in the asymptotic regime over a 22-km fiber transmission. The technique is expected to be used in more phase-sensitive quantum optical applications.

Chromatic dispersion (CD) equalization is one of the core tasks of the digital signal processing (DSP) chain in modern optical coherent receivers. A conventional impulse-invariant method for designing the CD equalization filter is revisited, improved by proper weighting, and reinterpreted as a Fourier series. To improve upon a direct evaluation of the passband least-squares (LS) approximation, we propose to design a CD equalization finite impulse response (FIR) filter based on a discrete LS approximation. The proposed method avoids numerical evaluation of nontrivial functions and relies only on Fourier transform. Its flexibility is corroborated by a filter design demonstration of joint matched filtering and CD equalization.

Clock recovery plays an important role in the digital signal processing (DSP) chain of modern coherent optical receivers. It references the local sampling clock with the signal baudrate and finds the optimal sampling instances by performing endless timing error corrections. At the core of clock recovery, a timing error detector (TED) is used to provide instantaneous error tracking. However, usual TEDs suffer from effects such as chromatic dispersion (CD) and polarization rotation, thus requiring additional efforts to remove those effects before TED. Here we propose a modified square TED based on the signal's cyclic autocorrelation function (CAF), which generalizes its classical counterpart and exhibits a much larger CD tolerance. It provides a time-domain solution of the CD-tolerant TED. The previously analyzed equivalence among the time-domain and the frequency-domain TEDs is reestablished in the framework of spectral correlation. The modified square TED demands a minimum extra complexity. Both numerical simulation and experiments are performed to study the performance of the proposed TED.