Time-varying Angle Research Articles

Finite-Time Line-of-Sight Guidance-Based Path-Following Control for a Wire-Driven Robot Fish.

This paper presents an adaptive line-of-sight (LOS) guidance method, incorporating a finite-time sideslip angle observer to achieve precise planar path tracking of a bionic robotic fish driven by LOS. First, an adaptive LOS guidance method based on real-time cross-track error is presented. To mitigate the adverse effects of the sideslip angle on tracking performance, a finite-time observer (FTO) based on finite-time convergence theory is employed to observe the time-varying sideslip angle and correct the target yaw. Subsequently, classical proportional-integral-derivative (PID) controllers are utilized to achieve yaw tracking, followed by static and dynamic yaw angle experiments for evaluation. Finally, the yaw-tracking-based path-tracking control strategy is applied to the robotic fish, whose motion is generated by an improved central pattern generator (CPG) and equipped with a six-axis inertial measurement unit for real-time swimming direction. Quantitative comparisons in tank experiments validate the effectiveness of the proposed method.

An Improved ELOS Guidance Law for Path Following of Underactuated Unmanned Surface Vehicles.

In this paper, targeting the problem that it is difficult to deal with the time-varying sideslip angle of an underactuated unmanned surface vehicle (USV), a line-of-sight (LOS) guidance law based on an improved extended state observer (ESO) is proposed. A reduced-order ESO is introduced into the identification of the sideslip angle caused by the environmental disturbance, which ensures a fast and accurate estimation of the sideslip angle. This enables the USV to follow the reference path with high precision, despite external disturbances from wind, waves, and currents. These unknown disturbances are modeled as drift, which the modified ESO-based LOS guidance law compensates for using the ESO. In the guidance subsystem incorporating the reduced-order state observer, the observer estimation and track errors are proved uniformly ultimately bounded. Simulation and experimental results are presented to validate the effectiveness of the proposed method. The simulation and comparison results demonstrate that the proposed ELOS guidance can help a USV track different types of paths quickly and smoothly. Additionally, the experimental results confirm the feasibility of the method.

Aerodynamic Effects of Time-Varying Corrugations on Dragonfly Wings in Flapping Flight.

The aerodynamic effects of wing corrugation on insect flight have received widespread attention. However, there has hardly been any specific focus on dynamic changes to corrugation angle in the models. The flexible vein joints containing resilin in the wings of dragonflies and damselflies enable the longitudinal veins to rotate and thereby change the corrugation angles throughout flapping cycles. Therefore, a two-dimensional corrugated airfoil with time-varying corrugation angles is proposed and the aerodynamic performance is evaluated in terms of aerodynamic force, power and efficiency. The results indicate that the airfoil with time-varying corrugations outperforms the rigid one in terms of enhancing thrust and reducing power consumption. The aerodynamic performance of time-varying corrugated airfoils is optimal when the angle varies in a specific range, and an excessively large angle variation may have negative effects. In addition, excessive height or a negative leading edge of the corrugation can lead to a reduction in the thrust. A design concept for the 2D airfoil with time-varying corrugations is provided and the findings are of significance for enhancing the aerodynamic performance of biomimetic flexible flapping-wing vehicles.

Adaptive Dynamic Model-Based Path Following Controller Design for an Unmanned Surface Vessel

Abstract The effective design of a path following controller for Unmanned Surface Vessels (USVs) under uncertain influences induced by various factors such as environmental disturbances is a challenging task. In this study, we propose to ful?lling this task through taking benefits from an online parameter identi?cation technique, the discrete-time sliding mode control (DSMC) method, and the improved line of sight (LOS) algorithm. The Particle Swarm Optimization algorithm (PSO) was adopted to provide initial settings for the straightforward online identification method, i.e., the Forgetting Factor Recursive Least Square method (FFRLS). In order to handle the time-varying sideslip angle of a ship that exists in reality due to environmental disturbances, a multi-model course control scheme is proposed to improve the control performance. For this control scheme, a flexible selection mechanism in-between a heading angle or a course angle tracking controller based on the DSMC method is designed. A solution to ?xing the tracking deviation problem of the LOS guidance law is investigated for which the gradient descent method is introduced. A series of experiments are carried out at sea with a USV called Orca to verify and validate the proposed hybrid path following approach. The results showed that tracking errors mainly induced by environmental disturbances existed but the maximum magnitude among them was small enough and remaining within the acceptable range especially from the marine engineering point of view. These results, to a high degree, validated the robustness and precision of the proposed controller.

Predefined-time prescribed performance second-order sliding mode path following control for underactuated marine surface vehicles using self-structuring NN

This paper proposes a predefined time-prescribed performance second-order sliding mode path following controller for underactuated marine surface vehicles (MSVs) with unknown external environmental disturbances based on predefined time predictor line-of-sight (PTPLOS) guidance. First, a predefined time predictor is designed to address the problem of time-varying sideslip angles, and then a guidance law is designed. Second, a prescribed performance function with predefined times is proposed, which can not only set the rate of convergence and the final convergence range but also set an upper bound on the convergence time. Third, the predefined-time controller is designed in combination with second-order sliding mode control. Then, a self-structuring neural network (SSNN) is developed to approximate external disturbances and uncertainties, and this approach can adaptively adjust the number of neurons, reducing the computational burden while maintaining high approximation accuracy. After that, the closed-loop system is proven to be predefined-time stable by using of the Lyapunov stability theory. Finally, the control method proposed in this paper is validated through numerical simulations, demonstrating its effectiveness.

Numerical investigation on the use of various blade tips for the helicopter's main rotor blade in forward flight regarding aerodynamic performance and HSI noise considerations

The goal of this research is to investigate aerodynamic performance and high-speed impulsive (HSI) noise of various blade tips for the helicopter's main rotor in forward flight. For this purpose, three-dimensional compressible flow field around the rotor blades is numerically simulated by the solution of the unsteady Reynolds averaged Navier-Stokes (URANS) equations with the "SST k-ω" turbulence model. Solution is quantified by the calculation of torque, drag, and thrust coefficients of CQ, CD, CT, and L/D ratio. HSI noise on the rotor plane is assessed by the calculation of sound pressure level at certain points of the flow field using the Ffowcs Williams-Hawking (FW-H) equation. Blade tips are eleven and include anhedral, dihedral, Eagle and combinations of them, and also Blue Edge and rectangular. The combinations are inspired by the tip configurations of the fixed wings. In this regard effects of the tip geometry parameters including curvature and height of its parts have been considered as well. All of the tips are examined for two flight conditions of Caradonna and Tung two-blade rotor with fixed pitch angle and time-varying pitch angles. Based on the present results, it is found that blade tips of dihedral family do not improve the aerodynamic performance of the helicopter blade. Also, addition of anhedral part to the blade tip improves the L/D ratio. According to the present acoustic analysis, it was seen that after the Blue Edge, the Eagle tip stands in order of priority. For the condition of Caradonna and Tung two-blade rotor with tip Mach number of 0.8 and advance ratio of 0.2, HSI noise of the Eagle-tip blade decreases by 2.39 % compared to that of the two-blade rotor with rectangular tip. However, the aerodynamics performance of the Eagle tip is much better than that of the Blue Edge.

Improved Stanley guidance law–based adaptive path-following control of underactuated ship with state-constrained and time-varying drift angle

To improve the following performance in large curve path and time-varying drift angle, a reduced-order extended state observer is added to the Improved Stanley Guidance Law (EISGL). Combining with the dynamic surface control (DSC), an adaptive auxiliary system is simultaneously built to compensate for the effect of the state constraints on the system. A barrier Lyapunov function combined with a prescribed performance function is designed to constrain the heading angle error of path following. Adaptive laws are also designed to approximate errors, estimating perturbation in poor sea condition. Lyapunov stability analysis shows that all signals are semi-global coherent and eventually bounded. In conclusion, the numerical comparison simulation experiments verify that the scheme has a strong anti-jamming capability and achieves good path following in large curve path.

Modelling the unsteady lift of a pitching NACA 0018 aerofoil using state-space neural networks

The development of simple, low-order and accurate unsteady aerodynamic models represents a crucial challenge for the design optimisation and control of fluid dynamical systems. In this work, wind tunnel experiments of a pitching NACA 0018 aerofoil conducted at a Reynolds number $Re = 2.8 \times 10^5$ and at different free-stream turbulence intensities are used to identify data-driven nonlinear state-space models relating the time-varying angle of attack of the aerofoil to the lift coefficient. The proposed state-space neural network (SS-NN) modelling technique explores an innovative methodology, which brings the flexibility of artificial neural networks into a classical state-space representation and offers new insights into the construction of reduced-order unsteady aerodynamic models. The work demonstrates that this technique provides accurate predictions of the nonlinear unsteady aerodynamic loads of a pitching aerofoil for a wide variety of angle-of-attack ranges and frequencies of oscillation. Results are compared with a modified version of the Goman–Khrabrov dynamic stall model. It is shown that the SS-NN methodology outperforms the classical semi-empirical dynamic stall models in terms of accuracy, while retaining a fast evaluation time. Additionally, the proposed models are robust to noisy measurements and do not require any pre-processing of the data, thus involving only a limited user interaction. Overall, these features make the SS-NN technique an excellent candidate for the construction of accurate data-driven models from experimental fluid dynamics data, and pave the way for their adoption in applications entailing design optimisation and real-time control of systems involving lift.

Fixed-time angle of attack constrained control for aircraft considering dynamic icing process

Aircraft icing deteriorates aerodynamic performance and reduces stall angle of attack, the fast convergence rate of tracking error is required to stabilize the aircraft when aircraft icing occurs. The state-of-the-art control methods for icing aircraft mostly assume that the icing of aircraft is instantaneous. Aiming at these issues, a fixed-time angle of attack-constrained control strategy is designed considering dynamic icing process. In order to explore the variation of aerodynamic coefficients in the process of dynamic icing, an ice wind tunnel experiment is implemented, and the relationship between lift coefficient, drag coefficient and pitching moment coefficient with angle of attack and icing intensity is obtained by fitting method. In order to prevent the stalling problem caused by the decrease of the stalling angle of attack in the process of dynamic icing, a method to determine the stalling angle of attack based on deep neural network is proposed. Considering the asymmetric and time-varying angle of attack constraint, a fixed-time convergent angle of attack-constrained robust control method is designed. The ice wind tunnel experiment shows the process of dynamic icing of the airfoil, and the simulation results verify the effectiveness of the proposed control method.

Mutual-information based optimal experimental design for hyperpolarized ^{13}C-pyruvate MRI

A key parameter of interest recovered from hyperpolarized (HP) MRI measurements is the apparent pyruvate-to-lactate exchange rate, k_{{textrm PL}}, for measuring tumor metabolism. This manuscript presents an information-theory-based optimal experimental design approach that minimizes the uncertainty in the rate parameter, k_{{textrm PL}}, recovered from HP-MRI measurements. Mutual information is employed to measure the information content of the HP measurements with respect to the first-order exchange kinetics of the pyruvate conversion to lactate. Flip angles of the pulse sequence acquisition are optimized with respect to the mutual information. A time-varying flip angle scheme leads to a higher parameter optimization that can further improve the quantitative value of mutual information over a constant flip angle scheme. However, the constant flip angle scheme, 35 and 28 degrees for pyruvate and lactate measurements, leads to an accuracy and precision comparable to the variable flip angle schemes obtained from our method. Combining the comparable performance and practical implementation, optimized pyruvate and lactate flip angles of 35 and 28 degrees, respectively, are recommended.

Distributed adaptive cooperative guidance against maneuvering targets with time-varying terminal angle constraint and overload saturation

Distributed adaptive cooperative guidance problem for multiple missiles intercepting a maneuvering target with time-varying terminal angle constraint and overload saturation is investigated in this paper. First of all, an extended state observer (ESO) is designed for each missile which can estimate the line-of-sight (LOS) rate and unknown external disturbances simultaneously. Secondly, a sliding manifold is proposed for each missile which consists of states of the ESO and neighbor terminal angle formation error. Then, a distributed cooperative guidance law is presented which can achieve the terminal angle constrained cooperative guidance. Furthermore, in order to deal with overload saturation, an auxiliary state is designed for the stability of the whole guidance system. Thirdly, the design process of cooperative guidance law is summarized as a guidance algorithm and the stability of the guidance error dynamics is proved via Lyapunov theories. Finally, the validity of the presented cooperative guidance algorithm is demonstrated by a numerical example.

A new dynamic model for gear systems incorporating the sliding friction and time-varying pressure angle

The dynamic characteristics of gear systems are affected by the sliding friction and time-varying pressure angle. In the previous studies, the sliding friction is usually neglected for simplification, while the pressure angle is always considered as a constant. Therefore, the coupling effect between the sliding friction and pressure angle is not considered. In view of this, a new six degrees-of-freedom model for spur gear systems is proposed. The sliding friction and time-varying pressure angle are emphasized in this model. The differential equations of motion are derived using Lagrange’s equation. The Runge–Kutta numerical integration algorithm is applied to gain dynamic response. The proposed model is somewhat more realistic compared to previous models. Furthermore, parametric studies are carried out to reveal the effects of friction coefficient and equivalent shaft-bearing stiffness (directly related to translational motion and time-varying pressure angle). The coupling effect between the sliding friction and pressure angle is verified not only by the mathematical model but also by the dynamic response. The results reveal that both friction coefficient and equivalent shaft-bearing stiffness affect the contact ratio and pressure angle and lead to distinctive dynamic responses. This research can provide a foundation for further study and be used as a reference for gear system design and vibration prediction.

Continuously tunable modulation scheme for homodyne detection and state tomography.

Homodyne detection is a common self-referenced technique to extract optical quadratures. Due to ubiquitous fluctuations, experiments measuring optical quadratures require homodyne angle control. Current homodyne angle locking techniques only provide high quality error signals in a span significantly smaller than π radians, the span required for full state tomography, leading to inevitable discontinuities during full tomography. Here, we present and demonstrate a locking technique using a universally tunable modulator which produces high quality error signals at an arbitrary homodyne angle. Our work enables continuous full-state tomography and paves the way to backaction evasion protocols based on a time-varying homodyne angle.

Effect of clearance on the dynamic characteristics of high-speed rolling bearings with multiple defects

Clearance is a pivotal factor in determining the fatigue life of high-speed rolling bearings (HSRBs). As HSRBs naturally experience various defects, their clearance levels tend to rise. However, a clear understanding of the vibration caused by clearance is still lacking. To address this gap, a five-degree-of-freedom dynamics model for HSRBs is proposed. This model accounts for centrifugal force, gyroscopic moment, and time-varying contact angle. In addition, the proposed model incorporates asymptotic theory to describe the defect process and the time-varying contact force derived from the Hertzian point contact theory between rolling elements and raceways. Furthermore, the model considers the variations in load zone and rolling element velocity that arise due to clearance. Applying this model, the dynamic response of HSRBs with different level clearances is calculated. The model's correctness is verified by comparing the dynamic response with the finite element model results and data measured using a test rig built for aero-engine spindle bearing. The results demonstrate that the extent of the load zone shrinks as the clearance increases, although the reduction rate gradually slows down. Since the bearing is loaded only in the load zone, aggravated clearance causes rolling elements to slip in the non-load zone. The effect of clearance on contact force is significantly weaker pronounced than that of defects. These research findings provide a theoretical foundation for the analysis and performance prediction of HSRBs and have important reference values for their optimal design.

Sideslip angle observation-based LOS and adaptive finite-time path following control for sailboat

In this article, double finite-time observers-based line-of-sight guidance (DFLOS) and adaptive finite-time control (DFLOS-AFC) scheme is presented for path following of sailboat. The time-varying sideslip angle is accurately observed by double finite-time sideslip observers (DFSO), which improves the robustness and accuracy of line-of-sight guidance. For heading controller, the finite-time filter is used to solve the differential explosion problem of the virtual control law. The second order integral terminal sliding mode is devised to ensure the precision of heading control. Finite-time auxiliary system is introduced to compensate for actuator saturation constraints. Model uncertainties and external disturbance are compensated through three adaptive updated parameters, which reduces the calculation complexity of heading control system. Finally, simulation and comparisons results demonstrate the effectiveness of DFLOS-AFC scheme.

Super-Twisting Sliding Mode Control for the Trajectory Tracking of Underactuated USVs with Disturbances

For an underactuated unmanned surface vehicle (USV), time-varying external disturbances affect the accuracy of trajectory tracking. To ensure trajectory tracking accuracy, in this paper the reduced-order extended state observer (ESO) and the super-twisting second-order sliding mode controller are adopted. The ESO is designed to address the unknown time-varying sideslip angle in the guidance law. Additionally, the super-twisting technology contributes to a reduced chattering effect of the sliding mode. The Lyapunov method is used to analyze the stability of the tracking system and prove that the proposed controllers can ensure the convergence of the tracking errors in finite time. The simulation experiments of the proposed super-twisting sliding mode control (STSMC) and adaptive sliding mode control (ASMC) methods are compared. The results show that the STSMC method enables the USV to complete the task of the reference trajectory tracking. The chattering of the STSMC is also significantly reduced compared to that of the ASMC.

Time-varying modeling and intelligent compensation control of singletendon-sheath structure of surgical robot

The inaccurate force and position control of tendon sheath system (TSS) due to nonlinear friction during surgery seriously hinders its development in the field of precision surgical robots. To this end, this paper proposes a time-varying bending angle estimation method under the state of sensorless offline identification combined with robot kinematics by analyzing the friction of the TSS and the deformation of the robot during the movement, and establishes a force and position transfer model with time-varying path trajectory (SJM model). The model uses B-spline curve to fit tendon-sheath trajectory. In order to further improve the control accuracy of force and position, a new intelligent feedforward control strategy that integrates the SJM model and a neural network algorithm is proposed. In order to gain an in-depth understanding of the transmission process of force and position and to demonstrate the validity of the SJM model, an experimental platform for the TSS was built. A feedforward control system under the MATLAB environment was built with the aim of verifying the accuracy of the intelligent feedforward control strategy. The system innovatively combines the SJM model with BP and RBF neural networks, respectively. The experimental results showed that the correlation coefficients (R2) of force and position transfer are above 99.10% and 99.48%, respectively. Ultimately, we compared the intelligent feedforward and intelligent control strategy under a single neural network, and observed that the intelligent feedforward control strategy has a better effect.

Modeling of dynamic cutting forces in thin-walled structures trimming

Cutting force plays an important role in the analysis of machining dynamics. In trimming of thin-walled structures, the stick-out length of the workpiece is very large when compared with the traditional milling process, which may result in a large vibration velocity along the tool axis. Since the amplitude of the vibration velocity of the workpiece is comparable to that of the tool velocity caused by the rotary motion of the spindle, it affects the relative velocity between the tool and the workpiece, making the trimming process an oblique cutting process with a time-varying inclination angle, instead of a constant value β, the helix angle of the tool. To this end, we developed a dynamic cutting force model to investigate this effect, and compared simulated and dynamometer-measured cutting forces to validate the established model. The results show that the vibration velocity of the workpiece in the trimming process has a modulating effect on cutting forces, which can significantly reduce the amplitude of the cutting force along the tool axis.

Extended Drones Tracking From ISAR Images With Doppler Effect and Orientation Based Robust Sub-Random Matrices Algorithm

The simultaneous imaging and tracking of drones and small UAVs is one of the most challenging problems in inverse synthetic aperture radar (ISAR) signal processing and has received significant attention recently. Wide-angle ISAR imaging may offer better resolution and richer geometrical features. Aiming at this issue, we propose a new algorithm for multiple extended drone targets (EDTs) detection and tracking from wide-angle ISAR images. Since a conventional tracking algorithm using a random matrices model (RMM) is not accurate enough to reconstruct a drone's extension by one ellipse, an appropriate technique needs to be developed for ISAR imaging and tracking of EDTs. This paper models the EDT's extension as multiple ellipses with a time-varying orientation angle and solves the resulting interference problem involving data association between the nonlinear measurements and sub-ellipses. Recently, the multi-Bernoulli (MB) filter for extended targets has been proposed with the RMM approach for linear ellipsoidal target tracking by additional state variables. However, the implementation of the MB-RMM filter for nonlinear non-Gaussian models and the Doppler effect has not been presented, especially for ISAR images. We consider linearizing the nonlinear observations to solve the nonlinearity due to the Doppler effect, target motion, and wide-angle ISAR images. We presented a new robust Sub-RMM-MB-TBD filter to obtain the estimated orientation of EDT's shape after using the range-only motion compensation that uses both range and Doppler information. Moreover, the authors applied the k-space algorithm to generate ISAR image. Simulation results demonstrate this remarkable performance.

Training Beam Sequence Design for mmWave Tracking Systems With and Without Environmental Knowledge

In this paper, we consider a millimeter wave multiple-input single-output tracking system, where the time-varying angle of departure (AoD) is assumed to change following a discrete state Markov process. Depending on whether the associated AoD transition function is available or not, we propose two different training beam sequence design approaches. Specifically, in the case when the AoD transition function is available, we leverage the maximum a posteriori criterion to estimate the updated AoD in each beam tracking period. Since it is infeasible to derive an explicit expression for the resultant estimation error rate, we turn to its upper bound, which possesses a closed-form expression and is therefore used as the objective function to optimize the training beam sequence. Considering the complicated objective function and the unit modulus constraints imposed by the analog phase shifters, we resort to a particle swarm algorithm to solve the formulated optimization problem. In the case when the AoD transition function is unavailable, we turn to the maximum likelihood criterion for AoD estimation. To cope with the unknown AoD transition function, we reformulate the beam tracking problem as a partially observable Markov decision process problem and develop an actor-critic reinforcement learning framework to obtain an efficient training beam sequence design. Numerical results demonstrate superiorities of the proposed training beam sequence design approaches for both two cases.