Coherent change detection of fine traces based on multi-angle SAR observations

Coherent change detection(CCD) is an effective method to detect subtle scene changes that occur between temporal synthetic aperture radar(SAR) observations. Most coherence estimators are obtained from a Hermitian product based on local statistics. Increasing the number of samples in the local window can improve the estimation bias, but cause the loss of the estimated images spatial resolution. The limitations of these estimators lead to unclear contour of the disturbed region, and even the omission of fine change targets. In this paper, a CCD approach is proposed to detect fine scene changes from multi-temporal and multi-angle SAR image pairs. Multi-angle CCD estimator can improve the contrast between the change target and the background clutter by jointly accumulating singleangle alternative estimator results without further loss of image resolution. The sensitivity of detection performance to image quantity and angle interval is analyzed. Theoretical analysis and experimental results verify the performance of the proposed algorithm.

Vibration Control of A Flexible Marine Riser System Subject to Input Dead Zone and Extraneous Disturbances

An observer-based adaptive backstepping boundary control is proposed for vibration control of flexible offshore riser systems with unknown nonlinear input dead zone and uncertain environmental disturbances.The control algorithm can update the control law online through real-time data to make the controller adapt to the environment and improve the control precision.Specifically,based on the adaptive backstepping framework,virtual control laws and Lyapunov functions are designed for each subsystem.Three direction interference observers are designed to track the timevarying boundary disturbance.On this basis,the inverse of the dead zone and linear state transformation are used to compensate for the original system and eliminate the adverse effects of the dead zone.In addition,the stability of the closed-loop system is proven by Lyapunov stability theory.All the system states are bounded,and the vibration offset of the riser converges to a small area of the initial position.Finally,four examples of flexible marine risers are simulated in MATLAB to verify the effectiveness of the proposed controller.

A Fractional-Order Ultra-Local Model-Based Adaptive Neural Network Sliding Mode Control of n-DOF Upper-Limb Exoskeleton With Input Deadzone

This paper proposes an adaptive neural network sliding mode control based on fractional-order ultra-local model for n-DOF upper-limb exoskeleton in presence of uncertainties,external disturbances and input deadzone.Considering the model complexity and input deadzone,a fractional-order ultra-local model is proposed to formulate the original dynamic system for simple controller design.Firstly,the control gain of ultra-local model is considered as a constant.The fractional-order sliding mode technique is designed to stabilize the closed-loop system,while fractional-order time-delay estimation is combined with neural network to estimate the lumped disturbance.Correspondingly,a fractional-order ultra-local model-based neural network sliding mode controller(FO-NNSMC) is proposed.Secondly,to avoid disadvantageous effect of improper gain selection on the control performance,the control gain of ultra-local model is considered as an unknown parameter.Then,the Nussbaum technique is introduced into the FO-NNSMC to deal with the stability problem with unknown gain.Correspondingly,a fractional-order ultra-local model-based adaptive neural network sliding mode controller(FO-ANNSMC) is proposed.Moreover,the stability analysis of the closed-loop system with the proposed method is presented by using the Lyapunov theory.Finally,with the co-simulations on virtual prototype of 7-DOF iReHave upper-limb exoskeleton and experiments on 2-DOF upper-limb exoskeleton,the obtained compared results illustrate the effectiveness and superiority of the proposed method.

Influence of heat input on the microhardness and microstructure of the welding interface between nickel-based alloy and low-alloy steel

The evolution of microstructure and local properties near the welding interface is essential for the service safety of dissimilar metal welded joints between nickel-based alloy(NA) and low-alloy steel(LA).In this work,NA filler metal was deposited on LA substrate under different heat inputs by tungsten inert gas(TIG) welding.Microstructural characterization and microhardness tests were carried out near the prepared cladding interfaces.Optical and scanning electron microscopes show the lack of evident hardening transition layer along the welding interface.As the heat input increases,the mean hardness of the deposited layer also increases remarkably due to the rising dilution rate.Microstructural characterization shows a significant composition gradient across the cladding interface,but the diffusion gradient is limited to a small range.Under high heat input,a planar grain zone is generated along the interface due to the large temperature gradient across the interface region.

Influence of heat input on microhardness and microstructure across the welding interface between stainless steel and low alloy steel

The welding interface is crucial to the service safety of dissimilar metal weld(DMW)joints between stainless steel(SS)and low alloy(LA)steel.Different status of welding interfaces was prepared by cladding SS consumables to LA steel substrates with different heat inputs via tungsten inert gas arc welding(TIG),followed by a series of microstructural characterizations and hardness tests.Results showed that a hardening and transition layer(TL)would be generated along the welding interface,and the width and hardening degree of the TL would increase with the heat input.Meanwhile,heavy load hardness tests showed that highly severe inhomogeneous plastic deformation and the microcrack would be generated in the interfacial region and the welding interface respectively in the highest heat input sample(1.03 kJ/mm).These results indicate that the increase in heat input would deteriorate the bonding performance of DMW joints.Further microstructural observations showed that the higher hardening degree of the highest heat input sample was mainly attributed to the stronger grain boundary,solution,and dislocation strengthening effects.

Dynamic Event-Triggered Consensus Control for Input Constrained Multi-Agent Systems With a Designable Minimum Inter-Event Time

This paper investigates the consensus control of multi-agent systems(MASs) with constrained input using the dynamic event-triggered mechanism(ETM).Consider the MASs with small-scale networks where a centralized dynamic ETM with global information of the MASs is first designed.Then,a distributed dynamic ETM which only uses local information is developed for the MASs with large-scale networks.It is shown that the semi-global consensus of the MASs can be achieved by the designed bounded control protocol where the Zeno phenomenon is eliminated by a designable minimum inter-event time.In addition,it is easier to find a trade-off between the convergence rate and the minimum inter-event time by an adjustable parameter.Furthermore,the results are extended to regional consensus of the MASs with the bounded control protocol.Numerical simulations show the effectiveness of the proposed approach.

A Hybrid Compensation Scheme for the Input Rate-Dependent Hysteresis of the Piezoelectric Ceramic Actuators

A hybrid compensation scheme for piezoelectric ceramic actuators(PEAs)is proposed.In the hybrid compensation scheme,the input rate-dependent hysteresis characteristics of the PEAs are compensated.The feedforward controller is a novel input rate-dependent neural network hysteresis inverse model,while the feedback controller is a proportion integration differentiation(PID)controller.In the proposed inverse model,an input ratedependent auxiliary inverse operator(RAIO)and output of the hysteresis construct the expanded input space(EIS)of the inverse model which transforms the hysteresis inverse with multi-valued mapping into single-valued mapping,and the wiping-out,rate-dependent and continuous properties of the RAIO are analyzed in theories.Based on the EIS method,a hysteresis neural network inverse model,namely the dynamic back propagation neural network(DBPNN)model,is established.Moreover,a hybrid compensation scheme for the PEAs is designed to compensate for the hysteresis.Finally,the proposed method,the conventional PID controller and the hybrid controller with the modified input rate-dependent Prandtl-Ishlinskii(MRPI)model are all applied in the experimental platform.Experimental results show that the proposed method has obvious superiorities in the performance of the system.

Adaptive Sensor-Fault Tolerant Control of Unmanned Underwater Vehicles With Input Saturation

This paper investigates the tracking control problem for unmanned underwater vehicles(UUVs)systems with sensor faults,input saturation,and external disturbance caused by waves and ocean currents.An active sensor fault-tolerant control scheme is proposed.First,the developed method only requires the inertia matrix of the UUV,without other dynamic information,and can handle both additive and multiplicative sensor faults.Subsequently,an adaptive fault-tolerant controller is designed to achieve asymptotic tracking control of the UUV by employing robust integral of the sign of error feedback method.It is shown that the effect of sensor faults is online estimated and compensated by an adaptive estimator.With the proposed controller,the tracking error and estimation error can asymptotically converge to zero.Finally,simulation results are performed to demonstrate the effectiveness of the proposed method.

Exact controllability of rational expectations model with multiplicative noise and input delay

This paper considers the rational expectations model with multiplicative noise and input delay,where the system dynamics rely on the conditional expectations of future states.The main contribution is to obtain a sufficient condition for the exact controllability of the rational expectations model.In particular,we derive a sufficient Gramian matrix condition and a rank condition for the delay-free case.The key is the solvability of the backward stochastic difference equations with input delay which is derived from the forward and backward stochastic system.

Estimating the Input Power of a Power Plant Using the Efficiency of the Inverter

The study focuses on estimating the input power of a power plant from available data, using the theoretical inverter efficiency as the key parameter. The paper addresses the problem of missing data in power generation systems and proposes an approach based on the efficiency formula widely documented in the literature. In the absence of input data, this method makes it possible to estimate the plant’s input power using data extracted from the site, in particular that provided by the Ministry of the Environment. The importance of this study lies in the need to accurately determine the input power in order to assess the overall performance of the energy system.

Determination of rice panicle numbers during heading by multi-angle imaging

Plant phenomics has the potential to accelerate progress in understanding gene functions and environmental responses. Progress has been made in automating high-throughput plant phenotyping. However, few studies have investigated automated rice panicle counting. This paper describes a novel method for automatically and nonintrusively determining rice panicle numbers during the full heading stage by analyzing color images of rice plants taken from multiple angles. Pot-grown rice plants were transferred via an industrial conveyer to an imaging chamber. Color images from different angles were automatically acquired as a turntable rotated the plant. The images were then analyzed and the panicle number of each plant was determined. The image analysis pipeline consisted of extracting the i2 plane from the original color image, segmenting the image, discriminating the panicles from the rest of the plant using an artificial neural network, and calculating the panicle number in the current image. The panicle number of the plant was taken as the maximum of the panicle numbers extracted from all 12 multi-angle images. A total of 105 rice plants during the full heading stage were examined to test the performance of the method. The mean absolute error of the manual and automatic count was 0.5, with 95.3% of the plants yielding absolute errors within ± 1. The method will be useful for evaluating rice panicles and will serve as an important supplementary method for high-throughput rice phenotyping.

Quantitative Relationship Between Multi-Angle Polarized Reflectance and BRDF of Rock

The traditional remote sensing mainly detects the ground vertically to obtain the 2D information but it is hard to get adequate parameters for the quantitative remote sensing to invert land features. The multi-angle observation can get more detailed and reliable 3D structural parameters of targets, so it makes the quantitative remote sensing applicable. During the process of reflecting, scattering and transmitting the electromagnetic wave, minerals and rocks could reveal the polarized features related to the nature of themselves. Therefore, it has become a new approach of quantitative remote sensing to detect multi-angle polarized information of minerals and rocks. In respect that the polarized reflectance always goes with the bidirectional one, we can obtain the 3D spatial distribution of targets by a polarized means together with detecting its bi-directional reflectance. From the perspective of multi-angle polarized remote sensing mechanism, the quantitative relationship between multi-angle polarized reflectance and the BRDF is studied in this paper. And it is testified that the bi-directional reflectance, polarized reflectance of 45° and the mean value of polarized reflectance are equal to that of the corresponding azimuth angle, zenith angle, detection angle and detection channels in 27t space by experiment.

An approach to wide-field imaging of linear rail ground-based SAR in high squint multi-angle mode

Ground-based synthetic aperture radar(GB-SAR) has been successfully applied to the ground deformation monitoring.However, due to the short length of the GB-SAR platform, the scope of observation is largely limited. The practical applications drive us to make improvements on the conventional linear rail GB-SAR system in order to achieve larger field imaging. First, a turntable is utilized to support the rotational movement of the radar.Next, a series of high-squint scanning is performed with multiple squint angles. Further, the high squint modulation phase of the echo data is eliminated. Then, a new multi-angle imaging method is performed in the wave number domain to expand the field of view. Simulation and real experiments verify the effectiveness of this method.

Numerical Simulation of Liquid-Solid Coupling in Multi-Angle Fractures in Pressure-Sensitive Reservoirs

This study clarifies the seepage characteristics of complex fractured pressure-sensitive reservoirs,and addresses a common technological problem,that is the alteration of the permeability degree of the reservoir bed(known to be responsible for changes in the direction and velocity of fluid flows between wells).On the basis of a new pressuresensitive equation that considers the fracture directional pressure-sensitive effect,an oil-gas-water three-phase seepage mathematical model is introduced,which can be applied to pressure-sensitive,full-tensor permeability,ultralow-permeability reservoirs with fracture-induced anisotropy.Accordingly,numerical simulations are conducted to explore the seepage laws for ultralow-permeability reservoirs.The results show that element patterns have the highest recovery percentage under a fracture angle of 45°.Accounting for the pressure-sensitive effect produces a decrease in the recovery percentage.Several patterns are considered:inverted five-seven-and nine-spot patterns and a cross-row well pattern.Finally,two strategies are introduced to counteract the rotation of the direction of the principal permeability due to the fracture directional pressure-sensitive effect.

Input Structure Design for Structural Controllability of Complex Networks

This paper addresses the problem of the input design of large-scale complex networks.Two types of network components,redundant inaccessible strongly connected component(RISCC)and intermittent inaccessible strongly connected component(IISCC)are defined,and a subnetwork called a driver network is developed.Based on these,an efficient method is proposed to find the minimum number of controlled nodes to achieve structural complete controllability of a network,in the case that each input can act on multiple state nodes.The range of the number of input nodes to achieve minimal control,and the configuration method(the connection between the input nodes and the controlled nodes)are presented.All possible input solutions can be obtained by this method.Moreover,we give an example and some experiments on real-world networks to illustrate the effectiveness of the method.

Effects of heat input on layer heterogeneity of selective laser melting Ti-6Al-4V components

Due to the layer-by-layer manufacturing characteristics,metallurgical process of selective laser melting(SLM)is inherently dif-ferent in the building direction because of varying conditions,thereby resulting inter-layer heterogeneity.To mitigate such anisotropy,it is of great significance to understand the effects of processing parameters on the property evolution and thus metallurgy of fabrication process.This research proposes one-factor-at-a-time experiment to investigate the influences of laser power and scanning speed on the surface qual-ity,microstructures and mechanical properties of selective laser melted Ti-6Al-4V parts.Surface quality is assessed by roughness around the printings while mechanical properties are evaluated through microhardness and tensile strengths.Phases in microstructure are quantified by XRD to correlate with mechanical properties.Fracture morphology is analyzed to understand the effect of defects and microstructure on mechanical performance.The optimized parameter corresponding to best surface quality and mechanical properties has been found respect-ively in laser power of 190 W and scanning speed of 800 mm/s.After optimization,surface roughness has decreased by 44.47%for upper surface.Yielding strength,tensile strength and elongation rate have improved by 13.17%,43.34%and 64.51%,respectively,with similar hardness and Young’s modulus.In addition,heterogeneity of mechanical properties has great improvement by a range of 31.63%-92.68%.

Generalized-Extended-State-Observer and Equivalent-Input-Disturbance Methods for Active Disturbance Rejection: Deep Observation and Comparison

Active disturbance-rejection methods are effective in estimating and rejecting disturbances in both transient and steady-state responses.This paper presents a deep observation on and a comparison between two of those methods:the generalized extended-state observer(GESO)and the equivalent input disturbance(EID)from assumptions,system configurations,stability conditions,system design,disturbance-rejection performance,and extensibility.A time-domain index is introduced to assess the disturbance-rejection performance.A detailed observation of disturbance-suppression mechanisms reveals the superiority of the EID approach over the GESO method.A comparison between these two methods shows that assumptions on disturbances are more practical and the adjustment of disturbance-rejection performance is easier for the EID approach than for the GESO method.

Observer-Based Path Tracking Controller Design for Autonomous Ground Vehicles With Input Saturation

This paper investigates the problem of path tracking control for autonomous ground vehicles(AGVs),where the input saturation,system nonlinearities and uncertainties are considered.Firstly,the nonlinear path tracking system is formulated as a linear parameter varying(LPV)model where the variation of vehicle velocity is taken into account.Secondly,considering the noise effects on the measurement of lateral offset and heading angle,an observer-based control strategy is proposed,and by analyzing the frequency domain characteristics of the derivative of desired heading angle,a finite frequency H_∞index is proposed to attenuate the effects of the derivative of desired heading angle on path tracking error.Thirdly,sufficient conditions are derived to guarantee robust H_∞performance of the path tracking system,and the calculation of observer and controller gains is converted into solving a convex optimization problem.Finally,simulation examples verify the advantages of the control method proposed in this paper.

Stabilization of fractional bilinear systems with multiple inputs

In this paper,we study in a constructive way the stabilization problem of fractional bilinear systems with multiple inputs.Using the quadratic Lyapunov functions and some additional hypotheses on the unit sphere,we construct stabilizing feedback laws for the considered fractional bilinear system.A numerical example is given to illustrate the efficiency of the obtained result.

SRResNet Performance Enhancement Using Patch Inputs and Partial Convolution-Based Padding

Due to highly underdetermined nature of Single Image Super-Resolution(SISR)problem,deep learning neural networks are required to be more deeper to solve the problem effectively.One of deep neural networks successful in the Super-Resolution(SR)problem is ResNet which can render the capability of deeper networks with the help of skip connections.However,zero padding(ZP)scheme in the network restricts benefits of skip connections in SRResNet and its performance as the ratio of the number of pure input data to that of zero padded data increases.In this paper.we consider the ResNet with Partial Convolution based Padding(PCP)instead of ZP to solve SR problem.Since training of deep neural networks using patch images is advantageous in many aspects such as the number of training image data and network complexities,patch image based SR performance is compared with single full image based one.The experimental results show that patch based SRResNet SR results are better than single full image based ones and the performance of deep SRResNet with PCP is better than the one with ZP.