基于TOF和自适应抗差卡尔曼滤波的UWB室内定位算法

为提高超宽带(UWB)定位系统在室内复杂环境下的定位精度,提出一种基于飞行时间(TOF)和自适应抗差卡尔曼滤波(ARKF)的改进定位算法。针对超低功耗宽带设备在复杂室内环境状态下易受周围干扰而存在标准时间偏差的问题,提出一种改进的TOF算法,同时进行测距标定,拟合数据;对室内存在非视距(NLOS)干扰的情形,提出一种ARKF算法,通过比较残差与3倍信息的方差来判断视距(LOS)与NLOS情形。实验结果显示:该算法可以在静态与动态定位实验中有效提高系统定位精度,降低定位误差,取得较好的定位效果。

Inversion of Seabed Geotechnical Properties in the Arctic Chukchi Deep Sea Basin Based on Time Domain Adaptive Search Matching Algorithm

The chirp sub-bottom profiler,for its high resolution,easy accessibility and cost-effectiveness,has been widely used in acoustic detection.In this paper,the acoustic impedance and grain size compositions were obtained based on the chirp sub-bottom profiler data collected in the Chukchi Plateau area during the 11th Arctic Expedition of China.The time-domain adaptive search matching algorithm was used and validated on our established theoretical model.The misfit between the inversion result and the theoretical model is less than 0.067%.The grain size was calculated according to the empirical relationship between the acoustic impedance and the grain size of the sediment.The average acoustic impedance of sub-seafloor strata is 2.5026×10^(6) kg(s m^(2))^(-1)and the average grain size(θvalue)of the seafloor surface sediment is 7.1498,indicating the predominant occurrence of very fine silt sediment in the study area.Comparison of the inversion results and the laboratory measurements of nearby borehole samples shows that they are in general agreement.

The Research on the Logic and Value of“Two Combinations”

Through the comprehensive analysis of the connotation and logic,inheritance and innovation and the value of social governance,and the dialectical relationship of“two combination”,the inheritance of the idea of Marxism,the inheritance of excellent traditional culture and the governance of contemporary society.

Promote the All-round Development of China's Human Right Cause in the New Era——Summary of the Symposium on “Deeply Studying and Implementing the Spirit of the 20th CPC National Congress and Adhering to the Chinese Path of Human Rights Development”

On November 8, 2022, the symposium on “Deeply Studying and Implementing the Spirit of the 20thCPC National Congress and Adhering to the Chinese Path of Human Rights Development” was held by the China Society for Human Rights Studies in Beijing. Focusing on “the leadership of the CPC and human rights development”, “adapting Marxism to the Chinese context and the needs of our times and human rights theories in contemporary China”, “the Chinese path to modernization and the new form of human rights civilization”, “Chinese human rights solutions and global human rights governance”, “making a better China’s story of advancing human rights and constructing human rights discourse system”, and other topics, the participants reached broad consensus after discussion, and the symposium achieved fruitful results.

Continuous on-line adaptation of the rotor time constant in FOC induction machine system

Rotor time constant is an important parameter for the indirect lleld oraentateO control of mauc- tion motor. Incorrect rotor tittle constant value will cause the flux observer generating a wrong angu- lar orientation of the rotor field. A new approach serves for rotor time constant on-line adaptation by setting the stator current to be zero for a short period. A smooth eorrector is designed to prevent ab- normal detection result from making adaptation. Impact of zero current duration on detection error and rotor speed is analyzed by experiments.

Communication Resource-Efficient Vehicle Platooning Control With Various Spacing Policies

Platooning represents one of the key features that connected automated vehicles may possess as it allows multiple automated vehicles to be maneuvered cooperatively with small headways on roads. However, a critical challenge in accomplishing automated vehicle platoons is to deal with the effects of intermittent and sporadic vehicle-to-vehicle data transmissions caused by limited wireless communication resources. This paper addresses the co-design problem of dynamic event-triggered communication scheduling and cooperative adaptive cruise control for a convoy of automated vehicles with diverse spacing policies. The central aim is to achieve automated vehicle platooning under various gap references with desired platoon stability and spacing performance requirements, while simultaneously improving communication efficiency. Toward this aim, a dynamic event-triggered scheduling mechanism is developed such that the intervehicle data transmissions are scheduled dynamically and efficiently over time. Then, a tractable co-design criterion on the existence of both the admissible event-driven cooperative adaptive cruise control law and the desired scheduling mechanism is derived. Finally, comparative simulation results are presented to substantiate the effectiveness and merits of the obtained results.

The ocean response to climate change guides both adaptation and mitigation efforts

The ocean’s thermal inertia is a major contributor to irreversible ocean changes exceeding time scales that matter to human society.This fact is a challenge to societies as they prepare for the consequences of climate change,especially with respect to the ocean.Here the authors review the requirements for human actions from the ocean’s perspective.In the near term(∼2030),goals such as the United Nations Sustainable Development Goals(SDGs)will be critical.Over longer times(∼2050–2060 and beyond),global carbon neutrality targets may be met as countries continue to work toward reducing emissions.Both adaptation and mitigation plans need to be fully implemented in the interim,and the Global Ocean Observation System should be sustained so that changes can be continuously monitored.In the longer-term(after∼2060),slow emerging changes such as deep ocean warming and sea level rise are committed to continue even in the scenario where net zero emissions are reached.Thus,climate actions have to extend to time scales of hundreds of years.At these time scales,preparation for“high impact,low probability”risks—such as an abrupt showdown of Atlantic Meridional Overturning Circulation,ecosystem change,or irreversible ice sheet loss—should be fully integrated into long-term planning.

Adaptive Stochastic Synchronization of Uncertain Delayed Neural Networks

This paper considers adaptive synchronization of uncertain neural networks with time delays and stochastic perturbation. A general adaptive controller is designed to deal with the difficulties deduced by uncertain parameters and stochastic perturbations, in which the controller is less conservative and optimal since its control gains can be automatically adjusted according to some designed update laws. Based on Lyapunov stability theory and Barbalat lemma, sufficient condition is obtained for synchronization of delayed neural networks by strict mathematical proof. Moreover, the obtained results of this paper are more general than most existing results of certainly neural networks with or without stochastic disturbances. Finally, numerical simulations are presented to substantiate our theoretical results.

ON SOLUTIONS OF BACKWARD STOCHASTIC DIFFERENTIAL EQUATIONS WITH JUMPS,WITH UNBOUNDED STOPPING TIMES AS TERMINAL AND WITH NON-LIPSCHITZ COEFFICIENTS,AND PROBABILISTIC INTERPRETATION OF QUASI-LINEAR ELLIPTIC TYPE INTEGRO-DIFFERENTIAL EQUATIO

The existence and uniqueness of solutions to backward stochastic differential equations with jumps and with unbounded stopping time as terminal under the non_Lipschitz condition are obtained. The convergence of solutions and the continuous dependence of solutions on parameters are also derived. Then the probabilistic interpretation of solutions to some kinds of quasi_linear elliptic type integro_differential equations is obtained.

Adaptive Conditional Hazard Regression Modeling of Multiple Event Times

Recurrent event time data and more general multiple event time data are commonly analyzed using extensions of Cox regression, or proportional hazards regression, as used with single event time data. These methods treat covariates, either time-invariant or time-varying, as having multiplicative effects while general dependence on time is left un-estimated. An adaptive approach is formulated for analyzing multiple event time data. Conditional hazard rates are modeled in terms of dependence on both time and covariates using fractional polynomials restricted so that the conditional hazard rates are positive-valued and so that excess time probability functions (generalizing survival functions for single event times) are decreasing. Maximum likelihood is used to estimate parameters adjusting for right censored event times. Likelihood cross-validation (LCV) scores are used to compare models. Adaptive searches through alternate conditional hazard rate models are controlled by LCV scores combined with tolerance parameters. These searches identify effective models for the underlying multiple event time data. Conditional hazard regression is demonstrated using data on times between tumor recurrence for bladder cancer patients. Analyses of theory-based models for these data using extensions of Cox regression provide conflicting results on effects to treatment group and the initial number of tumors. On the other hand, fractional polynomial analyses of these theory-based models provide consistent results identifying significant effects to treatment group and initial number of tumors using both model-based and robust empirical tests. Adaptive analyses further identify distinct moderation by group of the effect of tumor order and an additive effect to group after controlling for nonlinear effects to initial number of tumors and tumor order. Results of example analyses indicate that adaptive conditional hazard rate modeling can generate useful insights into multiple event time data.

Adaptive Conditional Hazard Regression Modeling of Multiple Event Times

Recurrent event time data and more general multiple event time data are commonly analyzed using extensions of Cox regression, or proportional hazards regression, as used with single event time data. These methods treat covariates, either time-invariant or time-varying, as having multiplicative effects while general dependence on time is left un-estimated. An adaptive approach is formulated for analyzing multiple event time data. Conditional hazard rates are modeled in terms of dependence on both time and covariates using fractional polynomials restricted so that the conditional hazard rates are positive-valued and so that excess time probability functions (generalizing survival functions for single event times) are decreasing. Maximum likelihood is used to estimate parameters adjusting for right censored event times. Likelihood cross-validation (LCV) scores are used to compare models. Adaptive searches through alternate conditional hazard rate models are controlled by LCV scores combined with tolerance parameters. These searches identify effective models for the underlying multiple event time data. Conditional hazard regression is demonstrated using data on times between tumor recurrence for bladder cancer patients. Analyses of theory-based models for these data using extensions of Cox regression provide conflicting results on effects to treatment group and the initial number of tumors. On the other hand, fractional polynomial analyses of these theory-based models provide consistent results identifying significant effects to treatment group and initial number of tumors using both model-based and robust empirical tests. Adaptive analyses further identify distinct moderation by group of the effect of tumor order and an additive effect to group after controlling for nonlinear effects to initial number of tumors and tumor order. Results of example analyses indicate that adaptive conditional hazard rate modeling can generate useful insights into multiple event time data.

Adaptive Control of MIMO Mechanical Systems with Unknown Actuator Nonlinearities Based on the Nussbaum Gain Approach

This paper investigates MIMO mechanical systems with unknown actuator nonlinearities. A novel Nussbaum analysis tool for MIMO systems is established such that unknown time-varying control coefficients are tackled. In contrast to existing literatures on continuous-time systems, the newly-developed Nussbaum tool focuses on extending the traditional Nussbaum result from one dimensional case to the multiple one. Specifically, not only the multiple unknown input coefficients are extended to the time-varying, but also the limitation of the prior knowledge of coefficients' upper and lower bounds is removed. Furthermore, an adaptive robust controller associated with the proposed tool is presented. The asymptotic tracking of MIMO mechanical systems is guaranteed with the help of the Lyapunov Theorem. Finally, a simulation example is provided to examine the validity of the proposed scheme. © 2014 Chinese Association of Automation.

Noise-Tolerant ZNN-Based Data-Driven Iterative Learning Control for Discrete Nonaffine Nonlinear MIMO Repetitive Systems

Aiming at the tracking problem of a class of discrete nonaffine nonlinear multi-input multi-output(MIMO) repetitive systems subjected to separable and nonseparable disturbances, a novel data-driven iterative learning control(ILC) scheme based on the zeroing neural networks(ZNNs) is proposed. First, the equivalent dynamic linearization data model is obtained by means of dynamic linearization technology, which exists theoretically in the iteration domain. Then, the iterative extended state observer(IESO) is developed to estimate the disturbance and the coupling between systems, and the decoupled dynamic linearization model is obtained for the purpose of controller synthesis. To solve the zero-seeking tracking problem with inherent tolerance of noise,an ILC based on noise-tolerant modified ZNN is proposed. The strict assumptions imposed on the initialization conditions of each iteration in the existing ILC methods can be absolutely removed with our method. In addition, theoretical analysis indicates that the modified ZNN can converge to the exact solution of the zero-seeking tracking problem. Finally, a generalized example and an application-oriented example are presented to verify the effectiveness and superiority of the proposed process.

Adaptive predictor-based control for a helicopter system with input delays:Design and experiments

In this paper,we consider a 2-degrees-of-freedom(DOF)helicopter system subject to long input delays and uncertain system parameters.To address the challenges including unknown system parameters and input delays in control design,we develop an adaptive predictor-feedback control law to achieve trajectory tracking.Stability of the closed-loop system is further established,where the tracking errors are shown to converge towards zero.Through simulation and experiments on the helicopter system,we illustrate that tracking of a desired trajectory is achieved with the proposed control scheme.

Vascular Plants of the Maritime Antarctic: Origin and Adaptation

The question of why only two species of vascular plant have colonized Antarctica has not been fully answered. This review is based on a series of parallel analyses of distribution, ecology, and adaptation on the morphological, cellular, and molecular genetic levels, and addresses the causes of the exclusive adaptation of Deschampsia antarctica Desv. (Poaceae) and Colobanthus quitensis (Kunth) Bartl. The authors conclude that the unique distribution of these species, including the Antarctic Peninsula, is not related to the presence of any specific mechanisms of adaptation to the ex-treme environment, but rather is a result of a gradual adaptation of these taxa to the extreme conditions during the de-velopment of glacial events and wide distribution and a substantial seed bank which could ensure mosaic survival in some ice-free areas, as well as survival through several years of snow and ice cover. Glaciological, molecular, popula-tion and reproduction biology studies are still necessary to deepen our understanding of the timing of the colonization of the region by vascular plants. However, keeping in mind that molecular methods alone are unlikely to give exhaus-tive evidence, application of other adequate methods in the context of the history of Pleistocenic glaciation in the region is also necessary to answer the question.

New type of adaptive control for a class of distributed time-delay systems with adaptation regard to delay parameter

The problem on stabilization for the system with distributed delays is researched. The distributed time-delay under consideration is assumed to be a constant time-delay, but not known exactly. A design method is proposed for a memory proportional and integral （PI） feedback controller with adaptation to distributed time-delay. The feedback controller with memory simultaneously contains the current state and the past distributed information of the addressed systems. The design for adaptation law to distributed delay is very concise. The controller can be derived by solving a set of linear matrix inequalities （LMIs）. Two numerical examples are given to illustrate the effectiveness of the design method.

Cooperative Adaptive Cruise Control Platoon Fleet Formation Model Considering Efficiency and Stability

In the existing formation model,vehicles in the same lane or adjacent lane are regarded as the structure,and the driving behavior of vehicles is studied from the perspectives of safety,speed consistency,and stability,and the speed control model is proposed from the perspective of vehicles themselves,to obtain a stable fleet with the same distance and speed.However,in this process,the initial condition of the vehicle,the traffic flow environment,and the efficiency of the fleet formation are less considered.Therefore,based on summarizing the existing fleet building model,this paper puts forward the rapid construction model and algorithm of a cooperative adaptive cruise control platoon fleet.One of the important goals of forming a team is to enter the team with the smoothest trajectory in the shortest time.Therefore,this chapter studies the trajectory optimization of the vehicle formation process from the perspective of vehicle dynamics.

The Role of a Novel Discrete-Time MRAC Based Motion Cueing on Loss of Control at a Hexapod Driving Simulator

The objective of this paper is to present the advantages of Model reference adaptive control (MRAC) motion cueing algorithm against the classical motion cueing algorithm in terms of biomechanical reactions of the participants during the critical maneuvers like chicane in driving simulator real-time. This study proposes a method and an experimental validation to analyze the vestibular and neuromuscular dynamics responses of the drivers with respect to the type of the control used at the hexapod driving simulator. For each situation, the EMG (electromyography) data were registered from arm muscles of the drivers (flexor carpi radialis, brachioradialis). In addition, the roll velocity perception thresholds (RVT) and roll velocities (RV) were computed from the real-time vestibular level measurements from the drivers via a motion-tracking sensor. In order to process the data of the EMG and RVT, Pearson’s correlation and a two-way ANOVA with a significance level of 0.05 were assigned. Moreover, the relationships of arm muscle power and roll velocity with vehicle CG (center of gravity) lateral displacement were analyzed in order to assess the agility/alertness level of the drivers as well as the vehicle loss of control characteristics with a confidence interval of 95%. The results showed that the MRAC algorithm avoided the loss of adhesion, loss of control (LOA, LOC) more reasonably compared to the classical motion cueing algorithm. According to our findings, the LOA avoidance decreased the neuromuscular-visual cues level conflict with MRAC algorithm. It also revealed that the neuromuscular-vehicle dynamics conflict has influence on visuo-vestibular conflict;however, the visuo-vestibular cue conflict does not influence the neuromuscular-vehicle dynamics interactions.

自适应解卷积方法抑制管道TOFD周向扫查盲区

利用超声衍射时差法(TOFD)沿管道外表面实施周向扫查时,受管道曲率和直达纵波脉冲宽度共同影响,在近表面区域形成分层盲区。本文采用自适应解卷积方法,选取与混叠信号主频接近的子带直达纵波信号作为参考信号,进行解卷积与自回归谱外推处理,拓宽有效频带范围,实现时域信号脉冲压缩,并结合周向扫查图像中端点衍射波确定缺陷深度。实验结果表明,对于外壁半径100.0 mm、壁厚30.0 mm,以及外壁半径148.0 mm、壁厚27.0 mm的碳钢管道,在中心频率5 MHz、探头中心距87 mm的检测条件下,自适应解卷积方法能够将管道近表面分层盲区范围减少约60%,且到直达纵波声线距离不小于4.0 mm缺陷的深度定量误差不超过10.6%。同常规频谱分析方法和自回归谱外推方法相比,自适应解卷积方法具有更优的盲区抑制效果,且能够准确定量前者难以检测的缺陷,测量误差不超过5.8%。

Oryza CLIMtools:A genome–environment association resource reveals adaptive roles for heterotrimeric G proteins in the regulation of rice agronomic traits

Modern crop varieties display a degree of mismatch between their current distributions and the suitability of the local climate for their productivity.To address this issue,we present Oryza CLIMtools(https://gramene.org/CLIMtools/oryza_v1.0/),thefirst resource for pan-genome prediction of climate-associated genetic variants in a crop species.Oryza CLIMtools consists of interactive web-based databases that enable the user to(1)explore the local environments of traditional rice varieties(landraces)in South-East Asia and(2)investigate the environment by genome associations for 658 Indica and 283 Japonica rice landrace accessions collected from georeferenced local environments and included in the 3K Rice Ge-nomes Project.We demonstrate the value of these resources by identifying an interplay betweenflowering time and temperature in the local environment that is facilitated by adaptive natural variation in OsHD2 and disrupted by a natural variant in OsSOC1.Prior quantitative trait locus analysis has suggested the impor-tance of heterotrimeric G proteins in the control of agronomic traits.Accordingly,we analyzed the climate associations of natural variants in the different heterotrimeric G protein subunits.We identified a coordi-nated role of G proteins in adaptation to the prevailing potential evapotranspiration gradient and revealed their regulation of key agronomic traits,including plant height and seed and panicle length.We conclude by highlighting the prospect of targeting heterotrimeric G proteins to produce climate-resilient crops.