Robust design of sliding mode control for airship trajectory tracking with uncertainty and disturbance estimation

The robotic airship can provide a promising aerostatic platform for many potential applications.These applications require a precise autonomous trajectory tracking control for airship.Airship has a nonlinear and uncertain dynamics.It is prone to wind disturbances that offer a challenge for a trajectory tracking control design.This paper addresses the airship trajectory tracking problem having time varying reference path.A lumped parameter estimation approach under model uncertainties and wind disturbances is opted against distributed parameters.It uses extended Kalman filter(EKF)for uncertainty and disturbance estimation.The estimated parameters are used by sliding mode controller(SMC)for ultimate control of airship trajectory tracking.This comprehensive algorithm,EKF based SMC(ESMC),is used as a robust solution to track airship trajectory.The proposed estimator provides the estimates of wind disturbances as well as model uncertainty due to the mass matrix variations and aerodynamic model inaccuracies.The stability and convergence of the proposed method are investigated using the Lyapunov stability analysis.The simulation results show that the proposed method efficiently tracks the desired trajectory.The method solves the stability,convergence,and chattering problem of SMC under model uncertainties and wind disturbances.

Estimating Aboveground Fresh Biomass of Different Cotton Canopy Types with Homogeneity Models Based on Hyper Spectrum Parameters

AGB （aboveground fresh biomass） is one of the most important parameters of the crop condition monitored with remote sensing. Hyper spectrum remote sensing with the fine spectrum information becomes the efficient method estimating the vegetation AGB. The research was conducted in Xinjiang, the largest cotton planting region of China. The paper analyzed the correlation between the cotton AGB and reflective spectrum and the first derivative spectrum, and the variation coefficient of the waveband reflectance. According to the analysis above, all of 23 parameters, including the hyper spectrum reflectance, the first derivative spectrum parameters and normalization vegetation indexes, were established. And then the estimation models on cotton AGB of relaxing and compact canopy type were established and tested respectively. The tested results showed that Fgo1, [901,502], [901,629], [901,672] among the reflective spectral parameters and D525, D956, D1019, D1751 among the first derivative spectral parameters had the homogenous effect on different cotton canopy types, and the determination coefficients of the models above all arrive at the significant level of 0.99 confidence interval. At last, the tested results of the homogeneity models for different canopy types indicated the parameters of [901, 502], [901,629], [901,672] have more satisfying veracity than others, and the relative errors are as low as 17.0, 16.3 and 16.7% correspondingly; in contrast, the estimation veracity of the first derivative spectrum parameters of single waveband is low.

Airship aerodynamic model estimation using unscented Kalman filter

An airship model is made-up of aerostatic,aerodynamic,dynamic,and propulsive forces and torques.Besides others,the computation of aerodynamic forces and torques is difficult.Usually,wind tunnel experimentation and potential flow theory are used for their calculations.However,the limitations of these methods pose difficulties in their accurate calculation.In this work,an online estimation scheme based on unscented Kalman filter(UKF)is proposed for their calculation.The proposed method introduces six auxiliary states for the complete aerodynamic model.UKF uses an extended model and provides an estimate of a complete state vector along with auxiliary states.The proposed method uses the minimum auxiliary state variables for the approximation of the complete aerodynamic model that makes it computationally less intensive.UKF estimation performance is evaluated by developing a nonlinear simulation environment for University of Engineering and Technology,Taxila(UETT)airship.Estimator performance is validated by performing the error analysis based on estimation error and 2-σ uncertainty bound.For the same problem,the extended Kalman filter(EKF)is also implemented and its results are compared with UKF.The simulation results show that UKF successfully estimates the forces and torques due to the aerodynamic model with small estimation error and the comparative analysis with EKF shows that UKF improves the estimation results and also it is more suitable for the under-consideration problem.

Delineation of an Urban Community Life Circle Based on a Machine-Learning Estimation of Spatiotemporal Behavioral Demand

Delineating life circles is an essential prerequisite for urban community life circle planning. Recent studies combined the environmental contexts with residents’ global positioning system(GPS) data to delineate the life circles. This method, however, is constrained by GPS data, and it can only be applied in the GPS surveyed communities. To address this limitation, this study developed a generalizable delineation method without the constraint of behavioral data. According to previous research, the community life circle consists of the walking-accessible range and internal structure. The core task to develop the generalizable method was to estimate the spatiotemporal behavioral demand for each plot of land to acquire the internal structure of the life circle, as the range can be delineated primarily based on environmental data. Therefore, behavioral demand estimation models were established through logistic regression and machine learning techniques, including decision trees and ensemble learning. The model with the lowest error rate was chosen as the final estimation model for each type of land. Finally, we used a community without GPS data as an example to demonstrate the effectiveness of the estimation models and delineation method. This article extends the existing literature by introducing spatiotemporal behavioral demand estimation models, which learn the relationships between environmental contexts, population composition and the existing delineated results based on GPS data to delineate the internal structure of the community life circle without employing behavioral data. Furthermore, the proposed method and delineation results also contributes to facilities adjustments and location selections in life circle planning, people-oriented transformation in urban planning, and activity space estimation of the population in evaluating and improving the urban policies.

Path Classification and Estimation Model Based Prognosis of Pneumatic Cylinder Lifetime

Prognosis is a key technology to improve reliability,safety and maintainability of products,a lot of researchers have been devoted to this technology.But to improve the predict accuracy of remaining life of products has been difficult.To predict the lifetime specification of pneumatic cylinders with high reliability and long lifetime and small specimen,this paper put forward the prognosis algorithm based on the path classification and estimation（PACE） model.PACE model is based entirely on failure data instead of failure threshold.Pneumatic cylinders normally characterize with failure mechanism wear and tear.Since the minimum working pressure increases with the number of working cycles,the minimum working pressure is chosen as degradation signal.PACE model is fundamentally composed of two operations：path classification and remaining useful life（RUL） estimation.Path classification is to classify a current degradation path as belonging to one or more of previously collected exemplary degradation paths.RUL estimation is to use the resulting memberships to estimate the remaining useful life.In order for verification and validation of PACE prognostic method,six pneumatic cylinders are tested.The test data is analyzed by PACE prognostics.It is found that the PACE based prognosis method has higher prediction accuracy and smaller variance and PACE model is significantly outperform population based prognostics especially for small specimen condition.PACE model based method solved the problem of prediction accuracy for small specimen pneumatic cylinders＇ prognosis.

An estimation method of soil wind erosion in Inner Mongolia of China based on geographic information system and remote sensing

Studies of wind erosion based on Geographic Information System（GIS） and Remote Sensing（RS） have not attracted sufficient attention because they are limited by natural and scientific factors.Few studies have been conducted to estimate the intensity of large-scale wind erosion in Inner Mongolia,China.In the present study,a new model based on five factors including the number of snow cover days,soil erodibility,aridity,vegetation index and wind field intensity was developed to quantitatively estimate the amount of wind erosion.The results showed that wind erosion widely existed in Inner Mongolia.It covers an area of approximately 90×104 km2,accounting for 80% of the study region.During 1985–2011,wind erosion has aggravated over the entire region of Inner Mongolia,which was indicated by enlarged zones of erosion at severe,intensive and mild levels.In Inner Mongolia,a distinct spatial differentiation of wind erosion intensity was noted.The distribution of change intensity exhibited a downward trend that decreased from severe increase in the southwest to mild decrease in the northeast of the region.Zones occupied by barren land or sparse vegetation showed the most severe erosion,followed by land occupied by open shrubbery.Grasslands would have the most dramatic potential for changes in the future because these areas showed the largest fluctuation range of change intensity.In addition,a significantly negative relation was noted between change intensity and land slope.The relation between soil type and change intensity differed with the content of Ca CO3 and the surface composition of sandy,loamy and clayey soils with particle sizes of 0–1 cm.The results have certain significance for understanding the mechanism and change process of wind erosion that has occurred during the study period.Therefore,the present study can provide a scientific basis for the prevention and treatment of wind erosion in Inner Mongolia.

Estimation Method of State-of-Charge For Lithium-ion Battery Used in Hybrid Electric Vehicles Based on Variable Structure Extended Kalman Filter

Since the main power source of hybrid electric vehicle（HEV） is supplied by the power battery,the predicted performance of power battery,especially the state-of-charge（SOC） estimation has attracted great attention in the area of HEV.However,the value of SOC estimation could not be greatly precise so that the running performance of HEV is greatly affected.A variable structure extended kalman filter（VSEKF）-based estimation method,which could be used to analyze the SOC of lithium-ion battery in the fixed driving condition,is presented.First,the general lower-order battery equivalent circuit model（GLM）,which includes column accumulation model,open circuit voltage model and the SOC output model,is established,and the off-line and online model parameters are calculated with hybrid pulse power characteristics（HPPC） test data.Next,a VSEKF estimation method of SOC,which integrates the ampere-hour（Ah） integration method and the extended Kalman filter（EKF） method,is executed with different adaptive weighting coefficients,which are determined according to the different values of open-circuit voltage obtained in the corresponding charging or discharging processes.According to the experimental analysis,the faster convergence speed and more accurate simulating results could be obtained using the VSEKF method in the running performance of HEV.The error rate of SOC estimation with the VSEKF method is focused in the range of 5% to 10% comparing with the range of 20% to 30% using the EKF method and the Ah integration method.In Summary,the accuracy of the SOC estimation in the lithium-ion battery cell and the pack of lithium-ion battery system,which is obtained utilizing the VSEKF method has been significantly improved comparing with the Ah integration method and the EKF method.The VSEKF method utilizing in the SOC estimation in the lithium-ion pack of HEV can be widely used in practical driving conditions.

Cooperative interception with fast multiple model adaptive estimation

For the case that two pursuers intercept an evasive target,the cooperative strategies and state estimation methods taken by pursuers can seriously affect the guidance accuracy for the target,which performs a bang For the case that two pursuers intercept an evasive target,the cooperative strategies and state estimation methods taken by pursuers can seriously affect the guidance accuracy for the target,which performs a bang-bang evasive maneuver with a random switching time.Combined Fast multiple model adaptive estimation(Fast MMAE)algorithm,the cooperative guidance law takes detection configuration affecting the accuracy of interception into consideration.Introduced the detection error model related to the line-of-sight(LOS)separation angle of two interceptors,an optimal cooperative guidance law solving the optimization problem is designed to modulate the LOS separation angle to reduce the estimation error and improve the interception performance.Due to the uncertainty of the target bang-bang maneuver switching time and the effective fitting of its multi-modal motion,Fast MMAE is introduced to identify its maneuver switching time and estimate the acceleration of the target to track and intercept the target accurately.The designed cooperative optimal guidance law with Fast MMAE has better estimation ability and interception performance than the traditional guidance law and estimation method via Monte Carlo simulation.

Research on the effect estimation of seismic safety evaluation

Seismic safety evaluation is a basic work for determining the seismic resistance requirements of major construc-tion projects. The effect, especially the economic effect of the seismic safety evaluation has been generally con-cerned. The paper gives a model for estimating the effect of seismic safety evaluation and calculates roughly the economic effect of seismic safety evaluation with some examples.

Crosstalk Model and Estimation Formula for VLSI Interconnect Wires

We develop an interconnect crosstalk estimation model on the assumption of linearity for CMOS device. First, we analyze the terminal response of RC model on the worst condition from theS field to the time domain. The exact 3 order coefficients inS field are obtained due to the interconnect tree model. Based on this, a crosstalk peak estimation formula is presented. Unlike other crosstalk equations in the literature, this formula is only used coupled capacitance and grand capacitance as parameter. Experimental results show that, compared with the SPICE results, the estimation formulae are simple and accurate. So the model is expected to be used in such fields as layout-driven logic and high level synthesis, performance-driven floorplanning and interconnect planning.

Ambiguity Resolution in Direction of Arrival Estimation with Linear Antenna Arrays Using Differential Geometry

Linear antenna arrays(LAs)can be used to accurately predict the direction of arrival(DOAs)of various targets of interest in a given area.However,under certain conditions,LA suffers from the problem of ambiguities among the angles of targets,which may result inmisinterpretation of such targets.In order to cope up with such ambiguities,various techniques have been proposed.Unfortunately,none of them fully resolved such a problem because of rank deficiency and high computational cost.We aimed to resolve such a problem by proposing an algorithm using differential geometry.The proposed algorithm uses a specially designed doublet antenna array,which is made up of two individual linear arrays.Two angle observation models,ambiguous observation model(AOM)and estimated observation model(EOM),are derived for each individual array.The ambiguous set of angles is contained in the AOM,which is obtained from the corresponding array elements using differential geometry.The EOM for each array,on the other hand,contains estimated angles of all sources impinging signals on each array,as calculated by a direction-finding algorithm such as the genetic algorithm.The algorithm then contrasts the EOM of each array with its AOM,selecting the output of that array whose EOM has the minimum correlation with its corresponding AOM.In comparison to existing techniques,the proposed algorithm improves estimation accuracy and has greater precision in antenna aperture selection,resulting in improved resolution capabilities and the potential to be used more widely in practical scenarios.The simulation results using MATLAB authenticates the effectiveness of the proposed algorithm.

PARAMETER ESTIMATION OF MULTI-CONSTITUENT WATER QUALITY MODEL FOR THE LIANGXI RIVER BY MARQUARDT METHOD

A multi-constituent water quality model is presented,Which relates carbonaceous biochemical oxygen demand (CBOD),amonia (NH3-N), nitrite(NO2-N), nitrate(NO3-N) and dissolvedoxygen(DO). The parameters are solved by Marquardt Method (i. e.,Dampled Least Square Method) while initial values inoptimization are produced by Monte-Carlo Method. The Potential ofthe method as a parameter estimation aid is demonstrated for theapplication to the Liangyi Rver, JiangSu Province of China and by aspecial comparison with Gauss Method.

ON THE ESTIMATION OF SURFACE ALBEDO USING SATELLITE DATE

The method to determine the surface albedo using satellite date hasbeen developed and discussed. The relatons betwam the planetary albedo andsurfoce albedo in clear skies are derived with the help of the radiative transfermodelling. To improve the accuracy of the denved surfoce albedo, theparameter X0, i.e., the ratio of the reflected to the total extinction radiation isintroduced into this model. The influences of the model paramenters on thesurfoce albedo have been analyzed. It is found that the error in the derivedsurfoce albedo due to the paramaters together is less than that caused by oulyone parameter because of the complementarity of the parameters. Test resultsin 22 stations over China have been given using the Geostationary SatelliteGMS. The results are generally agreeable except for the case of snow/ice cover.

Letter to the Editor Re “Fractional Modeling and SOC Estimation of Lithium-ion Battery”

A Recent paper by Ma et al.,claims to estimate the state of charge of Lithium-ion batteries with a fractionalorder impedance model including a Warburg and a constant phase element(CPE)with a maximum error of 0.5%[1].The proposed equivalent circuit model from[1]is reproduced in Fig.1.

A-posteriori error estimation for second order mechanical systems

One important issue for the simulation of flexible multibody systems is the reduction of the flexible bodies de- grees of freedom. As far as safety questions are concerned knowledge about the error introduced by the reduction of the flexible degrees of freedom is helpful and very important. In this work, an a-posteriori error estimator for linear first order systems is extended for error estimation of me- chanical second order systems. Due to the special second order structure of mechanical systems, an improvement of the a-posteriori error estimator is achieved. A major advan- tage of the a-posteriori error estimator is that the estimator is independent of the used reduction technique. Therefore, it can be used for moment-matching based, Gramian matrices based or modal based model reduction techniques. The capability of the proposed technique is demon- strated by the a-posteriori error estimation of a mechanical system, and a sensitivity analysis of the parameters involved in the error estimation process is conducted.

Global parameter estimation of the Cochlodinium polykrikoides model using bioassay data

Cochlodinium polykrikoides is a notoriously harmful algal species that inflicts severe damage on the aquacultures of the coastal seas of Korea and Japan. Information on their expected movement tracks and boundaries of influence is very useful and important for the effective establishment of a reduction plan. In general, the information is supported by a red-tide（a.k.a algal bloom） model. The performance of the model is highly dependent on the accuracy of parameters, which are the coefficients of functions approximating the biological growth and loss patterns of the C. polykrikoides. These parameters have been estimated using the bioassay data composed of growth-limiting factor and net growth rate value pairs. In the case of the C. polykrikoides, the parameters are different from each other in accordance with the used data because the bioassay data are sufficient compared to the other algal species. The parameters estimated by one specific dataset can be viewed as locally-optimized because they are adjusted only by that dataset. In cases where the other one data set is used, the estimation error might be considerable. In this study, the parameters are estimated by all available data sets without the use of only one specific data set and thus can be considered globally optimized. The cost function for the optimization is defined as the integrated mean squared estimation error, i.e., the difference between the values of the experimental and estimated rates. Based on quantitative error analysis, the root-mean squared errors of the global parameters show smaller values, approximately 25%–50%, than the values of the local parameters. In addition, bias is removed completely in the case of the globally estimated parameters. The parameter sets can be used as the reference default values of a red-tide model because they are optimal and representative. However, additional tuning of the parameters using the in-situ monitoring data is highly required.As opposed to the bioassay data, it is necessary because the bioassay data have limitations in terms of the in-situ coastal conditions.

落叶果树需冷量及其估算模型研究进展

落叶果树的需冷量得到满足,才能顺利完成自然休眠,进行下一个生长发育循环(尤其是正常开花结果),否则其他环境条件再适宜,果树也不萌芽开花,即使萌芽也不整齐,生长结果不良,达不到促成栽培的目的[1].因此,对落叶果树需冷量及其估算的研究至关重要,成为落叶果树设施栽培成败的关键.本文仅就需冷量估算模型进行介绍,以期为设施栽培和更完善的需冷量估算提供理论依据.……

Hot spot temperature prediction and operating parameter estimation of racks in data center using machine learning algorithms based on simulation data

In this paper,models to predict hot spot temperature and to estimate cooling air’s working parameters of racks in data centers were established using machine learning algorithms based on simulation data.First,simulation models of typical racks were established in computational fluid dynamics(CFD).The model was validated with field test results and results in literature,error of which was less than 3%.Then,the CFD model was used to simulate thermal environments of a typical rack considering different factors,such as servers’power,which is from 3.3 kW to 20.1 kW,cooling air’s inlet velocity,which is from 1.0 m/s to 3.0 m/s,and cooling air’s inlet temperature,which is from 16℃ to 26℃ The highest temperature in the rack,also called hot spot temperature,was selected for each case.Next,a prediction model of hot spot temperature was built using machine learning algorithms,with servers’power,cooling air’s inlet velocity and cooling air’s inlet temperature as inputs,and the hot spot temperatures as outputs.Finally,based on the prediction model,an operating parameters estimation model was established to recommend cooling air’s inlet temperatures and velocities,which can not only keep the hot spot temperature at the safety value,but are also energy saving.

Evaluating the grassland net primary productivity of southern China from 2000 to 2011 using a new climate productivity model

Grassland is the important component of the terrestrial ecosystems. Estimating net primary productivity （NPP） of grassland ecosystem has been a central focus in global climate change researches. To simulate the grassland NPP in southern China, we built a new climate productivity model, and validated the model with the measured data from different years in the past. The results showed that there was a logarithmic correlation between the grassland NPP and the mean annual temperature, and there was a linear positive correlation between the grassland NPP and the annual precipitation in southern China. Al these results reached a very signiifcant level （P〈0.01）. There was a good correlation between the simulated and the measured NPP, withR2 of 0.8027, reaching the very signiifcant level. Meanwhile, both root mean square errors （RMSE） and relative root-mean-square errors （RRMSE） stayed at a relatively low level, showing that the simulation results of the model were reliable. The NPP values in the study area had a decreasing trend from east to west and from south to north, and the mean NPP was 471.62 g C m？2 from 2000 to 2011. Additionaly, there was a rising trend year by year for the mean annual NPP of southern grassland and the tilt rate of the mean annual NPP was 3.49 g C m？2 yr？1 in recent 12 years. The above results provided a new method for grassland NPP estimation in southern China.