Optimal fuzzy PID controller with adjustable factors based on flexible polyhedron search algorithm

A new kind of optimal fuzzy PID controller is proposed, which contains two parts. One is an on line fuzzy inference system, and the other is a conventional PID controller. In the fuzzy inference system, three adjustable factors x p, x i , and x d are introduced. Their functions are to further modify and optimize the result of the fuzzy inference so as to make the controller have the optimal control effect on a given object. The optimal values of these adjustable factors are determined based on the ITAE criterion and the Nelder and Mead′s flexible polyhedron search algorithm. This optimal fuzzy PID controller has been used to control the executive motor of the intelligent artificial leg designed by the authors. The result of computer simulation indicates that this controller is very effective and can be widely used to control different kinds of objects and processes.

Verification of Depth Adjustment Factor in Eurocode 5 for Tropical Hardwood Timbers

The depth adjustment factor for bending strength stated in Eurocode 5(EC5)is only applicable to timbers having a characteristic density below 700 kg/m^(3).However,most Malaysian timbers are hardwood,some with a characteristic density reaching above 700 kg/m^(3).Therefore,the objective of this study was to examine whether the depth adjustment factor stipulated in EC5 is valid for Malaysian hardwood timbers.Six timber species were selected for this study,namely Kapur(Dryobalanops C.F.Gaertn.),Kempas(Koompassia Maingay ex Benth.),Keruing(Dipterocarpus C.F.Gaertn.),Light red meranti(Shorea Roxb.ex C.F.Gaertn.),Geronggang(Cratoxylum Blume)and Balau(Shorea Roxb.ex C.F.Gaertn.).The determination of bending strength and characteristic density was conducted according to BS EN 408:2010 and BS EN 384:2016,respectively.A graph for mean bending strength vs.(150/h)was plotted for each timber species.The power function was selected to analyze the relationship between the two variables.The power of the regression equations varied depending on the characteristic density of the timber species.For species with a characteristic density below 700 kg/m^(3),such as Kapur,Keruing,and Light red meranti,the power was between 0.16 to 0.17.In contrast,for species having a characteristic density above 700 kg/m^(3),namely Kempas and Balau,the power was higher at 0.23 and 0.24,respectively.Geronggang was an exception to this pattern.These values are close to the depth adjustment factor given in EC5,which is 0.2.Based on the results,it can be suggested that the adjustment factor of 0.2 is also applicable to Malaysian hardwood timbers with a characteristic density above 700 kg/m^(3).

Impacts of automated passenger cars on the capacity of a freeway basic section: applicability in the determination of vehicle adjustment factors in mixed traffic

The highway capacity manual(HCM)provides a formula to calculate the heavy vehicle adjustment factor(fHV)as a function of passenger car equivalent factors for the heavy vehicle(ET).However,a significant drawback is that the methodology was established solely based on human-driven passenger cars(HDPC)and human-driven heavy vehicles(HDHV).Due to automated passenger cars(APCs),a new adjustment factor(fAV)might be expected.This study simulated traffic flows at different percentages of HDHVs and APCs to investigate the impacts of HDHVs and APCs on freeway capacity by analyzing their influence on fHV and fAV values.The simulation determined observed adjustment factors at different percentages of HDHVs and APCs(fobserved).The HCM formula was used to calculate(fHCM).Modifications to the HCM formula are proposed,and vehicle adjustment factors due to HDHVs and APCs were calculated(fproposed).Results showed that,in the presence of APCs,while fobserved and fHCM were statistically significantly different,fobserved and fproposed were statistically equal.Hence,this study recommends using the proposed formula when determining vehicle adjustment factors(fproposed)due to HDHVs and APCs in the traffic stream.

What Drives China’s Transformational Growth:Technology,Efficiency or Factor Cost?

With rising costs of capital, labor and energy, cost efficiency and cost management have become important questions confronting the next stage of China＇s economic growth. By building a parametric cost frontier model using panel data, this paper investigates the drivers of economic growth transformation from a cost perspective. According to our research, among various effects triggering corporate cost variations and in addition to the expansion of production scale, the largest effect is from technological progress, followed by the effect of factor price adjustment and the effect of efficiency gains. Within the decomposition of factor price adjustment effect, the energy factor effect is the most significant. Furthermore, energy price fluctuations are likely to become major factors restricting saving-based growth. Further study reveals that both the ownership reform and opening up of SOEs are favorable to reducing the costs generated by inefficiency. This paper provides empirical evidence for the driving mechanism of saving-based growth transformation as well as empirical evidence to support to the further deepening of property rights and market-oriented reforms.

Emerging frontier technologies for food safety analysis and risk assessment

Access to security and safe food is a basic human necessity and essential for a sustainable world. To perform hi-end rood safety analysis and risk assessment with state of the art technologies is of utmost importance thereof. With applications as exemplified by microfiuidic immunoassay, aptasensor, direct analysis in real time, high resolution mass spectrometry, benchmark dose and chemical specific adjustment factor, this review presents frontier food safety analysis and risk assessment technologies, from which both food quality and public health will benefit undoubtedly in a foreseeable future.

Wind-induced response analysis of conical membrane structures

Conical membrane structures are a typical form of tensile membrane structures. In the past, most studies focused on the static performance, but few on dynamic performance. In this paper, systematic parameter analysis of wind-induced response of conical membrane structures has been performed with nonlinear random simulation method in a time domain, by considering some parameters, such as span, rise-span ratio, prestress of membrane, and characteristic of the approaching wind flow. Moreover, formulas of the dynamic coefficient and nonlinear adjustment factor are advised, which can be conveniently used in wind-resistant design of conical membrane structures.

Adaptive Statistical Spatial Downscaling of Precipitation Supported by High-Resolution Atmospheric Simulation Data for Mountainous Areas of Nepal

In complex terrain regions, it is very challenging to obtain high accuracy and resolution precipitation data that are required in land hydrological studies. In this study, an adaptive precipitation downscaling method is proposed based on the statistical downscaling model MicroMet. A key input parameter in the MicroMet is the precipitation adjustment factor(PAF) that shows the elevation dependence of precipitation. Its value is estimated conventionally based on station observations and suffers sparse stations in high altitudes. This study proposes to estimate the PAF value and its spatial variability with precipitation data from high-resolution atmospheric simulations and tests the idea in Nepal of South Himalayas, where rainfall stations are relatively dense. The result shows that MicroMet performs the best with the PAF value estimated from the simulation data at the scale of approximately 1.5 degrees. Not only the value at this scale is qualitatively consistent with early knowledge obtained from intensive observations, but also the downscaling performance with this value is better than or comparable to that with the PAF estimated from dense station data. Finally, it is shown that the PAF estimation, although critical, cannot replace the importance of increasing input station density for downscaling.

Fully Distributed Risk-based Robust Reserve Scheduling for Bulk Hybrid AC-DC Systems

To enhance the cost-effectiveness of bulk hybrid AC-DC power systems and promote wind consumption,this paper proposes a two-stage risk-based robust reserve scheduling(RRRS)model.Different from traditional robust optimization,the proposed model applies an adjustable uncertainty set rather than a fixed one.Thereby,the operational risk is optimized together with the dispatch schedules,with a reasonable admissible region of wind power obtained correspondingly.In addition,both the operational base point and adjustment capacity of tielines are optimized in the RRRS model,which enables reserve sharing among the connected areas to handle the significant wind uncertainties.Based on the alternating direction method of multipliers(ADMM),a fully distributed framework is presented to solve the RRRS model in a distributed way.A dynamic penalty factor adjustment strategy(DPA)is also developed and applied to enhance its convergence properties.Since only limited information needs to be exchanged during the solution process,the communication burden is reduced and regional information is protected.Case studies on the 2-area 12-bus system and 3-area 354-bus system illustrate the effectiveness of the proposed model and approach.

Long-Term Consistent Recalibration of VIRR Solar Reflectance Data Record for Fengyun Polar-Orbiting Satellites

The visible infrared radiometer(VIRR)is the first instrument with longest measurements equipped on the Fengyun(FY)polar-orbiting satellites.Through re-processing of the historic VIRR measurements,long-term(over 20 yr)global data can be integrated from multiple participating VIRRs on a consistent radiometric scale,which are valuable to climate and climate change studies.Due to lack of an onboard calibration system for VIRR,the reflective solar bands must be vicariously calibrated.This study applied the multi-site vicarious approach for consistent calibration of the VIRR visible(VIS)and near-infrared(NIR)data,and produced calibration coefficients for five VIRRs on FY-1 C/D and FY-3 A/B/C.The data quality was then evaluated with observations.The reflectance predicted by using the radiative transfer model over multiple invariant desert and ocean targets was used to derive the calibration slope via a weighted fitting scheme,in which the weights are the inverse of the variance from a radiative transfer simulation evaluated with reference to Aqua moderate resolution imaging spectroradiometer(MODIS).The sensor-specific calibration coefficients were derived on a daily basis by using piecewise polynomials.The calibration reference of the VIRR solar band record was further traced to the Aqua MODIS Collection 6.1 reference calibration with a systematic correction derived from the Libya4 desert.The VIRR record was compared with the Aqua MODIS C6.1 calibration over the polar region based on simultaneous nadir overpass observations.The lifetime relative difference for each sensor are within 3.3%and 4.5%for channels 1 and 2.Invariant deserts were also employed to evaluate the stability and consistency of the VIRR record.In general,the means of the directional and spectral corrected reflectance for each sensor are within 1%of the 20-yr average,implying that the VIRR reflectance of the invariant targets is consistent to within 1%among the sensors for channels 1 and 2.The VIRR data thus derived are reliable.

Advanced Unified Failure Model on Uniformly Reinforced Concrete Box Section Members

Based on the traditional Nielsen model,a unified failure model on the uniformly reinforced concrete box section members under combined forces was introduced by Luo and Liu.One of their contributions is adjustment of the shear carrying capacity of concrete at the member failure surface.In the unified failure model,the comparison with the experimental results verified this adjustment.Nevertheless,it should be pointed out that the adjustment factor of shear carrying capacity at member failure surface for the reinforced concrete members in the unified failure model is a fixed adjustment constant for all experiment data,which is basically determined by curve fitting.However,the adjustment factor should vary with the normal stress at the member failure surface.In this paper,an advanced theoretical model is introduced,in which the adjustment factor of shear carrying capacity at failure surface is a variable related to the normal stress at failure surface.Furthermore,the advanced unified failure model on the uniformly reinforced concrete box section member can still be expressed in a simple form.Finally,the comparison with several groups of test data has verified that this advanced model is more accurate and feasible to be used in design.