This paper constitutes the sensitivity study of application the Polar WRF model to the Svalbard area with testing selected parameterizations, including planetary boundary layer, radiation and microphysics schemes. The model was configured, using three one-way nested domains with 27 km, 9 km and 3 km grid cell resolutions. Results from the innermost domain were presented and compared against measured wind speed and air temperature at 10 meteorological stations. The study period covers two months: June 2008 and January 2009. Significant differences between simulations results occurred for planetary boundary layer (PBL) schemes in January 2009. The Mellor-Yamada-Janjic (MYJ) planetary boundary layer (PBL) scheme resulted in the lowest errors for air temperature, according to mean error (ME), mean absolute error (MAE) and correlation coefficient values, where for wind speed this scheme was the worst from all the PBL schemes tested. In the case of June 2008, shortwave and longwave radiation schemes influenced the results the most. Generally, higher correlations were obtained for January, both for air temperature and wind speed. However, the model performs better for June in terms of ME and MAE error statistics. The results were also analyzed spatially, to summarize the uncertainty of the model results related to the analyzed parameterization schemes groups. Significant variability among simulations was calculated for January 2009 over the northern part of Spitsbergen and fjords for the PBL schemes. Standard deviations for monthly average simulated values were up to 3.5°C for air temperature and around 1 m s-1 for wind speed.
Control of the technological processes of coal enrichment takes place in the presence of wide disturbances. Thus, one of the basic tasks of the coal enrichment process control systems is the stabilization of coal quality parameters at a preset level. An important problem is the choice of the controller which is robust for a variety of disturbances. The tuning of the controller parameters is no less important in the control process . Many methods of tuning the controller use the dynamic characteristics of the controlled process (dynamic model of the controlled object). Based on many studies it was found that the dynamics of many processes of coal enrichment can be represented by a dynamic model with properties of the inertial element with a time delay. The identification of object parameters (including the time constant) in industrial conditions is usually performed during normal operation (with the influence of disturbances) from this reason, determined parameters of the dynamic model may differ from the parameters of the actual process. The control system with controller parameters tuned on the basis of such a model may not satisfy the assumed control quality requirements. In the paper, the analysis of the influence of changes in object model parameters in the course of the controlled value has been carried out. Research on the controller settings calculated according to parameters T and τ were carried out on objects with other parameter values. In the studies, a sensitivity analysis method was used. The sensitivity analysis for the three methods of tuning the PI controller for the coal enrichment processes control systems characterized by dynamic properties of the inertial element with time delay has been presented. Considerations are performed at various parameters of the object on the basis of the response of the control system for a constant value of set point. The assessment of considered tuning methods based on selected indices of control quality have been implemented.
The problem of mathematical modelling and indication of properties of a DIP has been investigated in this paper. The aim of this work is to aggregate the knowledge on a DIP modelling using the Euler-Lagrange formalism in the presence of external forces and friction. To indicate the main properties important for simulation, model parameters identification and control system synthesis, analytical and numerical tools have been used. The investigated properties include stability of equilibrium points, a chaos of dynamics and non-minimum phase behaviour around an upper position. The presented results refer to the model of a physical (constructed) DIP system.
To reduce the influence of the static unbalance on an infrared missile guidance system, a new static unbalance measure system for the gimbals axes has been developed. Considering the coupling effects caused by a mass eccentricity, the static balance condition and measure sequence for each gimbal axis are obtained. A novel static unbalance test approach is proposed after analyzing the dynamic model of the measured gimbal axis. This approach is to drive the measured gimbal axis to do sinusoidal reciprocating motion in a small angle and collect its drive currents in real time. Then the static unbalance of the measured gimbal axis can be obtained by the current multi-cycle integration. Also a measuring system using the proposed approach has been developed. A balanced simulator is used to verify the proposed approach by the load and repeatability tests. The results show the proposed approach enhances the efficiency of the static unbalance measurement, and the developed measuring system is able to achieve a high precision with a greater stability.
This paper presents a robust model free controller (RMFC) for a class of uncertain continuous-time single-input single-output (SISO) minimum-phase nonaffine-in-control systems. Firstly, the existence of an unknown dynamic inversion controller that can achieve control objectives is demonstrated. Afterwards, a fast approximator is designed to estimate as best as possible this dynamic inversion controller. The proposed robust model free controller is an equivalent realization of the designed fast approximator. The perturbation theory and Tikhonov’s theorem are used to analyze the stability of the overall closed-loop system. The performance of the developped controller are verified experimentally in the position control of a pneumatic actuator system.
This paper researches the application of grey system theory in cost forecasting of the coal mine. The grey model (GM(1.1)) is widely used in forecasting in business and industrial systems with advantages of minimal data, a short time and little fluctuation. Also, the model fits exponentially with increasing data more precisely than other prediction techniques. However, the traditional GM(1.1) model suffers from the poor anti-interference ability. Aimed at the flaws of the conventional GM(1.1) model, this paper proposes a novel dynamic forecasting model with the theory of background value optimization and Fourier-series residual error correction based on the traditional GM(1.1) model. The new model applies the golden segmentation optimization method to optimize the background value and Fourier-series theory to extract periodic information in the grey forecasting model for correcting the residual error. In the proposed dynamic model, the newest data is gradually added while the oldest is removed from the original data sequence. To test the new model’s forecasting performance, it was applied to the prediction of unit costs in coal mining, and the results show that the prediction accuracy is improved compared with other grey forecasting models. The new model gives a MAPE & C value of 0.14% and 0.02, respectively, compared to 1.75% and 0.37 respectively for the traditional GM(1.1) model. Thus, the new GM(1.1) model proposed in this paper, with advantages of practical application and high accuracy, provides a new method for cost forecasting in coal mining, and then help decision makers to make more scientific decisions for the mining operation.