Higher-Order Iterative Learning Control with Optimal Control Gains Based on Evolutionary Algorithm for Nonlinear System

For the nonlinear discrete-time system, higher-order iterative learning control (HOILC) with optimal control gains based on evolutionary algorithm (EA) is developed in this paper. Since the updating actions are constituted by the tracking information from several previous iterations, the suitably designed HOILC schemes with appropriate control gains usually achieve fast convergence speed. To optimize the control gains in HOILC approach, EA is introduced. The encoding strategy, population initialization, and fitness function in EA are designed according to the HOILC characteristics. With the global optimization of EA, the optimal control gains of HOILC are selected adaptively so that the number of convergence iteration is reduced in ILC process. It is shown in simulation that the sum absolute error, total square error, and maximum absolute error of tracking in the proposed HOILC based on EA are convergent faster than those in conventional HOILC.

Research on UAV Three-Phase Transmission Line Tracking and Localization Method Based on Electric Field Sensor Array

The tracking and positioning of transmission lines is a key element for UAVs (Unmanned Aerial Vehicles) to achieve autonomous inspection of transmission lines. Current methods are vulnerable to weather and environmental factors, have high costs, and have difficulties in data processing. Therefore, this paper proposes a transmission line tracking and localization method based on the electric field sensor array, which calculates the current UAV’s heading angle deflection angle, the distance between the transmission line and the UAV, and the elevation angle, providing a new idea to solve the problem of UAV inspection of transmission lines. At the same time, the electric field distribution of different arrangements of three-phase transmission lines was analyzed using COMSOL to determine the flight area of the UAV. By comparing the electric field distribution of the UAV flight area and single-phase transmission lines, it was verified that the current method is also applicable in the three-phase transmission line scenario, and it was further verified that the sensor array used can sense the change of the UAV position in the flight area, indicating that the electric field sensor array can realize the transmission line tracking and localization of transmission lines. The experimental results showed that, in the three-phase transmission line scenario, when the sensor array moves along the transmission straight wire, the maximum absolute error of the heading angle deflection angle calculated according to this method was 8.2°, the maximum absolute error of the distance between the array and the transmission line was 19.3 cm, and the maximum absolute error of the elevation angle was 11.37°; the error was within a reasonable range and can be used for the UAV to realize autonomous inspection.

Piecewise Parabolic Approximate Computation Based on an Error-Flattened Segmenter and a Novel Quantizer

This paper proposes a novel Piecewise Parabolic Approximate Computation method for hardware function evaluation, which mainly incorporates an error-flattened segmenter and an implementation quantizer. Under a required software maximum absolute error (MAE), the segmenter adaptively selects a minimum number of parabolas to approximate the objective function. By completely imitating the circuit’s behavior before actual implementation, the quantizer calculates the minimum quantization bit width to ensure a non-redundant fixed-point hardware architecture with an MAE of 1 unit of least precision (ulp), eliminating the iterative design time for the circuits. The method causes the number of segments to reach the theoretical limit, and has great advantages in the number of segments and the size of the look-up table (LUT). To prove the superiority of the proposed method, six common functions were implemented by the proposed method under TSMC-90 nm technology. Compared to the state-of-the-art piecewise quadratic approximation methods, the proposed method has advantages in the area with roughly the same delay. Furthermore, a unified function-evaluation unit was also implemented under TSMC-90 nm technology.

An Active Balancing Method Based on SOC and Capacitance for Lithium-Ion Batteries in Electric Vehicles

An active balancing method based on the state of charge (SOC) and capacitance is presented in this article to solve the inconsistency problem of lithium-ion batteries in electric vehicles. The terminal voltage of each battery is collected first. Then, each battery SOC is accurately estimated by an extended Kalman filter (EKF) algorithm. In the experiment, the maximum absolute error of SOC evaluation is only 0.0061, and the mean absolute error is 0.0013 when the initial battery SOC is clear. Meanwhile, the maximum absolute error of SOC evaluation is 0.5 and the average absolute error of SOC is 0.0015 when the initial battery SOC is not clear. Afterward, an active balancing circuit based on the estimated battery SOC and capacitance is designed. The energy of capacitance is charged by the battery whose SOC is higher than the other batteries through the circuit to avoid the battery being overcharged. Then, the SOC of batteries gradually turn consistent. In the simulation experiment, the SOC difference of batteries is 7% before the balancing. Meanwhile, the SOC difference of batteries reduces to 0.02% after the balancing and the consuming time is merely 272s, which manifests that the proposed balancing method has a fast balancing speed and better balancing efficiency.

On the Problem of Choosing Optimal Methods for Approximating Functions

The materials of the article relate to the field of optimization of control systems and signal processing when preparing models for technical implementation. The informational level of structural and functional decomposition of models of approximators of square root functions is considered. The article investigates two classes of computational methods: sequential - polynomials of the best approximation and parallel - multilayer feedforward neural networks. For each of the classes, using particular examples, the approximation error was calculated according to the criteria of the maximum absolute error and the area of the error function, as well as the computational costs as the sum of the number of mathematical operations and queries in the memory of the calculator.

High-fidelity aerodynamic modeling of an aircraft using OpenFoam – application on the CRJ700

This study is focused on the development of longitudinal aerodynamic models for steady flight conditions. While several commercial solvers are available for this type of work, we seek to evaluate the accuracy of an open source software. This study aims to verify and demonstrate the accuracy of the OpenFoam solver when it is used on basic computers (32–64GB of RAM and eight cores). A new methodology was developed to show how an aerodynamic model of an aircraft could be designed using OpenFoam software. The mesh and the simulations were designed only using OpenFoam utilities, such as blockMesh, snappyHexMesh, simpleFoam and rhoSimpleFoam. For the methodology illustration, the process was applied to the Bombardier CRJ700 aircraft and simulations were performed for its flight envelope, up to M0.79. Forces and moments obtained with the OpenFoam model were compared with an accurate flight data source (level D flight simulator). Excellent results in data agreement were obtained with a maximum absolute error of 0.0026 for the drag coefficient, thus validating a high-fidelity aerodynamic model for the Bombardier CRJ-700 aircraft.

Inner Wall Temperature Distribution Measurement of The Ladle Based on Cavity Effective Emissivity Correction

Inner wall temperature of ladle is closely related to the quality of steelmaking and control of steel-making tapping temperature. This article adopts a rotating platform to drive an infrared temperature sensor and a laser sensor to scan the temperature field distribution of the ladle inner wall at the hot repair station, where the scanning laser sensor obtains coordinates of each measured point. Because of measuring errors of infrared thermal radiation caused by emissivity uncertainty of the ladle inner wall surface, this article proposes a method for temperature measurement based on Monte Carlo model for effective emissivity correction of each measured point. In the model, we consider the ladle and fire baffle as a cavity. By calculation of the model, the effect of distance from the fire baffle to the ladle and the material surface emissivity of the ladle inner wall on the effective emissivity of the cavity are obtained. After that, the effective emissivity of each measured point is determined. Then the scanning temperature of each measured point is corrected to real temperature. By field measuring test and verification contrast, the results show that: the maximum absolute error of the method in this article is 4.7℃, the minimum error is 0.6℃, and the average error is less than 2.8℃. The method in this article achieves high measurement accuracy and contributes to the control of metallurgical process based on temperature information.

A MATHEMATICAL APPROXIMATION TO LEFT-SIDED TRUNCATED NORMAL DISTRIBUTION BASED ON HART’S MODEL

Left-sided truncated distributions (LSTD) have been found in different situations in the industry. For example, the life distribution of used devices is left-sided truncated distribution. Moreover, if a lower specification exists without the upper specification limit, the product distribution is truncated from the left side. Left-sided truncated normal distributions (LSTND) is a special case where the original distribution is normal. LSTND characteristics, as well as cumulative densities and probabilities can be difficult to employ manually, with most practitioners relying largely on specialized (and expensive) software. In many cases, practitioners are against purchasing software, as they are often limited in the number of estimations. The paper will provide an accurate and straightforward approximation to the cumulative density of LSTND. Hart’s normal distribution is simplified and used as a foundation of this model. The maximum absolute error for the curve at different truncation points (i.e., ZL) over the definition range (i.e., [zL: ∞]) is as follows: 0.004303 for ZL=-4, 0.00432 for ZL=-3, 0.00449 for ZL=-2, 0.005727 for ZL=-1, and 0.0106 for ZL=0. Even the maximum errors are very ignorable in probability applications. Further, it is rare to find a truncation point of higher than -2 in the industry.

Probability Integral Method Parameter Determination by SBAS-InSAR Technology and GWO Algorithm

This paper proposed a method based on the SBAS-InSAR and gray wolf optimization algorithm aiming at the time-consuming and laborious defects of the traditional method used to obtain the expected parameters of the probability integral method and the shortcomings of the InSAR technology in the field of large gradient deformation detection in the mining area. The fitness function of the algorithm was established based on the geometric relationship between the radar side imaging and the three-dimensional model of the probability integral method. The stable sinking point of the settlement boundary obtained by SBAS-InSAR was used as the input value for the calculation of the predicted parameters of the probability integral method. Firstly, the simulation experiment was employed for the simulation of the direction of the InSAR line of sight combined with the geological mining conditions of the assumed working face, thereby obtaining the probability integral prediction parameters of the working face. Consequently, the maximum relative error of q , b , tanβ, and θ 0 does not exceed 8%, and that of S 1 , S 2 , S 3 , and S 4 does not exceed 35.5% (low parameter sensitivity). The error of the LOS-direction deformation fitting is 0.076 m, which meets the tolerance requirements, and the result is trustworthy. At last, the parameter finding method is applied to the engineering example, that is, the 112201 working face of Xiaobaodang Coal Mine in the northern Shaanxi mining area. The settlement value of the stable boundary point is obtained based on the SBAS-InSAR results, which is substituted into the fitness function. And the GWO optimization algorithm is used for optimization and parameter finding; the probability integral expected parameters of the working face are calculated as q = 0.63 , b = 0.37 , tan β = 2.76 , θ 0 = 83.94 , S 1 = − 36.34 m , S 2 = 26.69 m , S 3 = − 45.64 m , and S 4 = 39.62 m . Substitute the obtained parameters into the probability integral model for the prediction of the vertical and horizontal displacements of the working face, and verify its accuracy with the GPS measured data. The results showed that the maximum absolute error of vertical displacement reached 116 mm, the median error was 63 mm, and the maximum absolute error of north-south horizontal movement reached 56 mm; meanwhile, the median error was 23 mm, the maximum absolute error of east-west horizontal movement reached 61 mm, and the median error was 29 mm; all the above parameters are within the tolerance range, indicating that the method for the calculation of probability integral parameters proposed in this paper is applicable in actual engineering.

Optimization of Indoor Bluetooth Ranging Model Based on RSSI

Because the received signal strength indication (RSSI) ranging technology has problems with line-of-sight and multipath effects in indoor environments, the actual received RSSI value is unstable. In order to reduce the influence of RSSI value volatility on ranging accuracy, according to the fluctuation characteristics of the signal itself, a combined filtering method of Gaussian, median and mean is proposed to process the collected RSSI values, and the least squares method is used to fit and optimize the ranging parameter. Experiments show that using the RSSI intensity value processed by the combined filtering method to establish a model to achieve ranging, the maximum absolute error is about 2 m, and the absolute average error is about 0.763 m. The accuracy of the ranging has been significantly improved, and the ranging model has been optimized.