Frequency response data-based peak filter design applied to MIMO large-scale high-precision scan stage

A large-scale high-precision scan stage is important equipment in the industrial productions of micro-fabrication such as flat panel display (FPD) lithography systems. Designing controllers for multi-input multi-output (MIMO) systems is time-consuming and needs experience because of the interaction between each axis and many controller tuning parameters. The aim of this study is to develop a peak filter design method based on frequency response data to reduce repetitive disturbance. This data-based approach does not use the model and only uses the frequency response data of the controlled system and the disturbance spectrum calculated from the scanning error data (Contribution 1). The peak filter is designed by convex optimization and satisfies robust stability conditions for six-degree-of-freedom systems (Contribution 2). The control performance of the designed peak filter is experimentally demonstrated with an industrial MIMO large-scale high-precision scan stage in reducing the scanning error of the main stroke of the translation along the $x$-axis (Contribution 3).     

High Accuracy Network Cardinalities Estimation by Step Sampling Revision on GPU

Host cardinality estimation is an important research field in network management and network security. The host cardinality estimation algorithm based on the linear estimator array is a common method. Existing algorithms do not take memory footprint into account when selecting the number of estimators used by each host. This paper analyzes the relationship between memory occupancy and estimation accuracy and compares the effects of different parameters on algorithm accuracy. The cardinality estimating algorithm is a kind of random algorithm, and there is a deviation between the estimated results and the actual cardinalities. The deviation is affected by some systematical factors, such as the random parameters inherent in linear estimator and the random functions used to map a host to different linear estimators. These random factors cannot be reduced by merging multiple estimators, and existing algorithms cannot remove the deviation caused by such factors. In this paper, we regard the estimation deviation as a random variable and proposed a sampling method, recorded as the linear estimator array step sampling algorithm (L2S), to reduce the influence of the random deviation. L2S improves the accuracy of the estimated cardinalities by evaluating and remove the expected value of random deviation. The cardinality estimation algorithm based on the estimator array is a computationally intensive algorithm, which takes a lot of time when processing high-speed network data in a serial environment. To solve this problem, a method is proposed to port the cardinality estimating algorithm based on the estimator array to the Graphics Processing Unit (GPU). Experiments on real-world highspeed network traffic show that L2S can reduce the absolute bias by more than 22% on average, and the extra time is less than 61 milliseconds on average.     

An enhanced anti-disturbance attitude control law for flexible spacecrafts subject to multiple disturbances

As well-known disturbance rejection methods, active disturbance rejection control and disturbance observer-based control can effectively improve the control performances of complex systems in the presence of disturbances. However, the accurate rejection of multiple disturbances for control systems of practical engineering, for example, the attitude control system of flexible spacecraft, is still a bottleneck problem. In order to further improve the anti-disturbance capability and reduce the conservativeness, this paper proposes a novel enhanced anti-disturbance control law for the attitude control system of flexible spacecraft by combining active disturbance rejection control and disturbance observer-based control in a unified framework. More specifically, the disturbance from flexible vibration is described by an uncertain exogenous system based on the partially known information including elastic damping ratios and modal frequencies. The disturbance observer-based control is utilized to estimate and thereby reject this disturbance. On the other hand, the other disturbances such as external environmental disturbance and complex model nonlinearity are merged into a equivalent disturbance with bounded derivative, which is compensated by using the active disturbance rejection control law. Stability and robustness analysis are carried out for the disturbance observer and extended state observer. Finally, simulation results of low-earth-orbit flexible satellite are presented to verify the effectiveness of proposed methods.     

Fixed-time disturbance observer based fixed-time back-stepping control for an air-breathing hypersonic vehicle

This paper proposes a fixed-time backstepping control scheme based on fixed-time disturbance observer for flexible air-breathing hypersonic vehicles. The backstepping control is combined with the fixed-time control technique to achieve fixed-time convergence. A fixed-time super-twisting disturbance observer, which is convergent independently of initial conditions, is employed to estimate and compensate the uncertainties and flexible effects in tracking process. A nonlinear first-order filter is adopted to avoid the “explosion of complexity” problem that arises in traditional backstepping, and to guarantee overall fixed-time stability. The closed-loop system is proven to be semi-globally uniformly ultimately fixed-time bounded via Lyapunov analysis. Simulation results are given to demonstrate the effectiveness of the proposed scheme.     

Tuning of Active Disturbance Rejection Control with application to power plant furnace regulation

Active Disturbance Rejection Control (ADRC) is emerging as a promising solution in dealing with the unmeasurable disturbances and unknown uncertainties, which are treated in a lumped manner and augmented as an extended state variable. Subsequently, an extended state observer (ESO) is designed to estimate and cancel the combined uncertain term in real time, modifying the uncertain plant to behave like a nominal model consisting of integrators. In the original ADRC formulation, the plant model is assumed to be of delay-free and its order is assumed to be equal to that of the real plant. However, a low-order ADRC is preferred and received a wide acceptance in practice because of its simplicity. Currently, the feasibility of such practice is not clearly revealed as well as its potential dangers. To this end, this paper analyzes the control mechanism from the perspective of the modified plant, which, in turn, would give guidance to parameter tuning. The effect of each parameter on the compensation efficiency and stability conditions of the modified plant is analyzed, based on which a complete tuning procedure for ADRC is developed where the initial settings is derived from the existing PI controller parameters. Finally, the proposed tuning method is experimentally used for a furnace pressure regulation of a 1000MW power plant, validating the feasibility of the low-order ADRC, even in the absence of both dynamic model and the information on the model order.     

Study on estimating electric potential in space between parallel electrodes

We have been studying on estimating distribution of permittivity between measurement electrodes using capacitance and electric potential. Two arc electrodes were separated by long distance and there electrodes were surrounded by additional electrodes respectively. In past research work, we carried out numerical electric analysis for calculating the capacitance and electric potential using Finite Element Method (FEM) and compared with experimental and numerical results. The capacitance values were almost agreed with experimental and numerical results. However, the electric potential values were different between experimental and numerical results in conventional studies. In this paper, we proposed an equivalent circuit including the stray capacity and measurement method for capacitance, the electric potential in space between long distance electrodes was estimated.     

基于改进型延时观测器的电热炉温度复合控制方法

电热炉温控系统自身具有大时滞和大惯性的特点,常规控制方法难以实现炉温预期的控制效果。针对此问题,提出一种基于改进型延时观测器的电热炉温度复合控制方法,将扰动观测器与延时观测器相结合,在消除系统集总扰动的同时,估计出时滞前的状态变量,简化滑模控制器的设计,提高系统的抗干扰能力,消除时滞危害。将所提控制方法与GPC控制、基于Smith预估器的模糊自适应PID控制进行仿真对比,结果表明：所提控制方案的响应速度更快,超调量几乎为零,抗干扰能力更强,鲁棒性更好。     

Student perceptions of model-based estimating

The use of building information modeling (BIM) is well established in architecture, engineering and construction. However, previous studies note a lack of BIM expertise in academia, leading to slow adoption and limited knowledge on which to base BIM-related content. To improve course development, it is important to understand students’ perceptions of BIM-related subject matter. This study exposed estimating students (n = 214) to a model-based quantity takeoff (QTO) tutorial using Revit. Students’ perceptions of a Revit-based BIM’s usefulness for easily providing reliable and accurate material quantities were measured using a pre-test, tutorial and post-test design. Results revealed significant differences in students’ mean levels of agreement that an accurate QTO is completed for an estimator with the click of a button when a design team generated BIM model is available. Results also revealed significant differences in students’ level of agreement that a Revit-based BIM makes performing QTO by hand obsolete. This study provides educators’ insight into students’ perceptions of BIM use in QTO. Understanding student perceptions is paramount for construction management educators when designing a course and attempting to convey the value of foundational estimating skills while acknowledging the existence of more technologically advance estimating methods. Limitations and opportunities for further research are discussed.     

Mismatched disturbance attenuation control for static var compensator with uncertain parameters

The use of a static var compensator (SVC) as a component of flexible alternating current transmission system (FACTS) devices to control power systems has been investigated for decades. Its aim is to regulate the system voltage and improve the stability and loadability of power systems. A typical assumption in such a system is that the parameters of the controlled system are known accurately, which is rarely satisfied in practice. This paper explores the development of a simple but effective controller for a single-machine infinite-bus power system with SVC subjected to both matched and mismatched disturbances where the controller derivation is based on the assumption that all parameters used in the system modeling are unknown, but bounded in size. The research in this paper illustrates how an indirect robust control can be incorporated with a modified disturbance observer-based feedforward term to attenuate the influence of parameter variations and disturbances from the outputs of the system. Simulation results are presented to confirm the effectiveness of the proposed scheme.     

A tree-structured crash surrogate measure for freeways

In this paper, we propose a novel methodology to define and estimate a surrogate measure. By imposing a hypothetical disturbance to the leading vehicle, the following vehicle’s action is represented as a probabilistic causal model. After that, a tree is built to describe the eight possible conflict types under the model. The surrogate measure, named Aggregated Crash Index (ACI), is thus proposed to measure the crash risk. This index reflects the accommodability of freeway traffic state to a traffic disturbance. We further apply this measure to evaluate the crash risks in a freeway section of Pacific Motorway, Australia. The results show that the proposed indicator outperforms the three traditional crash surrogate measures (i.e., Time to Collision, Proportion of Stopping Distance, and Crash Potential Index) in representing rear-end crash risks. The applications of this measure are also discussed.