Identification and U-control of a state-space system with time-delay

This article presents a state-space model with time-delay to map the relationship between known input-output data for discrete systems. For the given input-output data, a model identification algorithm combining parameter estimation and state estimation is proposed in line with the causality constraints. Consequently, this article proposes a least squares parameter estimation algorithm, and analyzes its convergence for the studied systems to prove that the parameter estimation errors converge to zero under the persistent excitation conditions. In control system design, the U-model based control is introduced to provide a unilateral platform to improve the design efficiency and generality. A simulation portfolio from modeling to control is provided with computational experiments to validate the derived results.     

A PID-incorporated Latent Factorization of Tensors Approach to Dynamically Weighted Directed Network Analysis

A large-scale dynamically weighted directed network (DWDN) involving numerous entities and massive dynamic interaction is an essential data source in many big-data-related applications, like in a terminal interaction pattern analysis system (TIPAS). It can be represented by a high-dimensional and incomplete (HDI) tensor whose entries are mostly unknown. Yet such an HDI tensor contains a wealth knowledge regarding various desired patterns like potential links in a DWDN. A latent factorization-of-tensors (LFT) model proves to be highly efficient in extracting such knowledge from an HDI tensor, which is commonly achieved via a stochastic gradient descent (SGD) solver. However, an SGD-based LFT model suffers from slow convergence that impairs its efficiency on large-scale DWDNs. To address this issue, this work proposes a proportional-integral-derivative (PID)-incorporated LFT model. It constructs an adjusted instance error based on the PID control principle, and then substitutes it into an SGD solver to improve the convergence rate. Empirical studies on two DWDNs generated by a real TIPAS show that compared with state-of-the-art models, the proposed model achieves significant efficiency gain as well as highly competitive prediction accuracy when handling the task of missing link prediction for a given DWDN.      

Evaluation of dynamic modulus measurement for C/C-SiC composites at different temperatures

The determination of elastic properties at application temperature is fundamental for the design of fibre reinforced ceramic composite components. An attractive method to characterize the flexural modulus at room and high temperature under specific atmosphere is the nondestructive Resonant Frequency Damping Analysis (RFDA). The objective of this paper was to evaluate and validate the modulus measurement via RFDA for orthotropic C/C-SiC composites at the application temperature. At room temperature flexural moduli of C/C-SiC with 0/90° reinforcement were measured under quasi-static 4-point bending loads and compared with dynamic moduli measured via RFDA longitudinally to fibre direction. The dynamic modulus of C/C-SiC was then measured via RFDA up to 1250°C under flowing inert gas and showed an increase with temperature which fitted with literature values. The measured fundamental frequencies were finally compared to those resulting from numerical modal analyses. Dynamic and quasi-static flexural moduli are comparable and the numerical analyses proved that bending modes are correctly modeled by means of dynamic modulus measured via RFDA. The nondestructive RFDA as well as the numerical modeling approach are suitable for evaluation of C/C-SiC and may be transferred to other fibre reinforced ceramic composite materials.     

Structural load alleviation using distributed delay shaper: Application to flexible aircraft

Lightweight flexible aircraft suffers from unwanted oscillatory vibrations during aircraft manoeuvres. A recently developed distributed-delay signal (DZV) shaper is therefore proposed to be applied as a feedforward controller to alleviate the manoeuvre loads, as an alternative to traditional structural filters used routinely in this context. Structural filters are essentially linear low-pass filters with bandwidth below the significant flexible modes, applied to control signals generated either by the pilot’s direct input or by the flight control system. It has been showed that if instead a properly tuned signal shaper is used, better performance can be achieved: first, the target modes are significantly attenuated while the responsiveness of the aircraft is less compromised and secondly, the oscillatory nature of the vibrations are reduced. The high fidelity simulation results on a full scaled dynamic model of a highly flexible blended wing–body (BWB) aircraft show that in comparison to traditional structural filters, signal shapers significantly reduce the wing root loading (forces and moments) which provides potential structural benefits.     

气压仪器检定装置的升级改造

文章针对气压检定装置在使用中存在的一些问题,会同厂家对其进行了升级改造。介绍了改造后的气压检定装置的设计原理、软件和硬件设计以及技术指标等,新装置集成了目前先进的计量设备及技术,编写相应的程序软件升级改造而成。可广泛适用于气象部门空盒气压表、自动站气压传感器以及部分数字压力计的计量检定工作,实现气压检定工作的自动化,提高检定数据的准确性和可靠性,并有效提高检定的工作效率。     

气候环境实验室地面结冰云雾模拟控制系统设计

飞机结冰会引起飞机气动特性、动力系统性能改变,甚至造成飞行事故。地面结冰云雾模拟设施作为一种模拟飞机飞行结冰条件的重要设备,常用于飞机防除冰系统功能验证。针对气候环境实验室结冰云雾试验条件需要,在对地面结冰云雾模拟系统进行研究的基础上,对适用于气候环境实验室的结冰云雾模拟系统进行了设计。对系统关键设计技术、系统功能及组成进行了分析,并对控制系统方案进行了详细阐述。试验表明,控制系统人机界面友好,运行可靠,能够满足液态水含量、雾滴直径参数的精确调节,产生符合试验所需的结冰环境。     

Identifying and Verifying Vulnerabilities through PLC Network Protocol and Memory Structure Analysis

Cyberattacks on the Industrial Control System (ICS) have recently been increasing, made more intelligent by advancing technologies. As such, cybersecurity for such systems is attracting attention. As a core element of control devices, the Programmable Logic Controller (PLC) in an ICS carries out on-site control over the ICS. A cyberattack on the PLC will cause damages on the overall ICS, with Stuxnet and Duqu as the most representative cases. Thus, cybersecurity for PLCs is considered essential, and many researchers carry out a variety of analyses on the vulnerabilities of PLCs as part of preemptive efforts against attacks. In this study, a vulnerability analysis was conducted on the XGB PLC. Security vulnerabilities were identified by analyzing the network protocols and memory structure of PLCs and were utilized to launch replay attack, memory modulation attack, and FTP/Web service account theft for the verification of the results. Based on the results, the attacks were proven to be able to cause the PLC to malfunction and disable it, and the identified vulnerabilities were defined.     

Local weather prediction system for a heating plant using cognitive approaches

Present-day requirements emphasize the need of saving energy. It relates mainly to industrial companies, where the minimization of energy consumption is one of their most important tasks they face. In our paper, we deal with the design of the so-called weather prediction system (WPS) for the needs of a heating plant. The primary task of such a WPS is timely predicting expected heat consumption to prepare the technology characterized by long delays in advance. Heat prediction depends primarily on weather so the crucial part of WPS is the weather, especially temperature, prediction. However, a prediction system needs a variety of further data, too. Therefore, WPS must be regarded as a complex system, including data collection, its processing, own prediction and eventual decision support. This paper gives the overview about existing data processing systems and prediction methods and then it describes a concrete design of a WPS with distributed data measuring points (stations), which are processed using a structure of neural networks based on multilayer perceptrons (MLP) with a combination of fuzzy logic. Based on real experiments we show that also such simple means as MLPs are able to solve complex problems. The paper contains a basic methodology for designing similar WPS, too.     

Covariance matrix adaptation evolution strategy based design of fixed structure robust H∞ loop shaping controller

This paper proposes the application of Covariance Matrix Adaptation Evolution Strategy (CMA-ES) in fixed structure H_∞ loop shaping controller design. Integral Time Absolute Error (ITAE) performance requirement is incorporated as a constraint with an objective of maximization of stability margin in the fixed structure H_∞ loop shaping controller design problem. Pneumatic servo system, separating tower process and F18 fighter aircraft system are considered as test systems. The CMA-ES designed fixed structure H_∞ loop-shaping controller is compared with the traditional H_∞ loop shaping controller, non-smooth optimization and Heuristic Kalman Algorithm (HKA) based fixed structure H_∞ loop shaping controllers in terms of stability margin. 20% perturbation in the nominal plant is used to validate the robustness of the CMA-ES designed H_∞ loop shaping controller. The effect of Finite Word Length (FWL) is considered to show the implementation difficulties of controller in digital processors. Simulation results demonstrated that CMA-ES based fixed structure H_∞ loop shaping controller is suitable for real time implementation with good robust stability and performance.