RBF Neural Network Control for Linear Motor-Direct Drive Actuator Based on an Extended State Observer

Hydraulic power and other kinds of disturbance in a linear motor-direct drive actuator (LM-DDA) have a great impact on the performance of the system. A mathematical model of the LM-DDA system is established and a double-loop control system is presented. An extended state observer (ESO) with switched gain was utilized to estimate the influence of the hydraulic power and other load disturbances. Meanwhile, Radial Basis Function (RBF) neural network was utilized to optimize the parameters in this intelligent controller. The results of the dynamic tests demonstrate the performance with rapid response and improved accuracy could be attained by the proposed control scheme

Vehicular Edge Cloud Computing: Depressurize the Intelligent Vehicles Onboard Computational Power

Recently, with the rapid development of autonomous vehicles and connected vehicles, the demands of vehicular computing keep continuously growing. We notice a constant and limited onboard computational ability can hardly keep up with the rising requirements of the vehicular system and software application during their long-term lifetime, and also at the same time, the vehicles onboard computation causes an increasingly higher vehicular energy consumption. Therefore, we suppose to build a vehicular edge cloud computing (VECC) framework to resolve such a vehicular computing dilemma. In this framework, potential vehicular computing tasks can be executed remotely in an edge cloud within their time latency constraints. Simultaneously, an effective wireless network resources allocation scheme is one of the essential and fundamental factors for the QoS (quality of Service) on the VECC. In this paper, we adopted a stochastic fair allocation (SFA) algorithm to randomly allocate minimum required resource blocks to admitted vehicular users. The numerical results show great effectiveness of energy efficiency in VECC.Comment: 2018 IEEE 21st International Conference on Intelligent Transportation Systems (ITSC

Bearing fault diagnosis via kernel matrix construction based support vector machine

A novel approach on kernel matrix construction for support vector machine (SVM) is proposed to detect rolling element bearing fault efficiently. First, multi-scale coefficient matrix is achieved by processing vibration sample signal with continuous wavelet transform (CWT). Next, singular value decomposition (SVD) is applied to calculate eigenvector from wavelet coefficient matrix as sample signal feature vector. Two kernel matrices i.e. training kernel and predicting kernel, are then constructed in a novel way, which can reveal intrinsic similarity among samples and make it feasible to solve nonlinear classification problems in a high dimensional feature space. To validate its diagnosis performance, kernel matrix construction based SVM (KMCSVM) classifier is compared with three SVM classifiers i.e. classification tree kernel based SVM (CTKSVM), linear kernel based SVM (L-SVM) and radial basis function based SVM (RBFSVM), to identify different locations and severities of bearing fault. The experimental results indicate that KMCSVM has better classification capability than other methods

Finite-Time Boundedness Analysis for a Class of Switched Linear Systems with Time-Varying Delay

The problem of finite-time boundedness for a class of switched linear systems with time-varying delay and external disturbance is investigated. First of all, the multiply Lyapunov function of the system is constructed. Then, based on the Jensen inequality approach and the average dwell time method, the sufficient conditions which guarantee the system is finite-time bounded are given. Finally, an example is employed to verify the validity of the proposed method

Robust Observer Design for Switched Positive Linear System with Uncertainties

This paper is concerned with the design of a robust observer for the switched positive linear system with uncertainties. Sufficient conditions of building a robust observer are established by using the multiple copositive Lyapunov-krasovskii function and the average dwell time approach. By introducing an auxiliary slack variable, these sufficient conditions are transformed into LMI (linear matrix inequality). A numerical example is given to illustrate the validities of obtained results

Finite-Time Stabilization of Uncertain Switched Positive Linear Systems with Time-Varying Delays

This paper is concerned with finite-time stabilization (FTS) analysis for a class of uncertain switched positive linear systems with time-varying delays. First, a new definition of finite-time boundedness (FTB) is introduced for switched positive system. This definition can simplify FTS analysis. Taking interval and polytopic uncertainties into account, a robust state feedback controller is built such that the switched positive linear system is finite-time bounded. Finally, an example is employed to illustrate the validities of obtained results

Finite-Time Stabilization of Uncertain Switched Positive Linear Systems with Time-Varying Delays

This paper is concerned with finite-time stabilization (FTS) analysis for a class of uncertain switched positive linear systems with time-varying delays. First, a new definition of finite-time boundedness (FTB) is introduced for switched positive system. This definition can simplify FTS analysis. Taking interval and polytopic uncertainties into account, a robust state feedback controller is built such that the switched positive linear system is finite-time bounded. Finally, an example is employed to illustrate the validities of obtained results

Extremely High Methane Concentration in Bottom Water and Cored Sediments from Offshore Southwestern Taiwan

It has been found that Bottom Simulating Reflections (BSRs), which infer the existence of potential gas hydrates underneath seafloor sediments, are widely distributed in offshore southwestern Taiwan. Fluids and gases derived from dissociation of gas hydrates, which are typically methane enriched, affect the composition of seawater and sediments near venting areas. Hence, methane concentration of seawater and sediments become useful proxies for exploration of potential gas hydrates in a given area. We systematically collected bottom waters and sedimentary core samples for dissolved and pore-space gas analyses through five cruises: ORI-697, ORI-718, ORII-1207, ORII-1230, and ORI-732 from 2003 to 2005 in this study. Some sites with extremely high methane concentrations have been found in offshore southwestern Taiwan, e.g., sites G23 of ORI-697, N8 of ORI-718, and G96 of ORI-732. The methane concentrations of cored sediments display an increasing trend with depth. Furthermore, the down-core profiles of methane and sulfate reveal very shallow depths of sulfate methane interface (SMI) at some sites in this study. It implies sulfate reduction being mainly driven by the process of anaerobic methane oxidation (AMO) in sediments; thus indicating that there is a methane-enriched venting source, which may be the product of dissociation of gas hydrates in this area

Research on Optimal Scheduling Period of Flexray Based on Jitter-free Transmission

The scheduling period (SP) is an important parameter for building an in-vehicle communication network based on FlexRay bus. In this paper, we analyze the impact of SP on the bus bandwidth utilization and transmission jitter, study the method of assignment of bus period with jitter constraints, investigate necessary conditions should be meet when jitter-free transmission is demanded and establish mathematical model for the optimal SP. Considering there are many long period messages on in-vehicle communication network and much of bandwidth is wasted by them, we put forward an integer period extended model (IPEM) and present the structure of the modified period scheduling table and corresponding software architecture as well, thus the long period message can be transmitted with a period larger than SP and the bandwidth demanded is reduced dramatically. At last, the model is verified by various kinds of message sets and the result of simulation indicates that our method is effective

Aerodynamic Response and Running Posture Analysis When the Train Passes a Crosswind Region on a Bridge

Trains running on a bridge face more significant safety risks. Based on the Unsteady Reynolds-Averaged Navier–Stokes turbulence model, a three-dimensional Computational Fluid Dynamics computational model of the train–bridge–wind barrier was proposed in this study to measure the transient aerodynamic load of the train. The transient aerodynamic load was input into the wind–train–bridge coupling dynamic system to perform dynamic analysis of running safety. Significant fluctuations in the aerodynamic coefficients were found when the train entered and exited the wind barrier due to the dramatic change in flow pattern. The maximum value of the derailment coefficient decreased with the height of wind barriers, which hardly affected the wheel load reduction rate. The 2 m high wind barrier had no evident influence on the running posture of a general high-speed train, while the 4 m high wind barrier was proven to have better protection. Over-protection was found with an even higher wind barrier