The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
Aiming at the issues of random delay and delay uncertainty in both the before channel and feedback channel for network control system, the root causes of random delay influence closed-loop control system by case is analysis, and the predictive control method based on neural network to solve the feasibility of existence network random delay in control system closed-loop control has provided. Simulation...
Hardware failures in cloud data centers may cause substantial losses to cloud providers and cloud users. Therefore, the ability to accurately predict when failures occur is of paramount importance. In this paper, we present FailureSim, a simulator based on CloudSim that supports failure prediction. FailureSim obtains performance related information from the cloud and classifies the status of the hardware...
Recent years have seen a proliferation of complex Advanced Driver Assistance Systems (ADAS), in particular, for use in autonomous cars. These systems consist of sensors and cameras as well as image processing and decision support software components. They are meant to help drivers by providing proper warnings or by preventing dangerous situations. In this paper, we focus on the problem of design time...
Application of neural networks for direct prediction of lateral-directional force and moments coefficients from the measured flight data of the research aircraft is proposed in this paper. Proposed model of neural networks appears to be a suitable practical approach to develop relationship between flight variables. This relationship eliminates the need of aerodynamic model as well as thrust model...
The current work presents the simulation of tool life in high speed Hard Turning (HSHT) of AISI 4340 hardened steel using artificial neural networks. An experimental investigation was carried out using ceramic cutting tools, composed approximately of Al2O3 (70%) and TiC (30%) on AISI 4340 heat treated to a hardness of 60 HRC. A new model was adjusted to predict tool life for different values of cutting...
This paper focuses on a critical component of the situational awareness (SA), the neural control of depth flight of an autonomous underwater vehicle (AUV). Constant depth flight is a challenging but important task for AUVs to achieve high level of autonomy under adverse conditions. The fundamental requirement for constant depth flight is the knowledge of the depth, and a properly designed controller...
The four-stage evaporator is the core of the process in the manufacture of concentrated grape juice. The dynamic features of this process are very complex due to inputs and outputs constraints, time delays, loop interactions and the persistent unmeasured disturbances that affect it. Therefore, this kind of process requires a robust control in order to assure a stable operation taking into account...
The prediction and control of cutting process was a complicated problem and the suitable cutting parameters are instrumental to cutting process, the prediction models for cutting parameters realized with artificial neural networks was proposed in this paper. Artificial neural networks have strong non-linear modeling ability which can express the nonlinear mapping relation of input and output, but...
One of the challenges in designing computer networks is "queue management and congestion avoidance". There are several studies for congestion reduction and controlling such as random early detection (RED) and its variants. More recent works on developing congestion avoidance methods include modeling a TCP flow in an active queue management (AQM) of a bottlenecked network link. Rather than...
Based on the analysis of the standard Particle Swarm Optimization and the characteristic of typical multi-intersection for urban trunk road, a traffic flow forecasting model using dynamic recursion neural network is presented. The feature of this network is that the output of the hidden layer connects to the input of itself through the delay and storage of the context layer. The method of self-connection...
A control system, which consists of several cooperative modules whose combination and structures change dynamically according to the state and environment, is discussed in this paper. We propose a method to design a control system by modular learning. Numerical simulations and flight experiment of an autonomous aero-robot demonstrate the effectiveness of the proposed method.
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.