Real Time Platform for Rapid Prototyping and On-line Simulation of Digital Controllers for Electrical Drives

2006 ◽  
Author(s):  
Arno Ebner ◽  
Martin Ganchev ◽  
Johannes V. Gragger ◽  
Franz Pirker
Keyword(s):  
Rapid Prototyping ◽  
Real Time ◽  
Digital Controllers ◽  
Electrical Drives ◽  
On Line

Adaptive Signal Analysis and Interpretation for Real-time Intelligent Patient Monitoring

1994 ◽  
Vol 33 (01) ◽  
pp. 60-63 ◽  
Author(s):  
E. J. Manders ◽  
D. P. Lindstrom ◽  
B. M. Dawant
Keyword(s):  
Computer Architecture ◽  
Real Time ◽  
Data Abstraction ◽  
Monitoring Strategy ◽  
Intelligent Monitoring ◽  
Patient Status ◽  
On Line ◽  
Main Components ◽  
And Control ◽  
Adaptive Signal

Abstract:On-line intelligent monitoring, diagnosis, and control of dynamic systems such as patients in intensive care units necessitates the context-dependent acquisition, processing, analysis, and interpretation of large amounts of possibly noisy and incomplete data. The dynamic nature of the process also requires a continuous evaluation and adaptation of the monitoring strategy to respond to changes both in the monitored patient and in the monitoring equipment. Moreover, real-time constraints may imply data losses, the importance of which has to be minimized. This paper presents a computer architecture designed to accomplish these tasks. Its main components are a model and a data abstraction module. The model provides the system with a monitoring context related to the patient status. The data abstraction module relies on that information to adapt the monitoring strategy and provide the model with the necessary information. This paper focuses on the data abstraction module and its interaction with the model.

Nitrogen Removal in a Real-Time Controlled Sequencing Batch Membrane Bioreactor

2010 ◽  
Vol 5 (3) ◽  
Author(s):  
Cheng-Nan Chang ◽  
Li-Ling Lee ◽  
Han-Hsien Huang ◽  
Ying-Chih Chiu
Keyword(s):  
Real Time ◽  
Nitrogen Removal ◽  
Membrane Bioreactor ◽  
Synthetic Wastewater ◽  
Real Time Control ◽  
Time Control ◽  
Cake Layer ◽  
On Line ◽  
Solid Liquid ◽  
Solid Liquid Separation

The performance of a real-time controlled Sequencing Batch Membrane Bioreactor (SBMBR) for removing organic matter and nitrogen from synthetic wastewater has been investigated in this study under two specific ammonia loadings of 0.0086 and 0.0045g NH4+-N gVSS−1 day−1. Laboratory results indicate that both COD and DOC removal are greater than 97.5% (w/w) but the major benefit of using membrane for solid-liquid separation is that the effluent can be decanted through the membrane while aeration is continued during the draw stage. With a continued aeration, the sludge cake layer is prevented from forming thus alleviating the membrane clogging problem in addition to significant nitrification activities observed in the draw stage. With adequate aeration in the oxic stage, the nitrogen removal efficiency exceeding 99% can be achieved with the SBMBR system. Furthermore, the SBMBR system has also been used to study the occurrence of ammonia valley and nitrate knee that can be used for real-time control of the biological process. Under appropriate ammonia loading rates, applicable ammonia valley and nitrate knee are detected. The real-time control of the SBMBR can be performed based on on-line ORP and pH measurements.

Modifications of rainfall runoff and decision finding models for on-line simulation in real time control

1999 ◽  
Vol 39 (9) ◽  
pp. 201-207
Author(s):  
Andreas Cassar ◽  
Hans-Reinhard Verworn
Keyword(s):  
Real Time ◽  
Urban Drainage ◽  
Rain Event ◽  
Rainfall Runoff ◽  
Real Time Control ◽  
Design Storm ◽  
Time Control ◽  
Timing Data ◽  
On Line ◽  
Rainfall Runoff Model

Most of the existing rainfall runoff models for urban drainage systems have been designed for off-line calculations. With a design storm or a historical rain event and the model system the rainfall runoff processes are simulated, the faster the better. Since very recently, hydrodynamic models have been considered to be much too slow for real time applications. However, with the computing power of today - and even more so of tomorrow - very complex and detailed models may be run on-line and in real time. While the algorithms basically remain the same as for off-line simulations, problems concerning timing, data management and inter process communication have to be identified and solved. This paper describes the upgrading of the existing hydrodynamic rainfall runoff model HYSTEM/EXTRAN and the decision finding model INTL for real time performance, their implementation on a network of UNIX stations and the experiences from running them within an urban drainage real time control project. The main focus is not on what the models do but how they are put into action and made to run smoothly embedded in all the processes necessary in operational real time control.

scholarly journals Power Hardware-in-the-Loop-Based Performance Analysis of Different Converter Controllers for Fast Active Power Regulation in Low-Inertia Power Systems

Energies ◽  
2021 ◽  
Vol 14 (11) ◽  
pp. 3274
Author(s):  
Jose Rueda Torres ◽  
Zameer Ahmad ◽  
Nidarshan Veera Kumar ◽  
Elyas Rakhshani ◽  
Ebrahim Adabi ◽  
...  
Keyword(s):  
Performance Evaluation ◽  
Power Systems ◽  
Real Time ◽  
Control Strategies ◽  
Active Power ◽  
Power Electronic ◽  
Hardware In The Loop ◽  
Digital Controllers ◽  
Power Regulation ◽  
The Impact

Future electrical power systems will be dominated by power electronic converters, which are deployed for the integration of renewable power plants, responsive demand, and different types of storage systems. The stability of such systems will strongly depend on the control strategies attached to the converters. In this context, laboratory-scale setups are becoming the key tools for prototyping and evaluating the performance and robustness of different converter technologies and control strategies. The performance evaluation of control strategies for dynamic frequency support using fast active power regulation (FAPR) requires the urgent development of a suitable power hardware-in-the-loop (PHIL) setup. In this paper, the most prominent emerging types of FAPR are selected and studied: droop-based FAPR, droop derivative-based FAPR, and virtual synchronous power (VSP)-based FAPR. A novel setup for PHIL-based performance evaluation of these strategies is proposed. The setup combines the advanced modeling and simulation functions of a real-time digital simulation platform (RTDS), an external programmable unit to implement the studied FAPR control strategies as digital controllers, and actual hardware. The hardware setup consists of a grid emulator to recreate the dynamic response as seen from the interface bus of the grid side converter of a power electronic-interfaced device (e.g., type-IV wind turbines), and a mockup voltage source converter (VSC, i.e., a device under test (DUT)). The DUT is virtually interfaced to one high-voltage bus of the electromagnetic transient (EMT) representation of a variant of the IEEE 9 bus test system, which has been modified to consider an operating condition with 52% of the total supply provided by wind power generation. The selected and programmed FAPR strategies are applied to the DUT, with the ultimate goal of ascertaining its feasibility and effectiveness with respect to the pure software-based EMT representation performed in real time. Particularly, the time-varying response of the active power injection by each FAPR control strategy and the impact on the instantaneous frequency excursions occurring in the frequency containment periods are analyzed. The performed tests show the degree of improvements on both the rate-of-change-of-frequency (RoCoF) and the maximum frequency excursion (e.g., nadir).

scholarly journals Learning Feedforward Control Using Multiagent Control Approach for Motion Control Systems

Energies ◽  
2021 ◽  
Vol 14 (2) ◽  
pp. 420
Author(s):  
Phong B. Dao
Keyword(s):  
Real Time ◽  
Feedforward Control ◽  
Design Method ◽  
Mechatronic Systems ◽  
Control Approach ◽  
Runtime Environment ◽  
Multiagent Control ◽  
On Line ◽  
Promising Solution ◽  
Function Approximator

Multiagent control system (MACS) has become a promising solution for solving complex control problems. Using the advantages of MACS-based design approaches, a novel solution for advanced control of mechatronic systems has been developed in this paper. The study has aimed at integrating learning control into MACS. Specifically, learning feedforward control (LFFC) is implemented as a pattern for incorporation in MACS. The major novelty of this work is that the feedback control part is realized in a real-time periodic MACS, while the LFFC algorithm is done on-line, asynchronously, and in a separate non-real-time aperiodic MACS. As a result, a MACS-based LFFC design method has been developed. A second-order B-spline neural network (BSN) is used as a function approximator for LFFC whose input-output mapping can be adapted during control and is intended to become equal to the inverse model of the plant. To provide real-time features for the MACS-based LFFC system, the open robot control software (OROCOS) has been employed as development and runtime environment. A case study using a simulated linear motor in the presence of nonlinear cogging and friction force as well as mass variations is used to illustrate the proposed method. A MACS-based LFFC system has been designed and implemented for the simulated plant. The system consists of a setpoint generator, a feedback controller, and a time-index LFFC that can learn on-line. Simulation results have demonstrated the applicability of the design method.

scholarly journals DOLARS, a Distributed On-Line Activity Recognition System by Means of Heterogeneous Sensors in Real-Life Deployments—A Case Study in the Smart Lab of The University of Almería

Sensors ◽  
2021 ◽  
Vol 21 (2) ◽  
pp. 405
Author(s):  
Marcos Lupión ◽  
Javier Medina-Quero ◽  
Juan F. Sanjuan ◽  
Pilar M. Ortigosa
Keyword(s):  
Real Time ◽  
Activity Recognition ◽  
Real Life ◽  
Recognition System ◽  
Machine Learning Algorithms ◽  
Sensor Data ◽  
Heterogeneous Sensors ◽  
On Line ◽  
The University

Activity Recognition (AR) is an active research topic focused on detecting human actions and behaviours in smart environments. In this work, we present the on-line activity recognition platform DOLARS (Distributed On-line Activity Recognition System) where data from heterogeneous sensors are evaluated in real time, including binary, wearable and location sensors. Different descriptors and metrics from the heterogeneous sensor data are integrated in a common feature vector whose extraction is developed by a sliding window approach under real-time conditions. DOLARS provides a distributed architecture where: (i) stages for processing data in AR are deployed in distributed nodes, (ii) temporal cache modules compute metrics which aggregate sensor data for computing feature vectors in an efficient way; (iii) publish-subscribe models are integrated both to spread data from sensors and orchestrate the nodes (communication and replication) for computing AR and (iv) machine learning algorithms are used to classify and recognize the activities. A successful case study of daily activities recognition developed in the Smart Lab of The University of Almería (UAL) is presented in this paper. Results present an encouraging performance in recognition of sequences of activities and show the need for distributed architectures to achieve real time recognition.

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