Preface to the special section on algorithms and architectures for real-time control

Rapid developments in microelectronics and computer science continue to fuel new opportunities for real-time control engineers. The ever-increasing system complexity and sophistication, environmental legislation, economic competition, safety and reliability constitute some of the driving forces for the research themes presented at the IFAC Workshop on Algorithms and Architectures for Real-Time Control (AARTC'2000). The Spanish Society for Automatic Control hosted AARTC'2000, which was held at Palma de Maiorca, Spain, from 15 to 17 May. This workshop was the sixth in the series.

Algorithms and architectures for real-time control

Algorithm and Architectures for Real-Time Control Workshop had the objective to investigate the state of the art and to present new research and application results in software and hardware for real-timecontrol, as well as to bring together engeneers and computer scientists who are researchers, developers and practitioners, both from the academic and the industrial world.

Radio over fiber broadband access networks architectures based on wavelength division multiplexing techniques

The recent remarkable growth in bandwidth of both wired optical and wireless access networks supports a burst of new high bandwidth Internet applications such as: peer-topeer file sharing, cloud storage, on-line gaming, video streaming, etc. Within this scenario, the convergence of fixed and wireless access networks offers significant opportunities for network operators to satisfy user demands, and simultaneously reduce the cost of implementing and running separated wireless and wired networks. The integration of wired and wireless network can be accomplished within several scenarios and at several levels. In this thesis we will focus on converged radio over fiber architectures, particularly on two application scenarios: converged optical 60 GHz wireless networks and wireless overlay backhauling over bidirectional colorless wavelength division multiplexing passive optical networks (WDM-PONs). In the first application scenario, optical 60 GHz signal generation using external modulation of an optical carrier by means of lithium niobate (LiNbO3) Mach- Zehnder modulators (MZM) is considered. The performance of different optical modulation techniques, robust against fiber dispersion is assessed and dispersion mitigation strategies are identified. The study is extended to 60 GHz carriers digitally modulated with data and to systems employing subcarrier multiplexed (SCM) mm-wave channels. In the second application scenario, the performance of WDM-PONs employing reflective semiconductor optical amplifiers (RSOAs), transmitting an overlay orthogonal frequency-division multiplexing (OFDM) wireless signal is assessed analytically and experimentally, with the relevant system impairments being identified. It is demonstrated that the intermodulation due to the beating of the baseband signal and wireless signal at the receiver can seriously impair the wireless channel. Performance degradation of the wireless channel caused by the RSOA gain modulation owing to the downstream baseband data is also assessed, and system design guidelines are provided.

Open source data sensing software for ultrasonic non-invasive temperature estimation

In this paper, an open source solution for measurement of temperature and ultrasonic signals (RF-lines) is proposed. This software is an alternative to the expensive commercial data acquisition software, enabling the user to tune applications to particular acquisition architectures. The collected ultrasonic and temperature signals were used for non-invasive temperature estimation using neural networks. The existence of precise temperature estimators is an essential point aiming at the secure and effective applica tion of thermal therapies in humans. If such estimators exist then effective controllers could be developed for the therapeutic instrumentation. In previous works the time-shift between RF-lines echoes were extracted, and used for creation of neural networks estimators. The obtained estimators successfully represent the temperature in the time-space domain, achieving a maximum absolute error inferior to the threshold value defined for hyperthermia/diathermia applications.

Automatic parallelization of matricial algorithms

The introduction of parallel processing architectures allowed the real time impelemtation of more sophisticated control algorithms with tighter specifications in terms of sampling time. However, to take advantage of the processing power of these architectures the control engeneer, due to the lack of appropriate tools, must spend a considerable amount of time in the parallelizaton of the control algorithm.

Adaptive generalized predictive control algorithm implemented over an heterogeneous parallel architecture

In this paper a parallel implementation of an Adaprtive Generalized Predictive Control (AGPC) algorithm is presented. Since the AGPC algorithm needs to be fed with knowledge of the plant transfer function, the parallelization of a standard Recursive Least Squares (RLS) estimator and a GPC predictor is discussed here.

Implementation of an daptive generalized predictive control algorithm over an heterogeneous parallel architecture

In this paper a parallel implementation of an Adaprtive Generalized Predictive Control (AGPC) algorithm is presented. Since the AGPC algorithm needs to be fed with knowledge of the plant transfer function, the parallelization of a standard Recursive Least Squares (RLS) estimator and a GPC predictor is discussed here.

Neural network assisted autotuning of industrial PID controllers

A recent servey (1) has reported that the majority of industrial loops are controlled by PID-type controllers and many of the PID controllers in operation are poorly tuned. poor PID tuning is due to the lack of a simple and practical tuning method for avarage users, and due to the tedious procedurs involved in the tuning and retuning of PID controllers.

Real-time parameter estimation of dynamic temperature models for greenhouse environmental control

For a greenhouse located at UTAD-University, the methods used to estimate in real-time the parameters of the inside air temperature model will be described. The structure and the parameters of the climate discrete-time dynamic model were previously identified using data acquired during two different periods of the year.

A neural network controller

Proportional, Integral and Derivative (PID) regulators are standard building blocks for industrial automation. The popularity of these regulators comes from their rebust performance in a wide range of operating conditions, and also from their functional simplicity, which makes them suitable for manual tuning.

Numerical techniques for modeling Doppler ultrasound spectra systems

Evaluation of blood-flow Doppler ultrasound spectral content is currently performed on clinical diagnosis. Since mean frequency and bandwidth spectral parameters are determinants on the quantification of stenotic degree, more precise estimators than the conventional Fourier transform should be seek. This paper summarizes studies led by the author in this field, as well as the strategies used to implement the methods in real-time. Regarding stationary and nonstationary characteristics of the blood-flow signal, different models were assessed. When autoregressive and autoregressive moving average models were compared with the traditional Fourier based methods in terms of their statistical performance while estimating both spectral parameters, the Modified Covariance model was identified by the cost/benefit criterion as the estimator presenting better performance. The performance of three time-frequency distributions and the Short Time Fourier Transform was also compared. The Choi-Williams distribution proved to be more accurate than the other methods. The identified spectral estimators were developed and optimized using high performance techniques. Homogeneous and heterogeneous architectures supporting multiple instruction multiple data parallel processing were essayed. Results obtained proved that real-time implementation of the blood-flow estimators is feasible, enhancing the usage of more complex spectral models on other ultrasonic systems.

Peer-to-peer video streaming

The Internet as a video distribution medium has seen a tremendous growth in recent years. Currently, the transmission of major live events and TV channels over the Internet can easily reach hundreds or millions of users trying to receive the same content using very distinct receiver terminals, placing both scalability and heterogeneity challenges to content and network providers. In private and well-managed Internet Protocol (IP) networks these types of distributions are supported by specially designed architectures, complemented with IP Multicast protocols and Quality of Service (QoS) solutions. However, the Best-Effort and Unicast nature of the Internet requires the introduction of a new set of protocols and related architectures to support the distribution of these contents. In the field of file and non-real time content distributions this has led to the creation and development of several Peer-to-Peer protocols that have experienced great success in recent years. This chapter presents the current research and developments in Peer-to-Peer video streaming over the Internet. A special focus is made on peer protocols, associated architectures and video coding techniques. The authors also review and describe current Peer-to-Peer streaming solutions. © 2013, IGI Global.