Real time implementation

Automatic control applications are real-time systems which pose stringent requirements on precisely time-triggered synchronized actions and constant end-to-end delays in feedback loops which often constitute multi-rate systems. Motivated by the apparent gap between computer science and automatic control theory, a set of requirements for real-time implementation of control applications is given. A real-time behavioral model for control applications is then presented and exemplified. Important sources and characteristics of time-variations in distributed computer systems are investigated. This illuminates key execution strategies to ensure the required timing behavior. Implications on design and implementation and directions for further work are discussed.

Teleconferencing systems employ acoustic echo cancelers to reduce echoes that results from the coupling between loudspeaker and microphone. To enhance the sound realism, two-channel audio is necessary. However, stereophonic acoustic echo cancellation is more difficult to solve because of the necessity to uniquely identify two acoustic paths, which becomes problematic since the two excitation signals are highly correlated. In this paper an implementation of a stereophonic acoustic echo canceler on a parallel DSP board is presented.

The design and optimization of modern radio communication systems requires realistic models of the radio propagation channel. Especially for the test of mobile radio hardware devices, real-time implementations of such channel models are needed. Geometry based channel models are computationally intensive, since for every propagation path, every time instance and every delay or frequency bin a complex exponential has to be evaluated. On a real-time hardware channel emulator, like the ARC SmartSim, the number of paths P , that can be simulated, is limited by the available processing power. In this paper, a new method is introduced, that allows both to increase the number of paths P and to reduce the overall computational complexity.

Abstract-This paper presents a transform coding algorithm devoted to high quality audio coding at a bit rate of 64 kbps per monophonic channel. It enables the transmission of a high quality stereo sound through the basic access (2B channels) of ISDN. Although a complete ...

The problem of developing local reactive obstacle-avoidance behaviors by a mobile robot through online real-time learning is considered. The robot operated in an unknown bounded 2-D environment populated by static or moving obstacles (with slow speeds) of arbitrary shape. The sensory perception was based on a laser range finder. A learning-based approach to the problem is presented. To greatly reduce the number of training samples needed, an attentional mechanism was used. An efficient, real-time implementation of the approach was tested, demonstrating smooth obstacle-avoidance behaviors in a corridor with a crowd of moving students as well as static obstacles.

In this papev, we propose novel techniques for the implementation of MPEGIAudio (Layer I1 and Layer I l l) encoder: The proposed techniques concern implementing the encoder with a minimum complexity. As an effort to minimize the complexity, the I S 0 psycho-acoustic model (PAM) is simplified that often demands significant computational power of the implementation system. The simplification follows the statistical behavior of the PAM. A fast bit allocation algorithm is also developed, in which the quantizer step size is updated dynamically and adaptively according to input signal statistics. The performance of the developed techniques is verified via subjective tests as well as statistical analyses. Real-time implementations are tried for MEPG/Audio Layer I1 and Layer I l l encoders employing the proposed algorithms. The implemented systems show that the developed encoders can be as simple as decoders, but still produce bitstreams of high audio quality.

In this paper, we present a technique for using an additional parallel neural network to provide adaptive enhancements to a basic fixed neural network-based nonlinear control system. This proposed parallel adaptive neural network control system is applicable to nonlinear dynamical systems of the type commonly encountered in many practical position control servomechanisms. Properties of the controller are discussed, and it is shown that if Gaussian radial basis function networks are used for the additional parallel neural network, uniformly stable adaptation is assured and the approximation error converges to zero asymptotically. In the paper, the effectiveness of the proposed parallel adaptive neural network control system is demonstrated in real-time implementation experiments for position control in a servomechanism with asymmetrical loading and changes in the load.

Spectrally tunable quantum-dot infrared photodetectors (QDIPs) can be used to approximate multiple spectral responses with the same focal-plane array. Hence, they exhibit the potential for real time adaptive detection/classification. In the present study, it is shown that we can perform the detection/classification operation at the adaptive focal-plane array (AFPA) based on QDIPs by fitting the QDIP's response to the correspondent operators. With a new understanding of spectral signature in the sensor space, the best fitting can be achieved. Our simulation results show how well QDIPs perform in different regions of the spectrum in the mid-and long wave infrared. The results indicate that the AFPA performance does not match that of the ideal filtering operators, but reliable measurement can be accomplished.

Particle image velocimetry (PIV) allows measuring distributed flow velocity fields. It is well established as an experimental tool in modern fluid dynamics research, being applied to liquid, gases and multiphase flows. Images of tracer particles are processed by means of a statistical strategy, which makes its real-time implementation difficult to achieve. In this paper, we describe the design and implementation of an embedded architecture for real-time PIV based on FPGA technology. The proposed scheme has allowed us to exploit the lowlevel parallelization in both, the direct cross-correlation computation and interrogation windows handling. We propose a bus architecture to manage multiple interfaces among the processing modules and external devices. By using this scheme, we achieved design flexibility and improved processing speed. Major benefits of the speed improvement are enhanced experimental capabilities like feedback control, on-line flow regimen visualization, and a significant speed up in off-line processing. We show experimental results of a physical field of velocities calculated in real-time.

Hak cipta terpelihara. Tiada dibenarkan mengeluar ulang mana-mana bahagian artikel, ilustrasi, dan isi kandungan buku ini dalam apa juga bentuk dan cara apa jua sama ada dengan cara elektronik, fotokopi, mekanik, atau cara lain sebelum mendapat izin bertulis daripada Timbalan Naib Canselor (Penyelidikan dan Inovasi), Universiti Teknologi Malaysia, 81310 Skudai, Johor Darul Ta'zim, Malaysia. Perundingan tertakluk kepada perkiraan royalti atau honorarium.

From copyright protection to error concealment, video data hiding has found usage in a great number of applications. Recently proposed applications such as privacy data preservation require huge amount of information to be hidden inside a compressed video bitstream. Since data hiding disturbs the underlying statistical patterns of the source data, it adversely affects the performance of compression which are designed based on the statistical properties of the data. As such, it is imperative to design a data hiding scheme that is compatible with the compression algorithm and at the same time, introduces as little perceptual distortion as possible. In this paper, we propose a novel compression-domain video data-hiding algorithm that determines the optimal embedding strategy to minimize both the output perceptual distortion and the output bit rate. The hidden data is embedded into selective Discrete Cosine Transform (DCT) coefficients which are found in most video compression standards. The coefficients are selected based on minimizing a cost function that combines both distortion and bit rate via a usercontrolled weighting. Two methods are proposed-exhaustive search and fast Lagrangian approximation. While the former produces optimal results, the latter approach is significantly faster and amenable to real-time implementation.

Increasing needs for optimized designs and for handling the dependencies among control systems and their real-time implementation, cause a resulting need for tools that have the abilities to support design across these traditional discipline boundaries. Tools supporting such co-design provide new opportunities in developing cost-efficient, dependable and robust solutions where the interactions between control and implementation engineers can be improved, and where further possibilities are obtained by increasing the information flow between the control system and the hardware/software platform during run-time. Work on codesign has the important effect to stimulate new theoretical research directions where more work is needed because of the lack of theory and methods in the field. Co-design related to embedded control system is a fairly new area and most of the methods and theory developed so far are aimed at analysis rather than synthesis. A further great challenge is that of model and tool integration, where there are needs to coordinate and integrate the multitude of aspects and specialized models/tools that are used in the development of embedded control systems. This survey sets the context of embedded control systems development describing what is achievable with current generation industrial tools. The context is further elaborated by discussing categories of tools from different related research disciplines. A set of representative co-design tools are then described in depth and discussed.

The recent extensive application of permanent magnet synchronous motors (PMSM) in industry has been stimulated by the worldwide energy-saving mission. In this study, the assessment of the dynamic performance of a traditional cascaded PI field oriented motion control of a PMSM drive system is presented in both simulation and a real time implementation of the control strategy. The tuning of the cascaded position, velocity, and current controllers was carried out experimentally and the results demonstrated the feasibility and effectiveness of the used control scheme for velocity and position loops. Finally, the motion command tracking performance of the cascaded PI field oriented control algorithm of SMPM system was found satisfactory.

This paper is concerned with the numerical optimization of the Fuzzy Logic Controller (FLC) for both its efficient simulation and easy real-time implementation. The basic concept of the FLC based o n generalized T-operators approach has been presented. Several assumptions regarding the mathematical formalization of the FL,C have been made leading to its numerical simplification. They include: Goguen formulas for Toperators, "Center of Gravity" method for defuzzification and the overlapping between not more than two membership functions for the controllers fuzzy output. Under these assumptions, the paper presents the FLC nom-fuzzy output as the ratio of two weighted sums of certain functions of the inputs reducing the computational burden of the PLC algorithm at least few tens times comparing with the definition-based approach. The Fuzzy Logic Power System Stabilizer (PSS) has been chosen as an application example. Results of simulation studies demonstrate the efficiency of both the presented optimization method i n terms of numerical simplicity and the designed PSS i n terms of improving the power system stability.

The correction of angular misalignment between mating components is a fundamental requirement for their successful assembly. In this paper we present how a learning agent based on the Stochastic Gradient Ascent (SGA) algorithm can be used to command appropriate rotations of a robotic manipulator's hand in order to minimise such misalignments and allow the completion of a peg in hole task. The learning capabilities of the proposed methodology are proven both with simulation and real time implementation using a PUMA 6 DOF industrial manipulator.

The performance of the estimator used in the tracking of a fading channel plays an essential role in many wireless receivers. The conventional Kalman filter is an optimum estimator; however, it is computationally demanding and complex for realtime implementation. In this paper a new approach is proposed for the implementation of the Kalman filter based on differential channel states. This leads to a robust differential Kalman filtering algorithm that can be simplified further to ease the implementation without any major loss in performance. It is also shown that the simplifications made to the differential Kalman filter lead to the Least Mean Squares (LMS) algorithm, identifying it as a special case of the Kalman filter.