This paper investigates real-time scheduling algorithms on upcoming multithreaded processors. As evaluation testbed we introduce a multithreaded processor kernel which is specifically designed as core processor of a m...
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This paper investigates real-time scheduling algorithms on upcoming multithreaded processors. As evaluation testbed we introduce a multithreaded processor kernel which is specifically designed as core processor of a micro-controller or system-on-a-chip. Handling of external real-time events is performed through multithreading. Real-time threads are used as interrupt service threads (ISTs) instead of interrupt service routines (ISRs). Our proposed micro-controller supports multiple ISTs with zero-cycle context switching overhead. We investigate the behavior of fixed priority preemptive, earliest deadline first, least laxity first and guaranteed percentage scheduling with respect to multithreaded processors. Our finding is that the strategies GP and LLF result in a good blending of instructions of different threads thus enabling a multithreaded processor to utilize latencies best. Assuming a zero-cycle context switch LLF performs best, however implementation cost context, are prohibitive.
This paper presents a formulation for a class of robust fault detection problems, and its corresponding solution approach. In order to provide insight into the robust algorithm, one needs to consider the past and unde...
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This paper presents a formulation for a class of robust fault detection problems, and its corresponding solution approach. In order to provide insight into the robust algorithm, one needs to consider the past and understand its historical origins in optimal fault detection, where it is assumed that both plant and noise models are accurate. The deleterious effect of plant model uncertainties on the performance of the optimal tests is illustrated, thus motivating the idea of robust fault detection, which makes use of robust game theoretic ( H ∞ ) or risk sensitive estimators. These estimators provide test residuals or statistics that are insensitive to uncertainties, but still sensitive to failure modes. The paper concludes by motivating and suggesting new ideas for future research.
Combining position and force control is highly desirable in many robot applications. Many years of extensive research has resulted in a number of promising control approaches, but often too much engineering effort is ...
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Combining position and force control is highly desirable in many robot applications. Many years of extensive research has resulted in a number of promising control approaches, but often too much engineering effort is required in order to evaluate a low level (high performance) control scheme on a real manipulator. The new control system we have obtained has two main advantages: first it provides a total open control architecture, and second it is the simplicity and the interactivity of the platform developed. Using this new control architecture, any force and motion control strategy can be programmed and implemented in a graphical and easy way.
Decomposing dynamical systems in terms of orthogonal expansions enables the modelling/approximation of a system with a finite length expansion. By flexibly tuning the basis functions to underlying system characteristi...
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Decomposing dynamical systems in terms of orthogonal expansions enables the modelling/approximation of a system with a finite length expansion. By flexibly tuning the basis functions to underlying system characteristics, the rate of convergence of these expansions can be drastically increased, leading to highly accurate models (small bias) being represented by few parameters (small variance). Additionally algorithmic and numerical aspects are favourable. A recently developed general theory for basis construction will be presented, that is a generalization of the classical Laguerre theory. The basis functions are applied in problems of identification, approximation, realization, uncertainty modelling, and adaptive filtering, particularly exploiting the property that basis function models are linearly parametrized. Besides powerful algorithms, they also provide useful analysis tools for understanding the underlying identification/approximation algorithms.
Robotic soccer is an interesting test bench for the field of self-organizing and cooperating multi-agent systems. This paper deals with learning of two basic low-level behaviors that will enable the robotic player to ...
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Robotic soccer is an interesting test bench for the field of self-organizing and cooperating multi-agent systems. This paper deals with learning of two basic low-level behaviors that will enable the robotic player to participate further in higher-level collaborative and adversarial learning situations. First, a ball interception and obstacle avoidance behavior is learned. Then the acquired skills are incorporated into a next higher-level multi-agent learning scenario, namely the shooting ball behavior. The proposed control scheme for these behaviors consists of a trajectory generator with a layered structure, which supplies data to a trajectory-tracking controller.
This paper proposes a genetic-based algorithm for surface reconstruction of three-dimension (3-D) objects from a group of contours representing its section plane lines. The algorithm can optimize the triangulation of ...
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This paper proposes a genetic-based algorithm for surface reconstruction of three-dimension (3-D) objects from a group of contours representing its section plane lines. The algorithm can optimize the triangulation of the surface of 3-D objects with a multi-objective optimization function to meet the needs of a wide range of applications. Further, a new crossover operator for triangulation and a new 3-D quadrilateral mutation operator are also introduced.
The main motivation of the presented work is to realise a prototype of the CAD tool that supports the whole life cycle of the diagnostic system development process. In the proposed approach, the fault trees are automa...
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The effect of the type and quality of process models applied for fault detection and isolation is investigated in this paper. It is shown that the level of details and the modelled processes within the applied grey bo...
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The specification process for advanced industrial process control systems should be conducted by means of a methodology that takes into consideration the specification of control functions and the system architecture....
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The specification process for advanced industrial process control systems should be conducted by means of a methodology that takes into consideration the specification of control functions and the system architecture. For the domain of industrial process control by PLCs, we have implemented the automation of the specification process within a pragmatic low-cost and easy to use CASE environment, comprising commercial computer tools extended by a dedicated software. Such an environment makes possible domain-oriented non-redundant data entry, automatic data expansion and transfer into the CASE tool repository, and remains an advantage of CASE tool generic functions.
A fault detection and isolation scheme for a brushless DC motor driving a mechanical actuation system is presented. First, a detailed mathematical model of the drive is derived. The residual generator is based on pari...
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A fault detection and isolation scheme for a brushless DC motor driving a mechanical actuation system is presented. First, a detailed mathematical model of the drive is derived. The residual generator is based on parity relations while the fault isolation part is implemented by means of the transferable belief model. The problem of distinguishing between faults with the same fault signatures is addressed. It is shown that additional improvements in terms of resolution can be achieved by employing parameter estimation. The proposed FDI scheme is tested on the actual drive under various faults. The achieved performance features the highest resolution, diagnostic stability and accuracy.
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