In this paper we propose a novel distributed algorithm to solve degenerate linear programs on asynchronous networks. Namely, we propose a distributed version of the well known simplex algorithm. We prove its convergen...
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An algorithmic framework is developed for automatic deployment of car-like robots based on Linear Temporal Logic (LTL) formulae over a set of regions of interest in the environment. The environment and the regions of ...
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An algorithmic framework is developed for automatic deployment of car-like robots based on Linear Temporal Logic (LTL) formulae over a set of regions of interest in the environment. The environment and the regions of interest are a priori known, and the robot has non-negligible size and restricted steering capabilities. The approach relies on constructing a probabilistic finite-state abstraction of the car-like robot and on finding a trajectory (run) in this abstraction such that the probability of satisfying the LTL formula is maximized. The feasibility of our approach is supported by simulations under Matlab environment.
The article presents thermal analysis of three-phase induction motor using coupled circuit models. The MATLAB/SIMULINK environment and PLECS toolbox were used to create mathematical model of the examined motor. Coeffi...
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The article presents thermal analysis of three-phase induction motor using coupled circuit models. The MATLAB/SIMULINK environment and PLECS toolbox were used to create mathematical model of the examined motor. Coefficient of heat transfer through the winding was set experimentally. Results of calculations presented are verified by the measurements on the physical motor.
Motivated by the distributed control of fleets of identical linear subsystems, we consider the stability of block upper-triangular switched linear systems with switching delay, when switching between stable modes. Pro...
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Geometric fault detection and isolation filters are known for having excellent fault isolation properties. However, they are generally assumed to be sensitive to model uncertainty and noise. This paper proposes a robu...
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Abstract This paper introduces a method for synthesizing reduced-order nonlinear model-based predictive controllers that have support in an arbitrary open subset, for semilinear parabolic equations. The predictive con...
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Abstract This paper introduces a method for synthesizing reduced-order nonlinear model-based predictive controllers that have support in an arbitrary open subset, for semilinear parabolic equations. The predictive control law is computed based on reduced-order, nonlinear multi-step-ahead finite-element predictors, identified directly from experimental input-output data. An advantage of this approach is that it does not require knowledge of the partial differential equation (PDE) model of the process. The proposed approach is computationally efficient and suitable for real-time implementation as it does not involve solving a complex nonlinear programming problem. The design method can deal effectively with load disturbances and noise in a similar manner to that adopted in the classical Generalized Predictive control framework. The method is used to design and evaluate numerically a nonlinear predictive controller for a one-dimensional nonlinear parabolic equation.
In this paper a visual self-localization method for a humanoid robot is presented. This one is based on monocular information. The goal of this method is to obtain the position (x; y) and orientation θ of the humanoi...
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In this paper a visual self-localization method for a humanoid robot is presented. This one is based on monocular information. The goal of this method is to obtain the position (x; y) and orientation θ of the humanoid robot inside the field of play. The methods proposed include some digital image processing algorithms and geometric interpretation to perform a 3D monocular reconstruction, that allows to measure the relative position between the robot and some known objects (goals and beacons), and to use them to obtain the robot's absolute position, by means of a triangulation method. Finally, the results obtained in Webots and in the real platform are presented.
Abstract Multi-objective optimisation is a challenging and essential topic of both engineering and computation fields. Population-based approaches are able to achieve a set of solutions as an approximation to the Pare...
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Abstract Multi-objective optimisation is a challenging and essential topic of both engineering and computation fields. Population-based approaches are able to achieve a set of solutions as an approximation to the Pareto front and have therefore become popular. However, these algorithms have to use a significant number of evaluations to reach convergence, which can be time-consuming and/or economically expensive as far as real-world applications are concerned. Recently, an efficient hybrid framework, named EMO-FL, which combines a state-of-the-art multi-objective optimiser with an embedded approximate model of the objective functions, has been proposed to handle such problems. In this paper, a new multi-objective optimiser (DBSGA) is developed and successfully exploited to enhance the performance of this EMO-FL framework. Successful applications of the newly proposed algorithm include well-known challenging benchmark functions and the optimal design of alloy steels via the manipulation of chemical equations and processing conditions.
Abstract This work purposes using a 3D PMD camera as a sensor for mobile robot applications. The use of image sensors for environment detection is substantial and common usage in mobile robot exploration. Laser scanne...
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Abstract This work purposes using a 3D PMD camera as a sensor for mobile robot applications. The use of image sensors for environment detection is substantial and common usage in mobile robot exploration. Laser scanners, 3D stereo vision or a combination of them are be used generally. The PMD camera is a novel 3D measuring system, which is based on a time-of-flight principle. The main feature is an array sensor, which can measure the distance to the target without scanning. This relatively new technology offers a cost-effective alternative to the mentioned sensors. In the following we present methods for self-localization and 3D map building by remote sensor data acquisition. This allows the teleoperative control of a mobile robot in an unknown environment. To enhance the mobile robot tasks, a CCD and the PMD camera are registered in order to create the three dimensional mapping. The CCD texture data will be overlaid with the PMD depth data to increase the accuracy of the lateral resolution. The visual input from the CCD camera not only delivers high resolution texture data, it can also apply for object recognition in clutter environment.
This paper highlights the differences between a simple sensorless method and an adaptive flux and speed observer for a five-phase induction motor control. The drive is controlled using space vector modulation direct t...
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ISBN:
(纸本)9781467303408;9781467303422
This paper highlights the differences between a simple sensorless method and an adaptive flux and speed observer for a five-phase induction motor control. The drive is controlled using space vector modulation direct torque control (DTC- SVM) approach. The power measurement used for speed computation is simple, with a minimum processor time and memory, and relatively robust against parameters variation when compared with the adaptive observer based approach. Simulation verification and real time implementation are presented in the paper.
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