Variable Stiffness Actuators (VSA) are currently being regarded as promising actuator types in robotics research especially due to their capability to store potential energy in their elastic elements and to control th...
Variable Stiffness Actuators (VSA) are currently being regarded as promising actuator types in robotics research especially due to their capability to store potential energy in their elastic elements and to control this energy by altering the elastic properties of these elements. The controllable potential energy enables these actuators to outperform their rigid counterparts especially when realizing fast explosive motions. Most of joint designs with VSA's, however, are described by nonlinear deflection-torque relations and consequently a thorough analysis regarding their maximum attainable performance is difficult. In this work, we tackle this problem by using Pontryagin's Minimum Principle and develop a general method to solve the optimal control problem of minimizing any given terminal cost for these joints. In other words, we show the optimal control strategies to alter VSA's elastic properties for various tasks such as maximization of the final link velocity or time-optimal tracking, which are all found to depend on the change of the system's potential and kinetic energy relative to its total energy. The application of the method is illustrated for VSA's with adjustable linear and cubic springs, where the potential energy stored in the springs is maximized at a given final time.
In the present study, the finite-time asynchronous dissipative filter design problem for the Markov jump systems with conic-type nonlinearity is studied. The hidden Markov model can describe the asynchronism embodied ...
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In the present study, the finite-time asynchronous dissipative filter design problem for the Markov jump systems with conic-type nonlinearity is studied. The hidden Markov model can describe the asynchronism embodied in the system modes and the filter modes reasonably. Moreover, a suitable LyapunovKrasovskii function is utilized and linear matrix inequalities are applied to obtain adequate conditions. These techniques guarantee the finite-time boundedness and strict dissipativity of the filtering error dynamic system. Furthermore, the design problems of the passive filter and the H∞ filter are studied by adjusting the three parameters U, G and V. Finally, the filter gains and the optimal index α*are obtained and the correctness and feasibility of the designed approach are verified by a simulation example.
作者:
Dabrowski, AdamPoznań University of Technology
Faculty of Control Robotics and Electrical Engineering Institute of Automatic Control and Robotics Division of Signal Processing and Electronic Systems Jana Pawla II 24 Poznań60-965 Poland
In this tutorial some basic linear algebra problems: basis change and projection, are discussed together with examples of their applications in signal and image processing. In typical linear algebra university courses...
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The paper presents an analysis of the realization of digital signal processing algorithms with the use of STM32F4 microcontrollers. Various programming techniques have been demonstrated focusing on the implementation ...
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The method of fault isolation in large scale industrial processes is considered. The paper introduces description of the diagnosed object in form of an information system. The proposed algorithm takes into account the...
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The method of fault isolation in large scale industrial processes is considered. The paper introduces description of the diagnosed object in form of an information system. The proposed algorithm takes into account the dynamics of the symptoms. The result of such approach is augmentation of fault discernment and speed of fault isolation.
We propose a method capable of acquiring an occupancy grid map-based representation of the local, static driving environment around an intelligent vehicle in the presence of dynamic objects. These corrupt the represen...
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We propose a method capable of acquiring an occupancy grid map-based representation of the local, static driving environment around an intelligent vehicle in the presence of dynamic objects. These corrupt the representation due to violating the underlying static-world assumptions of common grid mapping algorithms and are therefore detected and filtered from the map. For this purpose, a subsequent step is suggested that identifies, clusters and merges dynamic cell hypothesis in a novel way. Thereafter, an Interacting-Multiple-Model-Unscented-Kalman-Probabilistic-Data-Association (IMM-UK-PDA) tracker is used to classify of whether cell movements behave consistently with possible movement characteristics of real dynamic objects or are just generated by noise or newly observed static environment. In opposition to many other approaches, the method explicitly combines information of newly occupied and free areas, completes the shape of only partly visible dynamic objects and uses an advanced object tracking scheme to clean the grid from dynamic object corruptions. The method is evaluated with grids generated by an automotive radar and stereo camera in real traffic environments.
This paper investigates enhancing the ability to detect cyber-attacks by using information and methods related to fault detection. An experimental stand, and an associated simulator have been constructed to enable tes...
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This paper investigates enhancing the ability to detect cyber-attacks by using information and methods related to fault detection. An experimental stand, and an associated simulator have been constructed to enable tests of combined cyber attacks and faults in industrial processes, and, possibly, to distinguish between them. Some scenarios of cyber attacks have been presented, analysed theoretically and then tested on the simulator, demonstrating that detection of cyber attacks by this method is possible.
In the paper the investigation of chosen fault detection method based on neural network models for industrial applications is presented. The investigation was done based on the real data acquired from first stage of e...
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In the paper the investigation of chosen fault detection method based on neural network models for industrial applications is presented. The investigation was done based on the real data acquired from first stage of evaporation station of sugar factory. The non-linear perceptron MA-type models and perceptron ARMA-type models were examined. The only three-layer perceptron networks were investigated. It was shown that MA models have better fault detection performance compared to ARMA models.
We propose a new method for free space detection and description for Advanced Driver Assistance Systems (ADAS) and autonomous vehicles. The detection is based on successive morphological image processing steps that ar...
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We propose a new method for free space detection and description for Advanced Driver Assistance Systems (ADAS) and autonomous vehicles. The detection is based on successive morphological image processing steps that are applied to an occupancy grid map-based environment representation acquired by an automotive radar sensor. The boundary of the found free space segment is traced and serves as a virtual measurement for a time-variant Kalman Filter in order to estimate and track the control points of a two-dimensional B-spline closed free space contour over time. In contrast to existing free space detection methods, the proposed solution incorporates knowledge about the vehicle's dimensions and does not exclude free space that is not directly in the line of sight, but mapped beforehand, as well as free space behind obstacles. Furthermore, the algorithm shows advantages in terms of an intuitive control over spatial and temporal smoothness of the solution as well as an inherent robustness due to model-based filtering. Moreover, the control points of the B-spline curve are proposed as a new low-dimensional representation of drivable free space of arbitrary shape. The effectiveness of the algorithm is demonstrated in real traffic scenarios.
Two-string inference systems produce output values from activations of recommending rules, as in standard fuzzy inference systems, but also with respect to inhibitions or warnings produced by negative rules. Besides a...
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ISBN:
(纸本)9781479938414
Two-string inference systems produce output values from activations of recommending rules, as in standard fuzzy inference systems, but also with respect to inhibitions or warnings produced by negative rules. Besides assuring that a forbidden output value must not occur, the crucial point with two-string inference is how the inference results from positive and negative rules can be combined to a single output membership function by which an output value can be calculated. In this paper, a new method for combining the output membership functions of both inference strings to a combined output membership function by means of fuzzy rule-based metainference is proposed. This method generalizes existing methods and additionally provides means to adjust or combine them in a transparent way. Moreover, the possibility of designing new context-dependent or -independent metainference patterns increases flexibility and applicability of two-string fuzzy inference.
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