This paper considers the synchronization problem of multi-agent SISO systems with general unidirectional communication structures. A distributed control strategy is presented which relies on relative output difference...
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This paper considers the synchronization problem of multi-agent SISO systems with general unidirectional communication structures. A distributed control strategy is presented which relies on relative output differences of neighboring agents and, thus, does not need relative state information. We propose a root locus design method to determine the synchronization gain. Since in directed networks the characteristic equation for synchronization might be complex valued, we use tools from the complex root locus technique to solve the synchronization task.
While collision detection and contact-related injury reduction in physical human-robot interaction has been studied intensively, safety issues in physical human-robot collaboration (pHRC) with continuous coupling of h...
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ISBN:
(纸本)9781467380270
While collision detection and contact-related injury reduction in physical human-robot interaction has been studied intensively, safety issues in physical human-robot collaboration (pHRC) with continuous coupling of human and robot(s) has received little attention so far. We develop an energy monitoring control system that observes energy flows among the different subsystems involved in pHRC, shaping them to improve human safety according to selected metrics. Port-Hamiltonian formalisms are used to model each sub-system and their interconnection. An energy-based compliance controller that enhances safety by adapting the robot behavior is proposed and validated through extensive simulations.
A semantic map which comprises quantitative and qualitative space representations with semantic information seems to be an obligatory part of every robotic system designed to work hand in hand with humans. In this pap...
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The paper presents the process and methodology of nomination control signals based on the measurement signals. The process was made to allow for the determination of the replacement of the control signal in order to a...
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The paper presents the process and methodology of nomination control signals based on the measurement signals. The process was made to allow for the determination of the replacement of the control signal in order to adjust its frequency to the frequency of operation of the control system. The purpose of the algorithm is to adjust the frequency of the measured signal to the frequency control circuit when the frequency of the signals from the measurements is too low. The algorithm is based on Hermite curves taking into account measurement signal and their first derivative. The paper also presents the verification of the algorithm. It has been tested to angular displacement measuring signals and their velocity in the human lower limb joints in the sagittal plane.
This paper reports on novel nonlinear observer for a flux-controlled active magnetic bearing (AMB). Also a nonlinear state-feedback control law is designed for AMB in zero-bias mode due to voltage saturation. The nonl...
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This paper reports on novel nonlinear observer for a flux-controlled active magnetic bearing (AMB). Also a nonlinear state-feedback control law is designed for AMB in zero-bias mode due to voltage saturation. The nonlinear reduced-order observer is designed, to estimate the flux, and incorporated in equivalence implementation of the nonlinear state-feedback controller. The main design tools such as sliding mode control, control Lyapunov Function (CLF) and passivity are used in this framework. Numerical simulations show the effectiveness of the proposed observer-feedback and state-feedback designs.
Recognition of people based on their way of movement is one of the most interesting issues of behavioural biometrics. Among the basic characteristics of each biometric system is accuracy. It is currently considered th...
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Recognition of people based on their way of movement is one of the most interesting issues of behavioural biometrics. Among the basic characteristics of each biometric system is accuracy. It is currently considered that greater accuracy of biometric can be achieved by ensemble of two and more classifiers. The aim of this study is to present our own method for the usage of ensemble classifiers in the biometrics of the human gait based on ground reaction forces. In the presented ensemble of k-nearest neighbor classifiers the input signals were formed by dividing the ground reaction forces into sub phases characteristic of the support phase of the gait cycle. The research was carried out based on measurements from 200 people (more than 3500 gait cycles). The correct classification rate for proposed here method is more than 97.37%.
Nowadays in industry, data acquisition system signals are often compressed by piecewise linear trending. Many authors have indicated that compression with use of a wavelet transform provides better results. In this pa...
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Nowadays in industry, data acquisition system signals are often compressed by piecewise linear trending. Many authors have indicated that compression with use of a wavelet transform provides better results. In this paper, the threshold selection algorithms, such as VisuShrink, SureShrink, BayesShrink, and NeighCoeffs are compared experimentally using real industrial data from the Damadics benchmark. The impact of the compression on the decoded signal is analysed. The results of the calculations are compared with a standard piecewise linear trending approach.
Motivation and emotion are inseparable component factors of value systems in living beings, which enable them to act purposefully in a partially unknown and sometimes unforgiving environment. Value systems that drive ...
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ISBN:
(纸本)9781479919611
Motivation and emotion are inseparable component factors of value systems in living beings, which enable them to act purposefully in a partially unknown and sometimes unforgiving environment. Value systems that drive innate reinforcement learning mechanisms have been identified as key factors in self-directed control and autonomous development towards higher intelligence and seem crucial in the development of a concept of “self” in sentient beings [1]. This contribution is concerned with the relationship between artificial learning control systems and innate value systems. In particular, we adapt the state-of-the-art model of motivational processes based on reduction of generalized drives towards higher flexibility, expressivity and representation capability. A framework for modelling self-adaptive value systems, which develop autonomously starting from an inherited (or designed) innate representation, within a learning control system architecture is formulated. We discuss the relationship of anticipated effects in this control architecture with psychological theory on motivations and contrast our framework with related approaches.
This article presents a software tool for the synthesis of supervisory control based on untimed finite state automata. The tool has a friendly graphical interface for the creation of models and, among other features, ...
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In the present paper, a discriminative model for object recognition based on the Hidden Conditional Random Fields (HCRF) model is proposed. It impose the constraints on the positions of object parts with a star shape ...
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ISBN:
(纸本)9781479989218
In the present paper, a discriminative model for object recognition based on the Hidden Conditional Random Fields (HCRF) model is proposed. It impose the constraints on the positions of object parts with a star shape spatial prior. The proposed model can learn the ideal locations of parts, but also their spatial extent. Actually, the added constraints refine the assignment of part labels to local patches. Thus, our model can take advantage of appearance features and geometric structures in recognizing object. Efficient inference and parameter learning approaches are developed to handle the extra hidden variables (i.e. the positions of parts). Experiment results demonstrate the proposed model perform better than original HCRF model.
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