As one of key technologies in photovoltaic converter control, Maximum Power Point Tracking (MPPT) methods can keep the power conversion efficiency as high as nearly 99% under the uniform solar irradiance condition. Ho...
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As one of key technologies in photovoltaic converter control, Maximum Power Point Tracking (MPPT) methods can keep the power conversion efficiency as high as nearly 99% under the uniform solar irradiance condition. However, these methods may fail when shading conditions occur and the power loss can over as much as 70% due to the multiple maxima in I – P curve in shading conditions v.s. single maximum point in uniformly solar irradiance. In this paper, a Real Maximum Power Point Tracking (RMPPT) strategy under Partially Shaded Conditions (PSCs) is introduced to deal with this kind of problems. An optimization problem, based on a predictive model which will change adaptively with environment, is developed to tracking the global maxima and corresponding adaptive control strategy is presented. No additional circuits are required to obtain the environment uncertainties. Finally, simulations show the effectiveness of proposed method.
Recently we studied communication delay in distributed control of untimed discrete-event systems based on supervisor localization. We proposed a property called delay-robustness: the overall system behavior controlled...
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ISBN:
(纸本)9781467360890
Recently we studied communication delay in distributed control of untimed discrete-event systems based on supervisor localization. We proposed a property called delay-robustness: the overall system behavior controlled by distributed controllers with communication delay is logically equivalent to its delay-free counterpart. In this paper we extend our previous work to timed discrete-event systems, in which communication delays are counted by a special clock event tick. First, we propose a timed channel model and define timed delay-robustness;for the latter, a polynomial verification procedure is presented. Next, if the delay-robust property does not hold, we introduce bounded delay-robustness, and present an algorithm to compute the maximal delay bound (measured by number of ticks) for transmitting a channeled event. Finally, we demonstrate delay-robustness on the example of an under-load tap-changing transformer.
The need for user privacy in social networks has prompted the exploration of social networking designs which do not rely on the common centralised client-server model. Many peer-to-peer microblogging solutions have be...
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This paper presents a framework for the nonlinear control of dual-stage actuators (DSA). Motivated by various nonlinear controllers that make use of sector bounded and £ ∞ nonlinearities for the control of satur...
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This paper presents a framework for the nonlinear control of dual-stage actuators (DSA). Motivated by various nonlinear controllers that make use of sector bounded and £ ∞ nonlinearities for the control of saturated linear systems, a methodology for integrating such nonlinear functions in order to improve the performance of DSA is presented. The stability of the closed-loop system is assessed by casting the nonlinearities in a mixed sector-bounded plus quasi-Linear Parameter Varying (LPV) framework, leading to a set of linear matrix inequalities (LMIs) to be satisfied by the controller parameters. Taking advantage of the developed framework, a new £ ∞ function is proposed to avoid the saturation of the secondary actuator. Simulation results illustrate the validity of the proposed framework and its potential for the performance improvement of DSA.
Communication-Based Train control (CBTC) systems use bidirectional train-wayside wireless communications to ensure the safe operation of rail vehicles. Due to unreliable wireless networks, the uncertainties in train s...
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Communication-Based Train control (CBTC) systems use bidirectional train-wayside wireless communications to ensure the safe operation of rail vehicles. Due to unreliable wireless networks, the uncertainties in train status information leads to imperfect traction/braking commands, which will affect CBTC performance. In this paper, we use recent advance in cognitive control to positively improve control performance as well as reduce information uncertainties. A cognitive control system composed of Networked control System (NCS)-based state-space model and entropic-state model is presented. The performance optimization problem based on communication period decision and Medium Access control (MAC)-layer parameters adaption is formulated as a stochastic control process. Minimizing the energy consumption and information uncertainties is the objective of our model. Simulation result shows that the proposed cognitive control scheme can improve CBTC performance.
This paper revisits the problem of estimating the domain of attraction for systems with saturation *** divide the input space into several regions. In one of these regions, none of the inputs saturate. In each of the ...
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ISBN:
(纸本)9781479947249
This paper revisits the problem of estimating the domain of attraction for systems with saturation *** divide the input space into several regions. In one of these regions, none of the inputs saturate. In each of the remaining regions, there is a unique input that saturates everywhere with the time-derivative of its saturated signal being zero. These special properties of the inputs in different regions of the input space are combined with an existing piecewise quadratic Lyapunov functions that contains the information of input saturation to arrive at a set of less conservative stability conditions, from which a larger level set of the piecewise quadratic Lyapunov function can be obtained as an estimate of the domain of *** results indicate that the proposed approach has the ability to obtain a significantly larger estimate of the domain of attraction than the existing methods.
This paper discusses the problem of global finite-time output feedback stabilization in probability for a class of stochastic high-order nonlinear systems. A homogeneous observer and controller are constructed for the...
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This paper discusses the problem of global finite-time output feedback stabilization in probability for a class of stochastic high-order nonlinear systems. A homogeneous observer and controller are constructed for the nominal system based on the stochastic Lyapunov theorem and the adding one power integrator technique. Then, a scaling gain is introduced into the homogenous observer and controller to render the closed-loop system to be globally finite-time stable in probability. A simulation example is given to illustrate the effectiveness of the proposed design scheme.
A novel Virus-like-particle (VLP) bioreceptor layer has been integrated with an optical microdisk resonator platform for biosensing applications. This bioreceptor layer can be genetically programmed for selective bind...
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Among health behaviors, physical activity has the most extensive record of research using passive sensors. controlsystems and other system dynamic approaches have long been considered applicable for understanding hum...
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Among health behaviors, physical activity has the most extensive record of research using passive sensors. controlsystems and other system dynamic approaches have long been considered applicable for understanding human behavior, but only recently has the technology provided the precise and intensive longitudinal data required for these analytic approaches. Although sensors provide intensive data on the patterns and variations of physical activity over time, the influences of these variations are often unmeasured. Health behavior theories provide an explanatory framework of the putative mediators of physical activity changes. Incorporating the intensive longitudinal measurement of these theoretical constructs is critical to improving the fit of control system model of physical activity and for advancing behavioral theory. Theory-based control models also provide guidance on the nature of the controllers which serve as the basis for just-in-time adaptive interventions based on these control system models.
In the majority of cases, cervical cancer (CxCa) develops as a result of underestimated abnormalities in the Pap test. Nowadays, there are ancillary molecular biology techniques providing important information related...
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In the majority of cases, cervical cancer (CxCa) develops as a result of underestimated abnormalities in the Pap test. Nowadays, there are ancillary molecular biology techniques providing important information related to CxCa and the Human Papillomavirus (HPV) natural history, including HPV DNA test, HPV mRNA tests and immunocytochemistry tests. However, these techniques have their own performance, advantages and limitations, thus a combinatorial approach via computational intelligence methods could exploit the benefits of each method and produce more accurate results. In this paper we present a risk assessment model based on a Bayesian Network which, by combining the results of Pap test and ancillary tests, may identify women at true risk of developing cervical cancer and support the management of patients with ASCUS or LSIL cytology. The model, following the paradigm of other implemented systems, can be integrated into existing platforms and be available on mobile terminals for anytime/anyplace medical consultation.
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