1,256 publications from this institution
This paper studies a class of stochastic systems with multiple disturbances which include the disturbance with partially-known information and the white noise. A disturbance observer is constructed to estimate the disturbance with partially-known information, based on which, a disturbance observer-based disturbance attenuation control (DOBDAC) scheme is proposed by combining pole placement and linear matrix inequality (LMI) methods.
No abstract is provided for this article.
A novel iris biometric watermarking scheme is proposed focusing on iris recognition instead of the traditional watermark for increasing the security of the digital products. The preprocess of iris image is to be done firstly, which generates the iris biometric template from person's eye images. And then the templates are to be on discrete cosine transform; the value of the discrete cosine is encoded to BCH error control coding. The host image is divided into four areas equally correspondingly. The BCH codes are embedded in the singular values of each host image's coefficients which are obtained through discrete cosine transform (DCT). Numerical results reveal that proposed method can extract the watermark effectively and illustrate its security and robustness.
Small wind turbines are becoming an attractive solution for household applications. These micro generation units can be used as standalone applications or grid connected applications. However to get the full potential benefits of these wind turbines, systems should be low cost and reliable. Introducing the wind speed and rotor speed sensors at the generator shaft may reduce the reliability of small wind turbines. In this study, a grid connected sensor-less 5 kW small wind energy conversion system has been studied. The maximum power point tracking method of the wind turbine is totally independent from wind speed and rotor speed measurements. Optimum rotor speed and actual rotor speed are estimated using output current and voltage of the generator. To estimate the optimum rotor speed of the wind turbine, power signal feedback method has been used. Moreover, a sliding-mode observer is designed to estimate the rotor speed. Performance of the sliding-mode observer system has been compared with the measured rotor speed based wind energy conversion system. The simulation results show the effectiveness of the proposed sensor-less control system for the system under consideration.
This paper describes the modeling and simulation of High Pressure Roller Crusher (HPRC) for the production of silicon carbide grains. The study is to make a model for simulation of a High Pressure Roller Crusher. A High Pressure Roller Crusher (HPRC) is an important part in the production of silicon carbide, where the grains are crushed into powder form and then sieved into specified sizes based on its usage. This paper will present a model based on Johanson's theory for roller compactors, considering all the delays. The non-linearity or delays were handled using Matlab software. Conclusions are given at end of the paper.
Floating wind turbine will suffer from more fatigue and ultimate loads compared with fixed-bottom installation due to its floating foundation, while structural control offers a possible solution for direct load reduction. This paper deals with the modelling and parameter tuning of a spar-type floating wind turbine with a tuned mass damper (TMD) installed in nacelle. First of all, a mathematical model for the platform surge-heave-pitch motion and TMD-nacelle interaction is established based on D’Alembert’s principle. Both intrinsic dynamics and external hydro and mooring effects are captured in the model, while tower flexibility is also featured. Then, different parameter tuning methods are adopted to determine the TMD parameters for effective load reduction. Finally, fully coupled nonlinear wind turbine simulations with different designs are conducted in different wind and wave conditions. The results demonstrate that the design of TMD with small spring and damping coefficients will achieve much load reduction in the above rated condition. However, it will deteriorate system performance when the turbine is working in the below rated or parked situations. In contrast, the design with large spring and damping constants will produce moderate load reduction in all working conditions.
In this paper, intelligent devices in industrial manufacturing are modeled as the nodes in the network systems. The sampled-data control is adopted to guarantee the synchronization of the network systems. The proposed sampled-data control strategy can reduce the updating frequency of the controller and the network communication burden. The closed-loop system is equivalently rewritten as the feedback interaction of a linear time-invariant system and a time-delay operator. The small gain theorem is utilized to calculate the upper bound of the sampling intervals. Furthermore, the integral quadratic constraints can provide the passivity-type property of the operator and give less-conservative results. Moreover, in order to further use the information about the sampling pattern and sawtooth structure, the time-delay integral operator is replaced by sample-data integral operator, and less-conservative results are proposed. Finally, the effectiveness of the proposed sampled-data distributed control strategy is demonstrated by a numerical example.
Co-segmentation aims at segmenting common objects from a group of images. Markov random field (MRF) has been widely used to solve co-segmentation, which introduces a global constraint to make the foreground similar to each other. However, it is difficult to minimize the new model. In this paper, we propose a new Markov random field-based co-segmentation model to solve co-segmentation problem without minimization problem. In our model, foreground similarity constraint is added into the unary term of MRF model rather than the global term, which can be minimized by graph cut method. In the model, a new energy function is designed by considering both the foreground similarity and the background consistency. Then, a mutual optimization approach is used to minimize the energy function. We test the proposed method on many pairs of images. The experimental results demonstrate the effectiveness of the proposed method.
Digitization and digitalization have already changed our world significantly.Further disruptions are imminent with the ongoing digital transformation, a major component of which is digital twins.As the big data techniques, Internet of Things, cloud computing, and artificial intelligence algorithms advance, the digital twin technology has entered a phase of rapid development.It has been stated to be one of the top ten most promising technologies.Although it is still in its early stages, digital twins are already being widely used in a variety of fields, especially in industry, smart cities, and smart health, which are points that attract most researchers to study.In the literature, there can be seen numerous articles and reviews on digital twins, published every year in these three fields.It is therefore timely, even necessary, to provide an analysis of the published work.This is the motivation behind this article, the focus of which is the major research and application areas of digital twins.The survey first analyzes the recent developments of digital twins, then summarizes the theoretical underpinnings of the technology, and finally concludes with specific developments in various application areas of digital twins.It also discusses the challenges that may be encountered in the future.
This paper presents an application of radial basis function (RBF) in the identification and control design of transverse flux machines as nonlinear systems with unknown nonlinearity part. The technique of feedback linearization and H/sub /spl infin// control are used to design an adaptive control law for compensating the unknown nonlinearity part, such that the effect of the cogging torque as a disturbance is decreased into the angle and angular velocity tracking.
No abstract is provided for this article.
This paper investigates the problem of observer-based robust control for a class of switched stochastic systems with time-varying delay. Based on the average dwell time method, an exponential stability criterion for switched stochastic delay systems is proposed. Then, performance analysis and observer-based robust controller design for the underlying systems are developed. Finally, a numerical example is presented to illustrate the effectiveness of the proposed approach.
