1,256 publications from this institution
Summary This paper investigates the problem of global control for a class of nonlinear systems via output feedback. The system nonlinearities satisfy the homogenous growth condition with unknown growth rate. First, a homogenous observer is constructed for estimating the system state. Then, two novel dynamic gains are presented to deal with the unknown growth rate. Subsequently, by adding a power integrator technique, a dynamic output feedback controller is designed to guarantee that all the signals of the closed‐loop system are bounded and the system states globally converge to origin. Finally, an example is provided to illustrate the validity of the proposed control scheme.
Notice of Violation of IEEE Publication Principles <br><br> After careful consideration by a duly constituted committee, an author of this article, Hamid Reza Karimi, was found to have acted in violation of the IEEE Principles of Ethical Publishing by artificially inflating the number of citations to this article. <br/> This paper deals with the observer design for Takagi–Sugeno (T–S) fuzzy models subject to unknown inputs and disturbance affecting both states and outputs of the system. Sufficient conditions to design an unknown input T–S observer are given in linear matrix inequality (LMI) terms. Both continuous-time and discrete-time cases are studied. Relaxations are introduced by using intermediate variables. Extension to the case of unmeasured decision variables is also given. A numerical example is given to illustrate the effectiveness of the given results.
The UK/European framework for access to the UHF TV band by white space devices (WSDs) is predicated on the communication of information on TV white space (TVWS) availability from white space databases (WSDBs) to WSDs. This information is in the form of location- and frequency-specific maximum permitted WSD radiated power levels. These levels are calculated in such a way so as to afford protection to the two incumbent (licensed) uses within the band, namely Digital Terrestrial Television (DTT), and Programme Making and Special Events (PMSE), as well as users of spectrum outside the band. In this paper we first outline the proposed framework for access to TV white spaces in the UK, describing the interactions between the regulator, WSDBs and WSDs. We then present the calculations required for the computation of maximum permitted WSD radiated power levels, accounting for nationwide DTT coverage and PMSE assignments.
Summary This article discusses the problem of global output feedback control for a class of uncertain nonlinear systems. Based on dynamic gain method and adding one power integrator, a new system design scheme is proposed to derive the adaptive output feedback controller such that the system state asymptotically converges to the origin. A numerical simulation and a practical example are presented to show the effectiveness of the proposed method.
Advanced manufacturing is a new trend for sustainable industrial development, and digital twin is a new technology that has attracted attention. Blast furnace smelting is an effective method in the manufacturing of iron and steel. Comprehensive and dependable surveillance of the blast furnace smelting process is essential for ensuring the smooth operation and improving of iron and steel output quality. The current technology makes it difficult to monitor the entire process of blast furnace ironmaking. Based on Unity 3D, this study presents a digital-twin virtual reality simulation system of blast furnace ironmaking. First, shading modeling creates a three-dimensional dynamic geometric model in different ironmaking system scenarios. Then, we script the animation and call particle system according to the motion mode of distinct geometric objects to give the dynamic effect of geometric objects. Shaders are the focus of the design and contributions. In addition, shader optimization technology can reduce hardware resource consumption and increase system fluency. Vertex shaders are used for all types of coordinate space transformation and vertex output; fragment shaders are used for texture sampling, light model calculation, normal calculation, noise superposition, and color output. The shader rendering technique allows for more realistic lighting effects. The presented dynamic digital twin system implements more realistic lighting analyzed in the ironmaking process. Virtual interaction logic’s design and deployment process is based on HTC VIVE hardware and VRTK toolkit. In the actual simulation process, the typical animation frame rate is stable at about 75 FPS (frames per second). The simulation system runs smoothly and a cutting-edge and state-of-the-art method for observing the blast furnace ironmaking process is suggested.
No abstract is provided for this article.
In this paper, a novel approach is proposed to design a robust fault detection observer for uncertain linear time delay systems. The system is composed of both norm‐bounded uncertainties and exogenous signals (noise, disturbance, and fault) which are considered to be unknown. The main contribution of this paper is to present unknown input observer ( UIO )‐based fault detection system which shows the maximum sensitivity to fault signals and the minimum sensitivity to other signals. Since the system contains uncertainty terms, an H ∞ model‐matching approach is used in design procedure. The reference residual signal generator system is designed so that the fault signal has maximum sensitivity while the exogenous signals have minimum sensitivity on the residual signal. Then, the fault detection system is designed by minimizing the estimation error between the reference residual signal and the UIO residual signal in the sense of H ∞ norm. A sufficient condition for the existence of such a filter is exploited in terms of certain linear matrix inequalities ( LMIs ). Application of the proposed method in a numerical example and an engineering process are simulated to demonstrate the effectiveness of the proposed algorithm. Simulation results show the validity of the proposed approach to detect the occurrence of faults in the presence of modeling errors, disturbances, and noise.
An actuator and sensor allocation approach is proposed for the design of coupled-adjacent-building vibration suppression under seismic excitation. This paper first establishes a full-order model of adjacent buildings with the location information of actuators and sensors. Then, the order of the model is reduced via modal cost analysis, by retaining the modes contributing the most. In view of the fact that the output powers of the actuators are limited, this paper brings forward a mixed <formula formulatype="inline" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex Notation="TeX">$H_{\infty}/GH_{2}$</tex></formula> control. By considering that not all the states of the system can be measured by the sensors, a dynamic output feedback controller is designed. The genetic algorithm is employed to obtain the locations of the actuators and sensors, as well as the corresponding controller. With the proposed approach, the allocation problem is solved, and the vibration of coupled adjacent buildings is attenuated at a sufficiently low level with constrained acting forces. Simulations demonstrate the effectiveness and robustness of the proposed approach in attenuating building vibration under earthquake excitation.
This paper presents a novel adaptive variable structure (AVS) method to design a fuzzy neural network (FNN). This AVS-FNN is based on radial basis function (RBF) neurons, which have center and width vectors. The network performs sequential learning through sliding data window reflecting system dynamic changes, and dynamic growing-and-pruning structure of FNN. The salient characteristics of the AVS-FNN are as follows: (1) Structure-learning and parameters estimation are performed automatically and simultaneously without partitioning input space and selecting initial parameters a priori. The structure-learning approach relies on the contribution of the size of the output. (2) A set of fuzzy rules can be inserted or reduced during the learning process. (3) The connection weighting factors between the deduction layer and output layer generated quickly without resorting to iteration learning are updated by the least-squares algorithm. The proposed method effectively generates a fuzzy neural model with a highly accurate and compact structure. Simulation results demonstrate that the proposed AVS-FNN has a self-organizing ability, which can determine the structure and parameters of the FNN automatically. The application of this new approach has been applied successfully in the 3 DOF helicopter systems, showing the effectiveness and potential of the proposed design techniques.
A decentralized unscented Kalman filter (UKF) method based on a consensus algorithm for multi-area power system dynamic state estimation is presented in this paper. The overall system is split into a certain number of non-overlapping areas. Firstly, each area executes its own dynamic state estimation based on local measurements by using the UKF. Next, the consensus algorithm is required to perform only local communications between neighboring areas to diffuse local state information. Finally, according to the global state information obtained by the consensus algorithm, the UKF is run again for each area. Its performance is compared with the distributed UKF without consensus algorithm on the IEEE 14-bus and 118-bus systems. The low communication requirements and high estimation accuracy of the decentralized UKF make it an alternative solution to the multi-area power system dynamic state estimation.
In this paper, the localization problem of a mobile robot equipped with a Doppler–azimuth radar (D–AR) is investigated in the environment with multiple landmarks. For the type (2,0) robot kinematic model, the unknown modeling errors are generally aroused by the inaccurate odometer measurement. Meanwhile, the inaccurate odometer measurement can also give rise to a type of unknown bias for the D–AR measurement. For reducing the influence induced by modeling errors on the localization performance and enhancing the practicability of the developed robot localization algorithm, an adaptive fading extended Kalman filter (AFEKF)-based robot localization scheme is proposed. First, the robot kinematic model and the D–AR measurement model are modified by considering the impact caused by the inaccurate odometer measurement. Subsequently, in the frame of adaptive fading extended Kalman filtering, the way to the addressed robot localization problem with unknown biases is sought out and the stability of the developed AFEKF-based localization algorithm is also discussed. Finally, in order to testify the feasibility of the AFEKF-based localization scheme, three different kinds of modeling errors are considered and the comparative simulations are conducted with the conventional EKF. From the comparative simulation results, it can be seen that the average localization error under the developed AFEKF-based localization scheme is [0.0245 m0.0224 m0.0039 rad]T and the average localization errors using the conventional EKF are [1.0405 m2.2700 m0.1782 rad]T, [0.4963 m0.3482 m0.0254 rad]T and [0.2774 m0.3897 m0.0353 rad]T, respectively, under the three cases of the constant bias, the white Gaussian stochastic bias and the bounded uncertainty bias.
No abstract is provided for this article.
Increasingly many teachers are turning to online social media to supplement educational resources and meet students' needs in the classrooms. The diffusion of information from online social media to the classroom is significantly faster than traditional curriculum-based approaches. However, this is contingent upon how well teachers across an online social media network are connected. To understand this, we perform a thorough and large-scale investigation of teacher connections in online social media, which is lacking in the literature. To make this feasible, we construct a large dataset of teachers on Pinterest, an image-based popular online social media. Our dataset includes 540 teachers across 5 states and 48 districts, thousands of connections they have established (either with their peers or some other Pinterest users), and all the resources they have shared in their accounts. Then, taking into account some crucial teacher-related attributes (e.g., their districts, grade levels, etc), we characterize direct and indirect teacher connections. Moreover, we compare the physical (face to face) and virtual (Pinterest) network of our surveyed teachers using several graph-related metrics. The finding in this study can serve as a basis to investigate teachers on social media in a deeper manner.
This paper deals with analyzing LQG control to mitigate vibrations in a semi-active suspension system (SAS) equipped with an MR rotary brake. The results of various simulations are studied and compared to the real system.
