This paper is concerned with the problem of stabilization of continuous-time Takagi-Sugeno (TS) fuzzy systems which are controlled through networks. Network-induced delays, data packet dropouts, and measurement quanti...
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ISBN:
(纸本)9781467364591
This paper is concerned with the problem of stabilization of continuous-time Takagi-Sugeno (TS) fuzzy systems which are controlled through networks. Network-induced delays, data packet dropouts, and measurement quantization are simultaneously considered for Network signal-transmission. Based on the LyapunovKrasovskii functional approach and a parallel distributed compensation scheme, a delay-dependent stabilization approach is developed for the NCSs, which guarantees that the closed-loop system is asymptotically stable. Finally, an illustrative example is given to illustrate the effectiveness of the proposed design technique.
We report planar integration of tapered Terahertz (THz) quantum cascade lasers (QCLs) with spoof surface plasmon (SSP) structures. The SSP structure consists of one plasmonic coupler and periodically arranged scatters...
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ISBN:
(纸本)9781557529992
We report planar integration of tapered Terahertz (THz) quantum cascade lasers (QCLs) with spoof surface plasmon (SSP) structures. The SSP structure consists of one plasmonic coupler and periodically arranged scatters. The resulting surface-emitting THz beam is highly collimated with a beam divergence as narrow as 3.6°×9.7°. As the beam divergence is inverse proportional to the light emission area, this low divergence indicates a good waveguiding property of the SSP structure, while the low optical background of the beam implies a high coupling efficiency of the THz wave from the laser cavity to the SSPs. Since all the structures are in-plane, this scheme provides a promising platform where the well-established SP techniques can be employed to engineer the THz QCL beam with high flexibilities.
The class of isotherm lumped process systems with constant overall mass in each of its balance volumes is considered in this paper. It is shown that the convection and transfer mechanisms can be described by a mass ac...
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The class of isotherm lumped process systems with constant overall mass in each of its balance volumes is considered in this paper. It is shown that the convection and transfer mechanisms can be described by a mass action law chemical reaction network (MAL CRN) with only linear kinetics where the in- and outflow terms are represented using the zero complex. This gives rise to a convection and transfer reaction sub-graph that connects atomic complexes consisting of the components in the balance volumes of the system. The real chemical reactions in each of the balance volumes can be described by their own CRNs, where the chemical reaction sub-graphs may be disconnected from the convection and transfer reaction sub-graph when nonlinear reactions occur. In the case of chemical reactions with a finite number of steady state points, the underlying linear dynamical system enables us to construct a dynamically similar linear overall reaction graph for the whole process system. The resulting overall reaction graph can be used for structural stability analysis by applying its graph theoretical properties.
The input current stimulating a neuron is not directly measurable without inference with the cell's activities. In this paper we consider two electrically coupled neurons. We present an approach to reconstruct the...
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The input current stimulating a neuron is not directly measurable without inference with the cell's activities. In this paper we consider two electrically coupled neurons. We present an approach to reconstruct the input current into one of the neurons using concepts from control theory. More precisely, we employ an unknown input observer to reconstruct the internal states of the neuron's model. A crucial part of this approach is the transformation of the nonlinear model into an appropriate normal form. Additional filtering yields the desired excitation current.
In this paper, we present a two-layer nonlinear adaptive steering controller for autonomous lane change maneuver with respect to a stopped vehicle. First, we derive a dynamic model of the vehicle using the Boltzmann-H...
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ISBN:
(纸本)9781467327534
In this paper, we present a two-layer nonlinear adaptive steering controller for autonomous lane change maneuver with respect to a stopped vehicle. First, we derive a dynamic model of the vehicle using the Boltzmann-Hamel method in quasi-coordinates for nonholonomic systems. The lane change maneuver is investigated as a tracking problem with respect to desired cycloidal trajectory, which is generated in real time. An adaptive update control law is designed that allows tracking the desired trajectories in the presence of unknown inertial parameters of the vehicle. Simulation results illustrate the performance of the proposed controller.
The steam temperature at the outlet of the reheater has always been lower than the designed value in a power plant.A reheat steam temperature adjustment test was conducted on the two subcritical,intermediate reheat an...
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ISBN:
(纸本)9781479933372
The steam temperature at the outlet of the reheater has always been lower than the designed value in a power plant.A reheat steam temperature adjustment test was conducted on the two subcritical,intermediate reheat and natural circulation boilers in the power *** analyzing the test data,reasons of the low reheat steam temperature have been ***’s more,three schemes about capacity-increasing transformation for reheaters have been proposed and compared,after which the most reasonable one is *** is studied in the paper provides helpful experiences in solving similar problems for boilers of the same type.
A new visual servo control scheme for a robotic manipulator is presented in this paper, where a back propagation （BP） neural network is used to make a direct transition from image feature to joint angles without req...
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A new visual servo control scheme for a robotic manipulator is presented in this paper, where a back propagation （BP） neural network is used to make a direct transition from image feature to joint angles without requiring robot kinematics and camera calibration. To speed up the convergence and avoid local minimum of the neural network, this paper uses a genetic algorithm to find the optimal initial weights and thresholds and then uses the BP Mgorithm to train the neural network according to the data given. The proposed method can effectively combine the good global searching ability of genetic algorithms with the accurate local searching feature of BP neural network. The Simulink model for PUMA560 robot visual servo system based on the improved BP neural network is built with the Robotics Toolbox of Matlab. The simulation results indicate that the proposed method can accelerate convergence of the image errors and provide a simple and effective way of robot control.
This article presents a novel fault classification and diagnosis technique for bearings based on a Minimum Volume Ellipsoid (MVE) method for feature extraction. Data from two accelerometers located at two different si...
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ISBN:
(纸本)9781479915583
This article presents a novel fault classification and diagnosis technique for bearings based on a Minimum Volume Ellipsoid (MVE) method for feature extraction. Data from two accelerometers located at two different sites of the test bed are combined to create a two dimensional representation and the feature extraction stage condenses that information using an ellipsoid description. The proposed features feed a simple non-linear classifier which separates almost perfectly between normal and faulty conditions, with also very high diagnostic accuracy between the faulty classes. The obtained results suggest that this novel representation can be used within a condition monitoring system.
Single intersection is generally regarded as the elementary unit for solving traffic problem. A Type-2 fuzzy logic controller (T2FLC) for single intersection signal control is presented in this paper as Type-2 fuzzy l...
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Single intersection is generally regarded as the elementary unit for solving traffic problem. A Type-2 fuzzy logic controller (T2FLC) for single intersection signal control is presented in this paper as Type-2 fuzzy logic can handle the imprecision, uncertainties and vagueness lying in the dynamic process more efficiently. Furthermore, the membership function parameters of Type-2 fuzzy logic controller are optimized by genetic algorithm (GA). Simulation experiments are designed to compare the queue length and vehicular average delay of Type-2 fuzzy control optimized by GA with general Type-2 fuzzy control, Type-1 fuzzy control and fixed-time control under various types of vehicle arrival rate. Experimental results indicate that our proposed control method can reduce the queue length and vehicular delay at the intersection effectively and thus demonstrates its superiority.
The availability of reliable underwater positioning systems to localize one or more vehicles simultaneously based on information received on-board a support ship or an autonomous surface vessel is key to the operation...
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The availability of reliable underwater positioning systems to localize one or more vehicles simultaneously based on information received on-board a support ship or an autonomous surface vessel is key to the operation of some classes of AUVs. Furthermore, there is considerable interest in reducing the number of sensors involved in acoustic navigation/positioning systems to reduce the costs involved and the time consumed in the deployment, callibration, and recovery phases. Motivated by these considerations, in this paper we address the problem of single underwater target positioning based on measurements of the ranges between the target and a moving sensor at the sea surface, obtained via acoustic ranging devices. In particular, and speaking in loose terms, we are interested in determining the optimal geometric trajectory of the surface sensor that will, in a well defined sense, maximize the range-related information available for underwater target positioning. To this effect, an appropriate Fisher Information Matrix is defined and its determinant is maximized to yield the sensor trajectory that maximizes the accuracy of the target position estimate that can possibly be obtained with any unbiased estimator. It is shown that the optimal trajectory depends on the relative velocity of the sensor, the sampling time between measurements, and the number of measurements acquired for the FIM computation. Simulation examples illustrate the key results derived.
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