This paper addresses the global consensus problem for multi-input multi-output saturated systems within a sampled-data framework, aiming to advance global consensus, manage heterogeneous actuator saturation across com...
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In this paper, a new intelligence paradigm scheme to forecast landslide based on functional networks is presented. Both methodology and learning algorithm for this kind of intelligence system paradigm using the minima...
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ISBN:
(纸本)9781479914845
In this paper, a new intelligence paradigm scheme to forecast landslide based on functional networks is presented. Both methodology and learning algorithm for this kind of intelligence system paradigm using the minimax method are derived. The performance and validity of the new functional networks intelligence paradigm are demonstrated by using real-world example. The results show that the landslide prediction using functional networks is reasonable, effective and achieves a high-quality performance.
This paper presents new theoretical results on the multistability analysis of a class of recurrent neural networks with nonmonotonic activation functions and mixed time delays. Several sufficient conditions are derive...
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Memristive neural systems are a groundbreaking concept that is helping to understand the behavior of many physical, technical and bionic systems. This paper reviews the research status of memristive neural systems in ...
ISBN:
(纸本)9781479914845
Memristive neural systems are a groundbreaking concept that is helping to understand the behavior of many physical, technical and bionic systems. This paper reviews the research status of memristive neural systems in the past few years. Considering there are too many publications about the memristive neural systems, we summarize the relevant models and applications rather than contemplating to go into details of particular results. First, some representative models of memristive neural systems are simply introduced. Then, we briefly describe some novel applications in the related fields (dynamic information storage or retrieval, logical operations and ultra-high-performance computing). Subsequently, some existing problems are summarized, and finally, the trend of memristive neural systems is pointed out.
This paper studies the aperiodic sampled-data control for the sliding-mode control (SMC) scheme of fuzzy systems with communication-induced delays via the event-triggered method. In practice, it is impossible to updat...
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In this paper, a novel interval type-2 fuzzy logic controller (IT2FLC) is proposed for controlling a mobile wheeled inverted pendulum(MWIP) with model uncertainties and external disturbances. The MWIP is a typical und...
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ISBN:
(纸本)9781467384148
In this paper, a novel interval type-2 fuzzy logic controller (IT2FLC) is proposed for controlling a mobile wheeled inverted pendulum(MWIP) with model uncertainties and external disturbances. The MWIP is a typical underactuated system which is generally composed of two subsystems, an invert pendulum and a mobile robot system. The IT2FLC proposed in this paper is composed of a balancing controller, a velocity controller and a yaw steering controller. The proposed integrated IT2FLC is linear combination of the three individual IT2FLCs which uses simplified type reduce method. The proposed controller has simple structure and requires less computation, also it is expected to have robustness to uncertainties and external disturbances in the practical implementation. Considering the model uncertainties and external disturbances, simulation results proved the effectiveness and robustness of the proposed IT2FLC compared with type-1 fuzzy logic controller (T1FLC).
This paper describes a novel 3D needle segmentation algorithm for 3DUS data. The algorithm includes the 3D Gray-level Hough Transform (3DGHT), which is based on the representation (ψ, θ, ρ, α) of straight lines in...
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Electric vehicles are not widely adopted without proper charging infrastructure, despite their environmental benefits and growing popularity in transportation. This paper focuses on the location problem of charging in...
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Electric vehicles are not widely adopted without proper charging infrastructure, despite their environmental benefits and growing popularity in transportation. This paper focuses on the location problem of charging infrastructure to achieve a more optimized charging facility layout. The charging demands of electric vehicles can be divided into two categories. The first category is generated at network points such as shopping malls, office buildings, parking lots, and residential areas. The second category is generated along the flow of network paths, such as on the highway and on the way to and from work. The goal of this problem is to maximize both categories of charging demands using a nonlinear integer programming model. We introduce the spatial intersection model to obtain the data on path demand. The spatial intersection model is introduced to obtain data on path demand. In addition, future demand is taken into account in the optimization through data forecasting. Then, the greedy algorithm is designed to solve the optimization model. The effectiveness is proved by a lot of random experiments. Finally, the effects of parameters are analyzed by a case study. The location decision of charging stations for both demands is more reasonable than only one type of demand consideration. The proposed model ensures the coverage and appropriate extension of the charging network.
This paper investigates the problem of coordinated tracking of a linear multi-agent system subject to actuator magnitude saturation and dead zone characteristic with input additive uncertainties and disturbances. Dist...
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For strict-feedback systems with mismatched uncertainties, adaptive fuzzy control techniques are developed to provide global prescribed performance with prescribed-time convergence. First, a class of prescribed-time p...
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For strict-feedback systems with mismatched uncertainties, adaptive fuzzy control techniques are developed to provide global prescribed performance with prescribed-time convergence. First, a class of prescribed-time prescribed performance functions are designed to quantify the performance constraints of the tracking error. Additionally, a novel error transformation function is provided to eliminate the initial value limitations and resolve the singularity issue in previous research. To ensure the convergence of the tracking error into a prescribed bounded region within a prescribed time and satisfactory transient performance, controllers with or without approximating structures are established. Notably, the settling time and initial condition of the prescribed performance function are completely independent of the initial tracking error and system parameters, thereby improving upon existing results. Furthermore, the disadvantage of the semi-global boundedness of tracking error induced by dynamic surface control can be eliminated through the use of a novel Lyapunov-like energy function. Finally, the effectiveness of the proposed strategies is validated through numerical simulations performed on practical examples.
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