This paper addresses the robust stabilization problem for T-S fuzzy stochastic descriptor systems using an integral sliding mode control paradigm. A classical integral sliding mode control scheme and a nonparallel dis...
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This paper addresses the robust stabilization problem for T-S fuzzy stochastic descriptor systems using an integral sliding mode control paradigm. A classical integral sliding mode control scheme and a nonparallel distributed compensation (Non-PDC) integral sliding mode control scheme are presented. It is shown that two restrictive assumptions previously adopted developing sliding mode controllers for Takagi-Sugeno (T-S) fuzzy stochastic systems are not required with the proposed framework. A unified framework for sliding mode control of T-S fuzzy systems is formulated. The proposed Non-PDC integral sliding mode control scheme encompasses existing schemes when the previously imposed assumptions hold. Stability of the sliding motion is analyzed and the sliding mode controller is parameterized in terms of the solutions of a set of linear matrix inequalities which facilitates design. The methodology is applied to an inverted pendulum model to validate the effectiveness of the results presented.
In this paper we discuss landmark based absolute localization of tiny autonomous mobile robots in a known environment. Landmark features are naturally occurring as it is not allowed to modify the environment with spec...
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In this paper, an integrative dynamical model of GnRH electrophysiology is used to study the calcium related interactions corresponding to bursting behavior. Various mechanisms affecting calcium dynamics are blocked o...
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These days' smart buildings have high intensive information and massive operational parameters, not only extensive power consumption. With the development of computation capability and future 5 G, the ACP theory(i...
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These days' smart buildings have high intensive information and massive operational parameters, not only extensive power consumption. With the development of computation capability and future 5 G, the ACP theory(i.e., artificial systems,computational experiments, and parallel computing) will play a much more crucial role in modeling and control of complex systems like commercial and academic buildings. The necessity of making accurate predictions of energy consumption out of a large number of operational parameters has become a crucial problem in smart buildings. Previous attempts have been made to seek energy consumption predictions based on historical data in buildings. However, there are still questions about parallel building consumption prediction mechanism using a large number of operational parameters. This article proposes a novel hybrid deep learning prediction approach that utilizes long short-term memory as an encoder and gated recurrent unit as a decoder in conjunction with ACP theory. The proposed approach is tested and validated by real-world dataset, and the results outperformed traditional predictive models compared in this paper.
A multi-level model, that provides a hierarchically structured description of a complex, multi-scale limb system is proposed in this paper for predicting and analyzing movement patters generated by various activation ...
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The aim of this work is to present an entropy-like Lyapunov function based dynamic feedback design technique for quasi-polynomial and Lotka-Volterra systems. It is shown, that the dynamic feedback design problem is eq...
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The aim of this work is to present an entropy-like Lyapunov function based dynamic feedback design technique for quasi-polynomial and Lotka-Volterra systems. It is shown, that the dynamic feedback design problem is equivalent to the feasibility of a bilinear matrix inequality. The problem is also formulated as a control Lyapunov function based feedback design when the Lyapunov function parameters are given, the solution of this problem can be obtained by solving a linear matrix inequality. The developed method is illustrated on a simple numerical example.
This paper investigates signal and system representations in special rational orthogonal bases of the Hardy space H2. These bases are derived from the Blaschke-group associated to the hyperbolic group SH(n) of matrice...
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It is shown that for open-loop stable plants the task of an MPC can be solved by identifying the plant model only instead of the redundant prediction model. Interesting structural considerations can be derived from co...
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It is shown that for open-loop stable plants the task of an MPC can be solved by identifying the plant model only instead of the redundant prediction model. Interesting structural considerations can be derived from comparison of the topologies and structural forms of regulators obtained by pole-placement design, the GTDOF scheme and the MPC . A new simple method is also introduced for adaptive and combined iterative identification and control for time-delay plants.
We present a sparse Bayesian reconstruction method based on multiple types of a priori information for multispectral bioluminescence tomography (BLT). In the Bayesian approach, five kinds of a priori information are i...
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This paper considers the design of robust H∞ filters for continuous-time linear systems with uncertainties described by integral quadratic constraints (IQCs). The synthesis problem can be converted into an infinite-d...
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