Multi-variable systems widely exist in the practical engineering controlsystems whose performances are always severely interrupted by strong disturbances including unmodeled dynamics, parameter variations, couplings ...
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Multi-variable systems widely exist in the practical engineering controlsystems whose performances are always severely interrupted by strong disturbances including unmodeled dynamics, parameter variations, couplings and external disturbances. Disturbance observer (DOB) is known as an effective technique to estimate disturbances and has been extensively applied for feed-forward compensation design in the presence of disturbances. Yet many disturbance observer techniques in previous literature are just used for single-input-single-output (SISO) systems or the DOBs can be applied in the multi-variable systems, but the DOBs are still SISO DOBs. A decoupled robust multi-input-multi-output neural network disturbance observer (MNNDOB) is designed for the multi-input-multi-output (MIMO) systems. Simulation results on the mixing tank show that the proposed method has better disturbance estimation performance when there are severe model mismatches compared with the MIMO linear disturbance observer.
The behavior patterns and strategies of Internet Water Army in online forums are investigated in this paper. Internet Water Army focuses on the controlling and steering of cyber collective opinions, and adjusts their ...
The behavior patterns and strategies of Internet Water Army in online forums are investigated in this paper. Internet Water Army focuses on the controlling and steering of cyber collective opinions, and adjusts their behavior according to two principles: to avoid being exposed and to increase the ability to exert influence. To study how the ability of Internet Water Army to exert influence, we construct a multi-agent system with coevolution of topics and cyber collective behaviors and design the behavior patterns and strategies of Internet Water Army. Based on synthetic data and real data, we find that Internet Water Army dynamically adjusts their behavior strategy to maximize their influence and the effectiveness of strategy of Internet Water Army is closely related to the features of the users. Our work sheds insight on the design of viral marketing mechanism in e-commerce systems as well as on guiding collective behaviors in social media.
A bi-branchiate robot is presented for the inspection of the high-voltage power transmission lines. With a symmetrical mechanical structure, the robot can roll along the power lines and negotiating all the obstacles i...
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In this paper, the adaptive dynamic programming (ADP) approach is employed for designing an optimal controller of unknown discrete-time nonlinear systems with control constraints. A neural network is constructed for i...
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The boom of Flickr, a photo-sharing social tagging system, leads to a dramatical increasing of online social interactions. For example, it offers millions of groups for users to join in order to share photos and keep ...
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This paper develops an adaptive optimal control for the infinite-horizon cost of unknown nonaffine nonlinear continuous-time systems with control constraints. A recurrent neural network (NN) is constructed to identify...
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In this paper, a new self-learning method using policy iterative adaptive dynamic programming (ADP) is developed to obtain the optimal control scheme of discrete-time nonlinear systems. The iterative ADP algorithm per...
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In this paper, we aim to solve an infinite-time optimal tracking control problem for a class of discrete-time nonlinear systems using iterative adaptive dynamic programming (ADP) algorithm. When the iterative tracking...
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In this paper, an H ∞ optimal tracking control scheme based on generalized Hamilton-Jacobi-Isaacs (GHJI) equation is developed for discrete-time (DT) affine nonlinear systems. First, via system transformation, the op...
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This paper develops an observer-based direct adaptive output feedback control for a class of multi-input-multi-out nonaffine nonlinear discrete-time systems with unknown bounded disturbances. A neural network (NN) obs...
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