This paper deals with the distributed output regulation problem for the discrete-time nonlinear multi-agent systems based on fuzzy models. T-S fuzzy models are constructed to approximate the considered nonlinear multi...
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ISBN:
(纸本)9781479900305
This paper deals with the distributed output regulation problem for the discrete-time nonlinear multi-agent systems based on fuzzy models. T-S fuzzy models are constructed to approximate the considered nonlinear multi-agent model, then we design the distributed feedback controller to guarantee the following agents asymptotically track the reference generated by an exosystem. The exosystem can be viewed as an active leader in the multi-agent systems, and the state of exosystem is assumed to be not completely measurable for each following agent. Finally, a numerical simulation example is provided to demonstrate the effectiveness of the obtained results.
An anti-windup compensate algorithm for active disturbance rejection mechanism is proposed in this paper. This paradigm extends the traditional anti-windup scheme to the Active Disturbance Rejection control(ADRC) mech...
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ISBN:
(纸本)9781479947249
An anti-windup compensate algorithm for active disturbance rejection mechanism is proposed in this paper. This paradigm extends the traditional anti-windup scheme to the Active Disturbance Rejection control(ADRC) mechanism, to deal with the input saturation nonlinearity and meanwhile reject the disturbance automatically by using Extended State Observer(ESO). The output of anti-windup compensator is treated as a part of unknown disturbances and is introduced into the ESO, which can online observe both internal and external disturbances(parameter uncertainties and model mismatches). The controller input is yielded by using a nonlinear feedback combination, and it is used to compensate the integrator windup caused by the saturation nonlinearity element. On the other hand, in order to determine the parameters of the ESO and the anti-windup compensator feedback gain, the L2 gain is adopted. The effectiveness and the robustness against model and parameter uncertainties of the proposed method is verified by an example of the seeker platform.
The paper proposes a new learning method for fuzzy cognitive maps, which makes it possible to encode an attractor into the map. The method is based on the principle of backpropagation through time known from the theor...
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ISBN:
(纸本)9781629934884
The paper proposes a new learning method for fuzzy cognitive maps, which makes it possible to encode an attractor into the map. The method is based on the principle of backpropagation through time known from the theory of artificial neural networks. Simulation results are presented to show how well the method performs. It is shown that the results are superior to those achieved using Hebbian learning approaches such as nonlinear Hebbian learning. Some lines for possible future research and development are given.
For synchronization of fractional-order chaotic systems,this paper presents a novel fractional-order sliding mode controller,in which fractional calculus is introduced to the sliding mode *** on Lyapunov stability the...
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ISBN:
(纸本)9789881563835
For synchronization of fractional-order chaotic systems,this paper presents a novel fractional-order sliding mode controller,in which fractional calculus is introduced to the sliding mode *** on Lyapunov stability theory and fractional-order system's stability theorem,stability analysis is *** examples are given respectively,which include synchronization of two identical fractional-order systems(Chen-Chen) and synchronization of two non-identical fractional-order systems(Chen-Liu).Numerical simulations illustrate the effectiveness of the proposed controller.
Quality-related fault detection attracted more and more attention in quality control and process monitoring. In recent literature, reconstruction based contributions (RBC) are used for isolating faulty variables which...
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ISBN:
(纸本)9781467355339
Quality-related fault detection attracted more and more attention in quality control and process monitoring. In recent literature, reconstruction based contributions (RBC) are used for isolating faulty variables which affect product quality. If datasets of known faults are available, fault-specific RBCs are used to identify fault types. Otherwise, variable RBCs are used to isolate faulty variables. However, the existing generalized RBC are quite improvable. On one side, fault-specific RBC can not tell faulty variables, which makes it hard to locate fault root. On the other side, it is well known that the variable RBC suffers a lot from the smearing effect, which provides too many candidates of faulty variables. In the present work, a new usage of RBC is derived to select faulty variables without smearing effect on non- faulty variables. The benchmark examples of Tennessee Eastman (TE) process is used to demonstrate the efficiency of the proposed approach for quality-related fault diagnosis.
OFDM is promising for underwater acoustic (UWA) communications due to its potential to combat the large delay spread. However, the performance of the OFDM system is seriously deteriorated by the inter-carrier interfer...
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ISBN:
(纸本)9781479982981
OFDM is promising for underwater acoustic (UWA) communications due to its potential to combat the large delay spread. However, the performance of the OFDM system is seriously deteriorated by the inter-carrier interference (ICI) caused by the transmitter/receiver motion and ocean waves. In this paper, we propose a novel ICI countermeasure. The key idea is to inactivate partial subcarriers according to index modulation and meanwhile transmit signals with opposite polarity on two adjacent active subcarriers for ICI self cancellation. Simulation results validate that the proposed scheme achieves much better bit error rate (BER) performance than many existing schemes in UWA communications.
A new knowledge-based Artificial Fish-swarm Algorithm (AFA) with crossover operator, namely CAFAC, is proposed to combat with the blind search of the original AFA. The crossover operator is explored, and the normative...
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During the practical production process, the soft sensors based on traditional single learning machine can not satisfied the needs of production. In this study, a multiple regression machine system (MRMS) is proposed ...
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