Networked controlsystems(NCSs) are facing a great challenge from the limitation of network communication resources. Event-triggered control(ETC) is often used to reduce the amount of communications while still keepin...
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ISBN:
(纸本)9781467374439
Networked controlsystems(NCSs) are facing a great challenge from the limitation of network communication resources. Event-triggered control(ETC) is often used to reduce the amount of communications while still keeping a satisfactory performance of the system, by transmitting the state measurements only when an event-triggered condition is met. However,some network-induced problems would happen inevitably, such as communication delay. The delay can degrade the control performance significantly and can even lead to instability. In this paper, we study an NCS considering both ETC and time-varying delay, which is rare in the literature. We formulate the system as a discretized piecewise linear system with exponential uncertainty. Then the model is embedded in a polytopic approximation with better structure suitable for stability *** conditions are derived in terms of linear matrix inequalities(LMIs). Finally, the developed method is illustrated by a numerical example.
This paper presents an online self-tuning Smith Predictor for the First Order Plus Dead Time Model (FOPDT). It can tune time delay through oscillated input and output. Realtime phase difference detection is used to ob...
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ISBN:
(纸本)9781509023974
This paper presents an online self-tuning Smith Predictor for the First Order Plus Dead Time Model (FOPDT). It can tune time delay through oscillated input and output. Realtime phase difference detection is used to obtain the phase difference between the input and the output. An online tuner is used to minimize the phase difference. Once the phase difference is minimized, the exact time delay is completely compensated. Our method is suitable for both systems with constant time delay or variant time delay.
This paper proposes an iterative evolutionary algorithm with emulating nodes' local movement for searching the best localization accuracy in range-free scenario. All localization methods face a trade-off between t...
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ISBN:
(纸本)9781467374439
This paper proposes an iterative evolutionary algorithm with emulating nodes' local movement for searching the best localization accuracy in range-free scenario. All localization methods face a trade-off between the solution quality and computation cost. When sensor network localization in range-free scenario is considered as a constraint satisfaction problem, localization will reach the highest accuracy but with huge computation complexity. To solve the constraint satisfaction, some characteristics that only exist in range-free localization problem are utilized as heuristics in the search of nodes' positions. They are summarized as simple and complex movement to emulate nodes' local movement, and proved to be effective to find a suitable searching direction and jump out of local-minimums existing in the localization. Those emulations are then included in each iteration of a two-objective evolutionary algorithm minimizing the number of node-pairs with violated connectivity, as well as the value quantitating how worse of the violations. Simulation results show that the proposed algorithm can greatly decrease the reach high-accurate positions within limited iterations.
When redundant manipulators work in a complex environment, many constraints need to be met. Gradient projection method (GPM) is a typical way to fulfil constraints that does not affect the main task. However it's ...
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Disrupting the circadian rhythms will cause health problems such as sleep disorders, memory disorders and obesity. Finding the suitable external stimulation to synchronize a model with a desired phase is a biologicall...
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ISBN:
(纸本)9781467374439
Disrupting the circadian rhythms will cause health problems such as sleep disorders, memory disorders and obesity. Finding the suitable external stimulation to synchronize a model with a desired phase is a biologically significant issue. The phase control of circadian rhythms for Drosophila is considered from control engineering viewpoint in this paper. If all parameters of the model are known, we can use the feedback linearization to design a tracking controller for the phase ***, in practice, parameters uncertainties always exist. To deal with this problem, a slide-mode controller is proposed for the phase tracking control of circadian rhythms. The simulation results show the effectiveness of the proposed method.
This paper reviews some main results and progress concerning with nonholonomic systemcontrol,especially focusing on the networked chained system *** controllability of nonholonomic system,the control method of nonhol...
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This paper reviews some main results and progress concerning with nonholonomic systemcontrol,especially focusing on the networked chained system *** controllability of nonholonomic system,the control method of nonholonomic system,the chained form transformation,the basic graph theory for multi-agent systems are recalled,*** important definitions,lemmas,theorems and dynamics are *** the consensus and formation control problems for networked nonholonomic chained systems are ***,some open questions are proposed.
With the addition of heating in thermal power *** to lack of guidance for heating scheduling in traditional scheduling mode,it has been unable to satisfy the current costs for energy conservation and saving of thermal...
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ISBN:
(纸本)9781467397155
With the addition of heating in thermal power *** to lack of guidance for heating scheduling in traditional scheduling mode,it has been unable to satisfy the current costs for energy conservation and saving of thermal power *** load distribution(especially heat load dispatch) is an important subject in the operation optimization of a thermal power *** model of heat load dispatch on the condition of economic power dispatch is established and linear programming for optimized heat load distribution among units based on LINGO is *** average distribution and linear programming distribution are contrasted in a thermal power *** is obviously shown by simulation and calculation that linear programming distribution gets more optimal results than current average *** has important significance to reduce energy consumption and save costs.
The state estimation problem for hidden Markov models subject to event-based sensor measurement updates is considered in this work, using the change of probability approach. We assume the measurement updates are trans...
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In this paper the asymmetric bistable system excited by binary aperiodic signals is taken as a model and the average symbol error rate is regarded as an index to study stochastic resonance (SR) phenomenon. Firstly, th...
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In this paper the asymmetric bistable system excited by binary aperiodic signals is taken as a model and the average symbol error rate is regarded as an index to study stochastic resonance (SR) phenomenon. Firstly, the SR driven by binary signals under α stable noise is studied. Secondly, the interplay between the α stable noise parameters α, β, and the system parameters a, b, r on the resonant output effect is explored. The results show that weak binary signals detection can be realized by adjusting the system parameters a, b and r. The optimal values solved by these parameters can make the system produce the best SR effect. For a certain a or b, there is an optimal value under different α or β. For the parameter r, there is an optimal value under different α, and there are several optimal values under different β. Moreover, when α or β is given different values, the evolution laws in asymmetric bistable SR system excited by binary signals are same. The results lay a foundation for realizing the adaptive parameter adjustment in asymmetric bistable SR system with α stable noise.
In this paper, the weak signal detection under α stable noise is investigated based on bistable vibrational resonance (VR) which is driven by a high frequency signal. On the one hand, the energy of the high frequency...
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In this paper, the weak signal detection under α stable noise is investigated based on bistable vibrational resonance (VR) which is driven by a high frequency signal. On the one hand, the energy of the high frequency drive signal is transferred to the low frequency weak signal when VR occurs; on the other hand, the control of stochastic resonance (SR) is achieved based on VR, which transfers more noise energy into useful signal energy. In addition, considering the requirements of real-time detection, the amplitude and frequency of the high frequency drive signal are optimized by the knowledge-based particle swarm optimization (KPSO), which takes the mean signal-noise-ratio (MSNR) of output as the fitness function, and the property that VR system produces the best resonance effect just when the valid system parameter â(B,Ω) is greater than zero as knowledge. Finally, the parameter compensation is combined to achieve multi-high frequency weak signals detection with a stable noise. Furthermore, the method is applied to the vibration fault diagnosis of a mono-crystalline silicon furnace, and the experiment results show the effectiveness and practicability of the method.
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