In this paper,the fixed-time consensus tracking control problem of multiagentsystems(MASs)subject to unknown nonlinearities and performance constraints is ***,an improved fixed-time performance function is designed,w...
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In this paper,the fixed-time consensus tracking control problem of multiagentsystems(MASs)subject to unknown nonlinearities and performance constraints is ***,an improved fixed-time performance function is designed,which enables the consensus tracking errors to converge to the preset region in fixed time,and alleviates the initial error conditions by setting the parameters ***,the unknown nonlinearities of MASs are approximated by the radial basis function neural network(RBF NN).Subsequently,a fixed-time prescribed performance controller is designed,which excludes the fractional power of tracking error to prevent potential singularity problems existing in stability ***,a fixed-time dynamic surface filter is formulated to eliminate the“explosion of complexity”issue,meanwhile,the filter errors are bounded in fixed *** the Lyapunov stability theory,it can be guaranteed that all signals in MASs exhibit practically fixed-time stability,and the consensus errors all approach a small region centered on origin within the prescribed ***,simulations are presented to verify the validity of the proposed control strategy.
Quadrotors play a significant role in our lives and are transforming our *** cable-suspended loads is an unavoidable quadrotor application trend and a hot research topic in the control ***,the load swing and unpredict...
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Quadrotors play a significant role in our lives and are transforming our *** cable-suspended loads is an unavoidable quadrotor application trend and a hot research topic in the control ***,the load swing and unpredictability pose significant challenges to the quadrotor's *** this paper,an anti-swing controller with an inner-outer control strategy for the quadrotor-slung load transportation system is *** facilitate the controller design,the outer position dynamics are restructured in the form of ***,a virtual controller is created to force the underactuated states to the dynamic surface to ensure the position subsystem's *** improve robustness,an adaptive law is used to eliminate the effects of uncertain cable ***,a dynamic surface controller for the inner attitude subsystem is presented to drive the actual force to the virtual *** is demonstrated that the control strategy can stabilize the quadrotor despite mass and cable length *** results are provided to demonstrate the efficacy and durability of the proposed method.
Fixed-time synchronization(FTS)of delayed memristor-based neural networks(MNNs)with discontinuous activations is studied in this *** continuous and discontinuous activations are considered *** the mixed delays which a...
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Fixed-time synchronization(FTS)of delayed memristor-based neural networks(MNNs)with discontinuous activations is studied in this *** continuous and discontinuous activations are considered *** the mixed delays which are closer to reality are taken into the ***,two kinds of control schemes are proposed,including feedback and adaptive control *** on some lemmas,mathematical inequalities and the designed controllers,a few synchronization criteria are ***,the upper bound of settling time(ST)which is independent of the initial values is ***,the feasibility of our theory is attested by simulation examples.
In order to scientifically and effectively evaluate the performance indexes of aircraft, the common Bayes multi-source data fusion method can comprehensively utilize a variety of information types under the condition ...
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ISBN:
(数字)9798350389463
ISBN:
(纸本)9798350389470
In order to scientifically and effectively evaluate the performance indexes of aircraft, the common Bayes multi-source data fusion method can comprehensively utilize a variety of information types under the condition that the decision risk is as small as possible, but there are risks such as insufficient data utilization and small sample data being “submerged” by large sample data in the fusion. This paper proposes a test data expansion method based on the combination of probability features and BP neural network model, and is verified by typical application to ensure that the sample size of multi-source data is comparable. Supplementary data not only retains the probability features of the original data, but also the sample generation has physical connotation.
The importance of Model Predictive control(MPC)has significant applications in the agricultural industry,more specifically for greenhouse’s control ***,the complexity of the greenhouse and its limited prior knowledge...
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The importance of Model Predictive control(MPC)has significant applications in the agricultural industry,more specifically for greenhouse’s control ***,the complexity of the greenhouse and its limited prior knowledge prevent an exact mathematical description of the *** methods provide a promising solution to this issue through their capacity to identify the system’s comportment using the fit between model output and observed *** this paper,we introduce an application of Constrained Model Predictive control(CMPC)for a greenhouse temperature and relative *** this purpose,two Multi Input Single Output(MISO)systems,using Numerical Subspace State Space system Identification(N4SID)algorithm,are firstly suggested to identify the temperature and the relative humidity comportment to heating and ventilation *** this sense,linear state space models were adopted in order to evaluate the robustness of the control *** the system is identified,the MPC technique is applied for the temperature and the humidity *** results show that the regulation of the temperature and the relative humidity under constraints was guaranteed,both parameters respect the ranges 15℃≤T_(int)≤30℃and 50%≤H_(int)≤70%*** the other hand,the control signals uf and uh applied to the fan and the heater,respect the hard constraints notion,the control signals for the fan and the heater did not exceed 0≤uf≤4.3 Volts and 0≤uh≤5 Volts,respectively,which proves the effectiveness of the MPC and the tracking ***,we show that with the proposed technique,using a new optimization toolbox,the computational complexity has been significantly *** greenhouse in question is devoted to Schefflera Arboricola cultivation.
Input variables selection(IVS) is proved to be pivotal in nonlinear dynamic system modeling. In order to optimize the model of the nonlinear dynamic system, a fuzzy modeling method for determining the premise structur...
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Input variables selection(IVS) is proved to be pivotal in nonlinear dynamic system modeling. In order to optimize the model of the nonlinear dynamic system, a fuzzy modeling method for determining the premise structure by selecting important inputs of the system is studied. Firstly, a simplified two stage fuzzy curves method is proposed, which is employed to sort all possible inputs by their relevance with outputs, select the important input variables of the system and identify the ***, in order to reduce the complexity of the model, the standard fuzzy c-means clustering algorithm and the recursive least squares algorithm are used to identify the premise parameters and conclusion parameters, respectively. Then, the effectiveness of IVS is verified by two well-known issues. Finally, the proposed identification method is applied to a realistic variable load pneumatic system. The simulation experiments indi cate that the IVS method in this paper has a positive influence on the approximation performance of the Takagi-Sugeno(T-S) fuzzy modeling.
This study introduces a data-driven approach for state and output feedback control addressing the constrained output regulation problem in unknown linear discrete-time systems. Our method ensures effective tracking pe...
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This study introduces a data-driven approach for state and output feedback control addressing the constrained output regulation problem in unknown linear discrete-time systems. Our method ensures effective tracking performance while satisfying the state and input constraints, even when system matrices are not available. We first establish a sufficient condition necessary for the existence of a solution pair to the regulator equation and propose a data-based approach to obtain the feedforward and feedback control gains for state feedback control using linear programming. Furthermore, we design a refined Luenberger observer to accurately estimate the system state, while keeping the estimation error within a predefined set. By combining output regulation theory, we develop an output feedback control strategy. The stability of the closed-loop system is rigorously proved to be asymptotically stable by further leveraging the concept of λ-contractive sets.
In this paper,we review the development of a phase theory for systems and networks in its first five years,represented by a trilogy:Matrix phases and their properties;The MIMO LTI system phase response,its physical in...
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In this paper,we review the development of a phase theory for systems and networks in its first five years,represented by a trilogy:Matrix phases and their properties;The MIMO LTI system phase response,its physical interpretations,the small phase theorem,and the sectored real lemma;The synchronization of a multi-agent network using phase *** the end,we also summarize a list of ongoing research on the phase theory and speculate what will happen in the next five years.
作者：
Tao, ZixingCao, WeihuaGan, Chao
Wuhan China
School of Future Technology School of Automation Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China
Air quality data exhibit nonlinearity, sensitivity to environmental factors, and long-term dependencies. Numerous factors influence air quality, making accurate predictions based on a single-dimensional dataset imprac...
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The distributed optimization for multi-agentsystems (MASs) is investigated in this paper. In the system, the unknown time-varying disturbances affecting each agent are taken into account. A distributed event-triggere...
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