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This paper develops a novel adaptive state tracking control scheme based on Takagi–Sugeno (T–S) fuzzy models with unknown parameters. The proposed method can deal with T–S models in a non-canonical form and allows the number of inputs to be less than state variables, which is more practical and has wider applications. The needed matching conditions for state tracking are relaxed by using a T–S fuzzy reference model to generate desired state reference signals. A new fuzzy estimator model is constructed whose states are compared with those of the T–S fuzzy model to generate the estimator state error which is used for the parameter adaptive law. Based on the Lyapunov stability theory, it has been proven that all the signals in the closed-loop system are bounded and the asymptotic state tracking can be achieved. The effectiveness of the proposed scheme is demonstrated through a magnetic suspension system and a transport airplane model. 相似文献
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N. García-Chan L.J. Alvarez-Vázquez A. Martínez M.E. Vázquez-Méndez 《Journal of The Franklin Institute》2014
Within the framework of numerical modelling and multi-objective control of partial differential equations, in this work we deal with the problem of determining the optimal location of a new industrial plant. We take into account both economic and ecological objectives, and we look not only for the optimal location of the plant but also for the optimal management of its emissions rate. In order to do this, we introduce a mathematical model (a system of nonlinear parabolic partial differential equations) for the numerical simulation of air pollution. Based on this model, we formulate the problem in the field of multi-objective optimal control from a cooperative viewpoint, recalling the standard concept of Pareto-optimal solution, and pointing out the usefulness of Pareto-optimal frontier in the decision making process. Finally, a numerical algorithm – based on a characteristics/Galerkin discretization of the adjoint model – is proposed, and some numerical results for a hypothetical situation in the region of Galicia (NW Spain) are presented. 相似文献
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This paper deals with the problem of constrained stability and tracking of Takagi–Sugeno (T–S) fuzzy positive systems. Linear programming (LP) is used to insert the constraints in the design phase while imposing positivity in closed-loop. The theoretical results are applied to the buck DC–DC converter which is widely used in the photovoltaic generators. Based on the simulation results success of the method is shown for this application. 相似文献
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This paper develops a novel stability analysis method for Takagi–Sugeno (T–S) fuzzy systems with time-varying delay. New delay-dependent stability criteria in terms of linear matrix inequalities for time-varying delayed T–S fuzzy systems are derived by the newly proposed augmented Lyapunov–Krasovski (L–K) functional. This functional contains the cross terms of variables and quadratic terms multiplied by a higher degree scalar function. Different from previous results, our derivation applies the idea of second-order convex combination, and the property of quadratic convex function without resorting to the Jensen's inequality. Two numerical examples are provided to verify the effectiveness of the presented results. 相似文献
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This paper deals with the problem of robust stability and robust stabilization for a class of continuous-time singular Takagi–Sugeno fuzzy systems. Sufficient conditions on stability and stabilization are proposed in terms of strict LMI (Linear Matrix Inequality) for uncertain T–S fuzzy models. In order to reduce the conservatism of results developed using quadratic method, an approach based on non-quadratic Lyapunov functions and S-procedure is proposed. Illustrative examples are given to show the effectiveness of the given results. 相似文献
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This paper deals with the fault tolerant control (FTC) design for a Vertical Takeoff and Landing (VTOL) aircraft subject to external disturbances and actuator faults. The aim is to synthesize a fault tolerant controller ensuring trajectory tracking for the nonlinear uncertain system represented by a Takagi–Sugeno (T–S) model. In order to design the FTC law, a proportional integral observer (PIO) is adopted which estimate both of the faults and the faulty system states. Based on the Lyapunov theory and ?2 optimization, the trajectory tracking performance and the stability of the closed loop system are analyzed. Sufficient conditions are obtained in terms of linear matrix inequalities (LMI). Simulation results show that the proposed controller is robust with respect to uncertainties on the mechanical parameters that characterize the model and secures global convergence. 相似文献
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In this paper, a method is proposed to reject disturbances in the model predictive control (MPC) strategy. In addition, uncertainties in the system parameters (i.e., internal disturbances) are considered as well. To achieve these goals, adaptive neural networks are designed as the predictor model and as the nonlinear disturbance observer, respectively. The disturbances are rejected via the optimization problem of the MPC. Stability of the closed-loop system is studied based on the Input-to-State Stability method. The proposed method is applied to the pH neutralization process and CSTR system and its effectiveness in optimal rejection of the disturbances and satisfying the system constrains is compared with the feed-forward control method. 相似文献
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The resilient adaptive controller design problem of a class of Itô-type Takagi–Sugeno (T–S) fuzzy stochastic systems with time-varying delay and Markovian switching is investigated. By utilizing improved matrix decoupling technique, passivity theory and stochastic Lyapunov–Krasovskii functional, LMIs-based sufficient conditions for the existence of resilient adaptive controller are provided such that the corresponding closed-loop system is almost surely asymptotically stable and robustly passive in the sense of expectation. The derived conditions can be easily solved with the help of LMI toolbox in Matlab. A simulation example is presented to illustrate the effectiveness of the proposed resilient adaptive control schemes. 相似文献
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This paper deals with the problem of stabilization by state feedback control of Takagi–Sugeno (T–S) fuzzy discrete-time systems with multiple fixed delays while imposing positivity in closed-loop. The obtained results are presented under linear programming (LP) form. In particular, the synthesis of state feedback controllers is first solved in terms of Linear programming for the unbounded controls case. This result is then extended to the stabilization problem by nonnegative controls, and stabilization by bounded controls. The stabilization conditions are derived using the single Lyapunov–Krasovskii functional (LKF). An example of a real plant is studied to show the advantages of the design procedure. A comparison between linear programming and LMI approaches is presented. 相似文献
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集群创新网络演化的动力和合作机制研究 总被引：4，自引：0，他引：4
依据霍兰的复杂适应系统理论,运用刺激—反应模型和回声模型对集群创新网络形成的动力、合作机制进行了深入地阐释。在剖析集群创新网络形成的特征、影响因素以及合作条件的基础上,提出了4条促进集群创新网络快速发展的政策建议。 相似文献
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[目的/意义]探究技术的知识网络层次结构以及不同层次技术知识的复杂度,对于揭示知识网络的微观形态和分析拥有不同知识结构创新主体的技术竞争优势具有重要研究意义。[方法/过程]以美国USPTO专利数据库中Energy Conservation领域的专利数据为例,构建技术的知识—知识网络(Knowledge-Knowledge Network,KKN)和知识—地理二模网络(Knowledge-Geography Network,KGN),基于K-core分解方法对KKN进行层次解析,获得知识网络的基础层、中间层、细节层三层微观知识结构,利用基于反射机制的知识复杂度测度模型(Knowledge Complexity Model,KCM)探究KKN中各层技术知识的复杂度,并分析不同城市在该领域所表现出的技术竞争优势。[结果/结论]知识复杂度能够反映知识空间分布集聚特征和被复制、模仿的难易程度,且随着该领域技术创新发展而逐渐提高。知识网络基础层代表着一个领域核心知识结构,具有较高空间覆盖率和较低知识复杂度;中间层和细节层代表一个领域微观知识结构,具有相对较低的空间覆盖率和较高的知识复杂度,是挖掘一个领域新兴技术的关键层次。城市拥有更多中间层和细节层知识往往更具有较明显的技术竞争优势。 相似文献
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基于多体动力学理论,通过ADAMS/CAR建立双横臂悬架的仿真模型。采用DOE试验设计方法对悬架模型进行优化,判断对悬架KC特性影响较大的关键硬点。结合NSGA-Ⅱ遗传算法,利用ADAMS-ISIGHT联合仿真对硬点进行多目标优化,获得关键硬点的pareto最优解集。通过验证,结果表明,优化后的双横臂悬架在车轮跳动过程中,车轮前束角、外倾角和轮距变化范围更小,有利于减少轮胎磨损,提高汽车操纵稳定性。 相似文献
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针对标准的BP神经网络对于声音信号识别率不高的问题,提出了一种用粒子群算法（PSO）优化BP神经网络的算法,建立了声音信号识别模型。PSO优化BP神经网络主要是用PSO来优化BP神经网络的初始权值和闽值,然后通过训练BP神经网络得到识别模型的最优解,优化后的神经网络具有误判率小、反应速度快等特点。在实验中把标准的BP神经网络和PSO优化后的BP神经网络用于八种异常声音的MFCC特征量和差分MFCC特征量识别,结果表明：在声音信号的识别系统中采用PSO优化BP神经网络的算法提高了系统的识别性能,达到了系统设计的目的。 相似文献
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This paper studies the optimal finite-time passive control problem for a class of uncertain nonlinear Markovian jumping systems (MJSs). The Takagi and Sugeno (T–S) fuzzy model is employed to represent the nonlinear system with Markovian jump parameters and norm-bounded uncertainties. By selecting an appropriate Lyapunov-Krasovskii functional, it gives a sufficient condition for the existence of finite-time passive controller such that the uncertain nonlinear MJSs is stochastically finite-time bounded for all admissible uncertainties and satisfies the given passive control index in a finite time-interval. The sufficient condition on the existence of optimal finite-time fuzzy passive controller is formulated in the form of linear matrix inequalities and the designed algorithm is described as an optimization one. A numerical example is given at last to illustrate the effectiveness of the proposed design approach. 相似文献
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This paper investigates the problem of robust fault detection for a class of discrete-time nonlinear systems, which are represented by Takagi–Sugeno (T–S) fuzzy affine dynamic models with norm-bounded uncertainties. The objective is to design an admissible fault detection filter guaranteeing the asymptotic stability of the resulting residual system with prescribed performances. It is assumed that the plant premise variables, which are often the state variables or their functions, are not measurable so that the fault detection filter implementation with state-space partition may not be synchronized with the state trajectories of the plant. Based on a piecewise quadratic Lyapunov function combined with S-procedure and some matrix inequality convexification techniques, the results are formulated in the form of linear matrix inequalities. Finally, a simulation example is provided to illustrate the effectiveness of the proposed approach. 相似文献
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Xuepan Zhong Qian Huang Robert M. Davison Xuan Yang Huaping Chen 《International Journal of Information Management》2012
Effective teamwork and knowledge coordination are becoming increasingly important for all kinds of organizations given the growing use of teams to tackle competitive challenges and sustain competitive advantage. In this study, we develop and validate a model of how two types of social network ties – expressive and instrumental – contribute to team efficacy and performance, mediated by three dimensions of a transactive memory system (TMS) – specialization, credibility and coordination within teams. We test the model in an empirical study drawing on data from 66 teams in a variety of organizations. The results suggest that both instrumental and expressive ties within teams can facilitate the formation of TMS and the three dimensions of TMS are all, even though to different extents, positively related to team efficacy. Team efficacy is also a powerful predictor of team performance. The findings in our study bridge the literature gap about social networks and TMS and explain the underlying process and mechanisms by which social network ties exert their influence on team outcomes. The results have implications for organizations that wish to leverage teams to take advantage of team members’ differentiated expertise and coordinate their work more effectively and efficiently. 相似文献