Adaptive Fuzzy Observer Backstepping Control for a Class of Uncertain Nonlinear Systems with Unknown Time-delay

In this paper, a new adaptive fuzzy backstepping control approach is developed for a class of nonlinear systems with unknown time-delay and unmeasured states. Using fuzzy logic systems to approximate the unknown nonlinear functions, a fuzzy state observer is designed for estimating the unmeasured states. On the basis of the state observer and applying the backstepping technique, an adaptive fuzzy observer control approach is developed. The main features of the proposed adaptive fuzzy control approach not only guarantees that all the signals of the closed-loop system are semiglobally uniformly ultimately bounded, but also contain less adaptation parameters to be updated on-line. Finally, simulation results are provided to show the effectiveness of the proposed approach.

New delay-dependent robust stability and stabilization for uncertain T-S fuzzy time-delay systems under imperfect premise matching

To alleviate the conservativeness of the stability criterion for Takagi-Sugeno （T-S） fuzzy time-delay systems, a new delay-dependent stability criterion was proposed by introducing a new augmented Lyapunov function with an additional triple-integral term, which was firstly u3ed to derive the stability criterion for T-S fuzzy time-delay systems. By the same approach, the robust stability issue for fuzzy time-delay systems with uncertain parameters was also considered. On the other hand, in order to enhance the design flexibility, a new design approach for uncertain fuzzy time-delay systems under imperfect premise matching was also proposed, which allows the fuzzy controller to employ different membership functions from the fuzzy time-delay model. By the numerical examples, the proposed stability conditions are less conservative in the sense of getting larger allowable time-delay and obtaining smaller feedback control gains. For instance, when the allowable time-delay increases from 7.3 s to 12 s for an uncertain T-S fuzzy control system with time-delay, the norm of the feedback gains decreases from （34.299 2, 38.560 3） to （10.073 3, 11.349 0）, respectively. Meanwhile, the effectiveness of the proposed design method was illustrated by the last example with the robustly stable curves of system state under the initial condition of x（0） = [3 -1].

Robust H_∞ controller design for a class of nonlinear fuzzy time-delay systems

The problem of fuzzy modeling for state and input time-delays systems with a class of nonlinear uncertainties by fuzzy T-S model is addressed.By using the linear matrix inequality（LMI） method, the problem of fuzzy robust H ∞ controller design for the system is studied.Assuming that the nonlinear uncertain functions in the model considered are gain-bounded, a sufficient condition for the robustly asymptotic stability of the closed-loop system is obtained via Lyapunov stability theory.By solving the LMI, a feedback control law which guarantees the robustly asymptotic stability of the closed-loop system is constructed and the effect of the disturbance input on the controlled output is ruduced to a prescribed level.

Adaptive Fuzzy Backstepping Output Feedback Control of Nonlinear Time-delay Systems with Unknown High-frequency Gain Sign

In this paper, an adaptive fuzzy robust feedback control approach is proposed for a class of single-input and singleoutput （SISO） strict-feedback nonlinear systems with unknown nonlinear functions, time delays, unknown high-frequency gain sign, and without the measurements of the states. In the backstepping recursive design, fuzzy logic systems are employed to approximate the unknown smooth nonlinear functions, K-filters is designed to estimate the unmeasured states, and Nussbaum gain functions are introduced to solve the problem of unknown sign of high-frequency gain. By combining adaptive fuzzy control theory and adaptive backstepping design, a stable adaptive fuzzy output feedback control scheme is developed. It has been proven that the proposed adaptive fuzzy robust control approach can guarantee that all the signals of the closed-loop system are uniformly ultimately bounded and the tracking error can converge to a small neighborhood of the origin by appropriately choosing design parameters. Simulation results have shown the effectiveness of the proposed method.

Robust H_∞ control for fuzzy descriptor systems with state delay

The problem of robust H ∞ fuzzy state feedback control for uncertain fuzzy descriptor systems with state delay is solved. In the case that time-varying uncertainties are in all parameter matrices, sufficient conditions for the existence of fuzzy state feedback controller are presented in terms of linear matrix inequality (LMI). The proposed robust H ∞ control laws guarantee that the resulting closed-loop system is regular, impulse free, and stable with prescribed H ∞ norm bounded constraint for all admissible uncertainties. Finally, a numerical example is provided to demonstrate the validity of the proposed method.

Application of the Adaptive Neuro-Fuzzy Inference System for Optimal Design of Reinforced Concrete Beams

Using a genetic algorithm owing to high nonlinearity of constraints, this paper first works on the optimal design of two-span continuous singly reinforced concrete beams. Given conditions are the span, dead and live loads, compressive strength of concrete and yield strength of steel;design variables are the width and effective depth of the continuous beam and steel ratios for positive and negative moments. The constraints are built based on the ACI Building Code by considering the strength requirements of shear and the maximum positive and negative moments, the development length of flexural reinforcement, and the serviceability requirement of deflection. The objective function is to minimize the total cost of steel and concrete. The optimal data found from the genetic algorithm are divided into three groups: the training set, the checking set and the testing set for the use of the adaptive neuro-fuzzy inference system (ANFIS). The input vector of ANFIS consists of the yield strength of steel, compressive strength of concrete, dead load, span, width and effective depth of the beam;its outputs are the minimum total cost and optimal steel ratios for positive and negative moments. To make ANFIS more efficient, the technique of Subtractive Clustering is applied to group the data to help streamline the fuzzy rules. Numerical results show that the performance of ANFIS is excellent, with correlation coefficients between the three targets and outputs of the testing data being greater than 0.99.

I-Fuzzy拓扑空间中的θ-连续函数

利用R-邻域系在I-fuzzy拓扑空间中定义θ-闭包、θ-内部、Rθ-邻域系和θ-连续函数,并且研究它们的一些性质。

Fuzzy系统的函数逼近功能及误差估计

揭示Fuzzy系统的函数逼近功能以及逼近效果的误差估计.首先,相对于不确定性系统,描述如何获得一个Fuzzy系统的思路和方法,它视为对一个不确定系统的逼近.然后指出,对于任意给定的一个不确定性系统,总能将它转化为一组Fuzzy推理规则,由此可构造一个Fuzzy系统,并且证明这样构造的Fuzzy系统能逼近给定的连续函数到指定的精度.随后,通过几个实例展示了Fuzzy系统逼近连续函数的性能和效果.

I-fuzzy拓扑空间中的准连续映射

给出了I-fuzzy拓扑空间中准开算子、准拟重邻域系的定义,并讨论了I-fuzzy拓扑空间中的准连续映射的性质。

Robust stability analysis of singular linear system with delay and parameter uncertainty

This paper deals with the problem of robust stability for continuous-time singular systems with state delay and parameter uncertainty. The uncertain singular systems with delay considered in this paper are assumed to be regular and impulse free.By decomposing the systems into slow and fast subsystems,a robust delay-dependent asymptotic stability criteria based on linear matrix inequality is proposed, which is derived by using Lyapunov-Krasovskii functionals, neither model transformation nor bounding for cross terms is required in the derivation of our delay-dependent result. The robust delay-dependent stability criterion proposed in this paper is a sufficient condition. Finally, numerical examples and Matlab simulation are provided to illustrate the effectiveness of the proposed method.

Improved adaptive fuzzy control for MIMO nonlinear time-delay systems

This paper presents an improved observer-based indirect adaptive fuzzy control scheme for multiinput-multioutput (MIMO) nonlinear time-delay systems.The control scheme synthesizes adaptive fuzzy control with adaptive fuzzy identification.An observer is designed to observe the system state,and an identifier is developed to identify the unknown parts of the system.The update laws for parameters utilize two types of errors in the adaptive time-delay fuzzy logic systems,the observation error and the identification error.Performance analysis proves the superiority of the update laws in terms of faster and improved tracking and parameter convergence.Simulation results of two-link manipulator demonstrate the effectiveness of the improved control scheme.

Energy-to-peak control for a class of discrete stochastic fuzzy systems with time-delay

This paper considers the problem of stochastic stabilization and energy-to-peak control for a class of discrete stochastic fuzzy systems with interval time-delays. The objective is to design a state feedback controller such that the closed-loop system is stochastic stable and satisfies energy-to-peak performance. Based on the idea of interval partitioning, some new sufficient conditions are presented in LMI.

Cooperative adaptive fuzzy control for a class of uncertain non-linear multi-agent systems with time delays

This paper studies the robust adaptive fuzzy cooperative tracking control problem for a class of uncertain non-linear multi-agent systems with multiple time delays and dead-zone non-linearities.First,based on the implicit function theorem,the non-affine form of the multi-agent system can be converted into the corresponding affine form.Then,using the local state information of neighbouring agents,a novel adaptive fuzzy cooperative tracking controller with the corresponding parameter-updated laws is designed based on undirected communication topologies.Furthermore,it is shown that all the closed-loop signals are bounded,and all follower nodes asymptotically tracking to the leader can be achieved in the presence of time-delayed perturbations and unknown dead-zone inputs.Finally,simulation results are given to demonstrate the effectiveness of the proposed adaptive control scheme.

New approaches to delay-dependent robust H_(∞) control of uncertain discrete-time T-S fuzzy systems with time-varying delay

This paper investigates the problem of delaydependent robust H_(∞) state-feedback control for a class of uncertain discrete-time state-delayed T-S fuzzy systems.The state delay is assumed to be time-varying and of an interval-like type with the lower and upper bounds.The parameter uncertainties are assumed to have a structured linear-fractional form.Based on a novel fuzzy-basisdependent Lyapunov-Krasovskii functional incorporating a free-weighting matrix approach,some new delaydependent sufficient conditions for robust H_(∞) performance analysis and controller synthesis are derived in terms of linear matrix inequalities(LMIs).Numerical examples are also provided to illustrate the effectiveness of the proposed approaches.

连续变量/离散变量混合因果图推理模型研究

针对因果图理论没有对于连续性问题进行理论上的研究的情况,根据因果图知识表达的特点,本文立足于模糊逻辑的方法,对变量的连续性问题、因果关系的连续性问题进行研究,通过理论分析提出了完整的解决方法,实现了同时兼容连续、离散问题的混合推理因果图模型,并完整地建立了清华大学北京核电模拟机的故障诊断连续／离散混合模型,将其二回路的15种故障全部正确定位,体现了因果图理论以及本文提出的连续／离散混合处理方式的有效性.

脑电中癫痫波的自动检测与分类──一种分层次、多方法整合的途径

脑电中癫痫波的自动检测与分类是临床上很有意义的工作。本文采用一种‘分层次、多方法整合’途径，把自适应预测、小波变换、人工神经网络、模糊识别、专家系统等信号处理技术有机地结合在处理的不同层次（如初筛、分解、特征提取、识别与分类等）上，建立起一种新的分析框架。

车辆无级变速器液压系统的模糊控制

研究了金属带式汽车无级变速器机液控制无级变速系统的性能缺陷 ,提出了一种使用电液控制的无级变速方案。模拟驾驶员的思维设计了模糊控制策略 ,并对系统进行仿真分析和试验验证。仿真结果表明模糊控制策略是可行和有效的 ,试验证明采用模糊控制策略误差可控制在 2 .5 %以内。

基于真空泵的正负压连续控制系统

提出采用真空泵构造正负压连续控制系统,基于该系统数学模型,完成了其特性仿真研究分析,采用模糊PID控制方法,对系统特性进行详细探讨和试验研究。仿真和试验结果表明,基于真空泵的正负压连续控制系统具有良好的动态和静态特性,鲁棒性强,对系统参数变化有一定的灵活性,能够较好地满足系统高精度高响应的要求。试验结果同时也证明了系统数学模型的正确性。

一类模糊系统的逼近问题

讨论了一般模糊系统对任意连续函数的逼近问题 .找到了一类更一般的模糊系统 ,在这一类模糊系统中 ,对于任意给定的连续函数 ,总可以构造出一模糊系统 ,它可以按任意精度逼近该连续函数 ;得到了模糊划分与逼近精度之间的关系 ;此外还将主要定理推广到了Lp(1≤p <∞ )

炼钢连铸混合智能调度方法及其应用

在炼钢连铸生产工艺约束条件下,针对多设备、多工序、以及生产类型复杂的生产环境,目前还难以在合理时间内获得最优调度解,提出了基于规则的专家调度方法、基于规划的两阶段调度方法和基于多级模糊综合评价方法的混合智能调度方法,并在合理时间内得到一个有效的可行解。应用混合智能调度方法建立了智能调度架构,设计并开发了软件系统。该系统应用于国内某大型钢厂的生产调度,在缩短计划编制时间、减少钢水等待时间、提高设备利用率方面获得显著经济效益。