基于T-S模糊模型非线性网络控制系统改进H∞跟踪控制

研究一类非线性网络控制系统改进H∞跟踪控制问题, 该类网络控制系统中非线性被控对象和被跟踪对象分别采用Takagi-Sugeno(T-S)模糊模型和线性稳定参考模型描述. 首先通过综合考虑网络中的数据传输时滞和数据丢包影响, 采用输入时滞法和并行分布补偿技术, 建立基于零阶保持器刷新时刻的系统状态跟踪误差模型. 然后利用改进的自由权矩阵方法, 并结合Lyapunov直接法给出系统满足H∞跟踪性能的充分条件以及模糊控制器的设计方法. 最后仿真实例表明本文方法的有效性和相比已有方法的优越性.     

Multi-objective PID control for non-Gaussian stochastic distribution system based on two-step intelligent models

A new method for controlling the shape of the conditional output probability density function (PDF) for general nonlinear dynamic stochastic systems is proposed based on B-spline neural network (NN) model and T-S fuzzy model. Applying NN approximation to the measured PDFs, we transform the concerned problem into the tracking of given weights. Meanwhile, the complex multi-delay T-S fuzzy model with exogenous disturbances, parametric uncertainties and state constraints is used to represent the nonlinear weigh...     

Predictive functional control based on fuzzy T-S model for HVAC systems temperature control

In heating, ventilating and air-conditioning (HVAC) systems, there exist severe nonlinearity, time-varying nature, disturbances and uncertainties. A new predictive functional control based on Takagi-Sugeno (T-S) fuzzy model was proposed to control HVAC systems. The T-S fuzzy model of stabilized controlled process was obtained using the least squares method, then on the basis of global linear predictive model from T-S fuzzy model, the process was controlled by the predictive functional controller. Especially the feedback regulation part was developed to compensate uncertainties of fuzzy predictive model. Finally simulation test results in HVAC systems control applications showed that the proposed fuzzy model predictive functional control improves tracking effect and robustness. Compared with the conventional PID controller, this control strategy has the advantages of less overshoot and shorter setting time, etc.     

Predictive functional control based on fuzzy T-S model for HVAC systems temperature control

In heating, ventilating and air-conditioning （HVAC） systems, there exist severe nonlinearity, time-varying nature, disturbances and uncertainties. A new predictive functional control based on Takagi-Sugeno （T-S） fuzzy model was proposed to control HVAC systems. The T-S fuzzy model of stabilized controlled process was obtained using the least squares method, then on the basis of global linear predictive model from T-S fuzzy model, the process was controlled by the predictive functional controller. Especially the feedback regulation part was developed to compensate uncertainties of fuzzy predictive model. Finally simulation test results in HVAC systems control applications showed that the proposed fuzzy model predictive functional control improves tracking effect and robustness. Compared with the conventional PID controller, this control strategy has the advantages of less overshoot and shorter setting time, etc.     

Robust L1 output tracking control for uncertain networked control systems described by T-S fuzzy model with distributed delays

This paper concentrates on investigating the robust L₁ output tracking control problem for the networked control systems described by Takagi–Sugeno fuzzy model with distributed delays and uncertainties. First, according to the parallel distributed compensation and Lyapunov theory, a fuzzy delay-dependent and basis-dependent Lyapunov–Krasovskii function that contributes to reducing the conservatism is constructed. Second, the L₁ performance criterion guaranteeing the asymptotic stability of the corresponding tracking control system and satisfying the prescribed tracking performance is derived. Furthermore, the output tracking control problem is converted into a convex optimisation problem. Finally, the results from simulation certify the effectiveness of the designed controller.     

基于T-S模糊模型的状态反馈预测控制

将T-S模糊模型和状态反馈预测控制相结合,提出了一种基于T-S模糊模型的预测控制算法.该算法把T-S模糊模型作为预测模型得到状态和输出的预估值,并利用可测的过程变量对输出预估值进行反馈修正,然后利用最优控制理论,由修正后的预估值和给定值计算出控制整个系统的控制律.本文还对串级CSTR控制系统的不同的初态、设定值及干扰情况下进行了仿真,仿真结果表明了该方法的有效性和可行性.     

Controller design of uncertain nonlinear systems based on T-S fuzzy model

A robust control for uncertain nonlinear systems based on T-S fuzzy model is discussed in this paper. First, a T-S fuzzy system is adopted to model the uncertain nonlinear systems. Then, for the system with input variables adopting standard fuzzy partitions, the efficient maximal overlapped-rules group （EMORG） is presented, and a new sufficient condition to check the stability of T-S fuzzy system with uncertainty is derived, which is expressed in terms of Linear Matrix Inequalities. The derived stability condition, which only requires a local common positive definite matrix in each EMORG, can reduce the conservatism and difficulty in existing stability conditions. Finally, a simulation example shows the proposed approach is effective.     

基于T-S 模糊模型的网络控制系统非脆弱H∞ 跟踪控制

针对一类T-S 模糊模型描述的网络控制系统(NCSs) 非脆弱H_∞跟踪控制问题进行研究. 首先, 综合考虑网络中数据传输时滞和数据丢包的影响, 采用输入时滞法和并行分布补偿(PDC) 技术, 建立基于T-S 模糊模型的NCSs 状态跟踪误差模型; 然后, 利用Lyapunov 方法和改进的自由权矩阵方法, 基于线性矩阵不等式(LMI), 给出满足系统H_∞ 跟踪性能的条件, 并给出非脆弱模糊控制器设计方法; 最后, 通过仿真实例表明了该方法的有效性.     

Guaranteed cost control for T-S fuzzy systems with time-varying delays

This paper deals with the problem of guaranteed cost control for nonlinear systems with time-varying delays which is represented by Takagi-Sugeno (T-S) fuzzy models with time-varying delays. The derivatives of timevarying delay are not necessary to be bounded. Based on the free weighting matrix method, sufficient conditions for the existence of fuzzy guaranteed cost controller via state feedback are given in terms of linear matrix inequalities (LMIs). A minimizing method is also proposed to search the suboptimal upper bound of the guaranteed cost function. The results are delay-dependent but contain delay-independent criteria as a special case. A numerical example is presented to demonstrate the effectiveness and less conservativeness of our work.     

离散T-S模糊广义系统的H∞控制

研究了离散T-S模糊广义系统的H_∞控制问题. 首先引入辅助矩阵变量得到新的容许性条件, 解决了由于矩阵P的不定性, 无法运用Schur补引理处理非线性Lyapunov不等式的问题, 进而得到严格不等式表示的H_∞控制条件.基于模糊Lyapunov函数方法, 分别研究了状态反馈控制器、静态输出反馈控制器、动态输出反馈控制器的构造方法. 所得结论可推广到系统具有范数有界不确定性的情况. 最后通过算例验证方法的有效性.     

基于T-S模型的轮式移动机器人轨迹跟踪控制

针对带有执行机构饱和约束与外部干扰的轮式移动机器人,提出了一种基于T-S模糊模型的轨迹跟踪方法.利用机器人运动特性和参考轨迹建立轨迹跟踪的误差系统并将其作T-S模型描述.通过求解具有LMI约束的半定规划问题,对每个线性子系统单独设计满足控制约束与H∞性能约束的状态反馈控制器,并在PDC(动态平行分配补偿)设计框架下构建全局控制器,最后证明闭环系统的李雅普诺夫稳定性.仿真结果验证了该方法的有效性和可行性.     

基于T-S模型的非线性系统非脆弱极小极大控制

研究一类非线性离散系统的鲁棒非脆弱极小极大控制问题.针对含有不确定项的非线性离散系统,构造T-S模型,引入参数不确定项,使得模糊模型能够更精确逼近原系统.考虑系统和控制器同时含有不确定性,利用线性矩阵不等式(LMI)处理方法和Lyapunov稳定性理论,设计鲁棒且非脆弱的控制器.考虑不确定性使得性能指标最大的情形,得到极小极大鲁棒非脆弱控制器存在的充分条件.引入凸优化算法,求解使闭环系统渐近稳定且性能指标上界最小的最优极小极大鲁棒控制器的参数.最后以著名的truck-trailer模型为例的仿真结果表明所设计的控制器具有良好的鲁棒性和非脆弱性.     

基于T-S模型的自校正模糊PID控制器的设计

基于Takagi和Sugeno的模糊控制模型，设计了基于T-S模型的积分分离算法的模糊PID控制器，同时引入了继电反馈控制进行模糊PID控制器初始值的整定，实现了自校正模糊PID控制器。通过对工业过程的时滞对象的数字仿真分析表明，该控制器获得了很好的静动态性能、鲁棒性和抗干扰能力，为实现自动型控制器提供了简单而又实用的新方法。     

连续T-S模糊系统的严格二次型耗散控制

研究一类连续Ｔ-Ｓ模糊系统的严格二次型耗散控制问题,给出了保证系统严格二次型耗散稳定的状态反馈控制器的设计方法．控制器可通过求解一组线性矩阵不等式获得,所得结果不仅提供了解决犎∞ 控制与正实控制的统一框架,而且提供了一种更灵活、保守性更小的控制器设计方法．最后通过仿真说明了所提出方法的有效性、可行性和优越性．     

离散T-S 模糊系统的稳定条件

针对应用公共Lyapunov函数方法、模糊Lyapunov函数方法和分段模糊Lyapunov函数方法进行T-S模糊系统稳定性分析的保守性问题,通过定义有效最大交叠规则组,并基于离散型分段模糊Lyapunov函数,提出一个判定开环离散T-S模糊系统稳定性的充分条件.该条件仅需在每个有效最大交叠规则组内分别满足模糊Lyapunov方法中的条件,从而降低上述判定方法的保守性和难度.仿真实例验证了所提出条件的有效性和优越性.     

Fuzzy tracking control design for hypersonic vehicles via T-S model

The main focus of this paper is on designing a T-S fuzzy controller for the hypersonic vehicle. The longitudinal dynamics of the vehicle are studied using time-scale decomposition to reduce the complexity of T-S modeling. The dynamic inversion with PI control technique is applied for the slow dynamics to derive the flight path angle command and throttle setting by taking the pilot altitude and velocity command as its inputs. The T-S fuzzy controller is designed for the fast dynamics to derive the elevator d...     

Minimum rational entropy fault tolerant control for non-Gaussian singular stochastic distribution control systems using T-S fuzzy modelling

In this paper, a new fault diagnosis (FD) and fault tolerant control (FTC) algorithm for a non-Gaussian nonlinear singular stochastic distribution control (SDC) system is studied. The rational square-root fuzzy logic model is used to approximate the output probability density function of non-Gaussian processes and a Takagi-Sugeno (T-S) fuzzy model is employed to transform the non-Gaussian nonlinear SDC system into a fuzzy SDC system. An adaptive fuzzy fault diagnosis observer is constructed to achieve reconstruction of system state and fault. Based on the estimated fault information, the controller is reconfigured by minimising the performance index with regard to the rational entropy subjected to mean constraint. Minimum rational entropy fault tolerant control is introduced to make the output of the past-fault SDC system still have the minimum uncertainty. Simulation results are provided to demonstrate the validity of the FD and minimum rational entropy FTC algorithm.     

隶属度函数相关的不确定T-S模糊系统的保成本控制

研究了一类带有参数不确定性模糊T-S系统的状态反馈保成本控制问题。通过使用阶梯隶属度函数来近似模糊模型和控制器的隶属度函数,应用Lyapunov稳定性理论,得到了一组新的隶属度函数相关的系统渐近稳定充分条件,该条件可用线性矩阵不等式(LMIs)表示。最后通过仿真验证了该方法的有效性,结果表明,通过取得较小的阶梯宽度,系统可以具有更小的保守性和更好的动态性能。     

Event-triggered controller design of nonlinear discrete-time networked control systems in T-S fuzzy model

This article is concerned with event-triggered fuzzy control design for a class of discrete-time nonlinear networked control systems (NCSs) with time-varying communication delays. Firstly, a more general mixed event-triggering scheme (ETS) is proposed. Secondly, considering the effects of the ETS and communication delays, based on the T-S fuzzy model scheme and time delay system approach, the original nonlinear NCSs is reformulated as a new event-triggered networked T-S fuzzy systems with interval time-varying delays. Sufficient conditions for uniform ultimately bound (UUB) stability are established in terms of linear matrix inequalities (LMIs). In particular, the quantitative relation between the boundness of the stability region and the triggering parameters are studied in detail. Thirdly, a relative ETS is also provided, which can be seen as a special case of the above proposed mixed ETS. As a difference from the preceding results, sufficient conditions on the existence of desired fuzzy controller are derived to ensure the asymptotic stability of the closed-loop system with reduced communication frequency between sensors and controllers. Moreover, a co-design algorithm for simultaneously determining the gain matrices of the fuzzy controller and the triggering parameters is developed. Finally, two illustrative examples are presented to demonstrate the advantage of the proposed ETS and the effectiveness of the controller design method.