基于线性矩阵不等式的磁悬浮轴承多目标控制系统设计

首先建立了磁悬浮轴承局部子系统线性Takagi- Sugeno(TS)模糊模型，利用单点模糊化、乘积推理和加权平均得到整个系统的非线性模型。针对以往非线性系统的单目标控制设计，提出了基于线性矩阵不等式(LMI)的多目标模糊控制系统的设计方法。该方法将闭环控制系统的稳定性、抗干扰性及极点配置的要求统一到1个线性矩阵不等式组中，通过求解线性矩阵不等式组获得满足要求的控制器参数，利用并行分布补偿控制(PDC)方法得到整个系统的非线性模糊状态反馈控制器，实现了系统同时满足多目标的要求，并且避免了设计过程的多次反复。应用于磁悬浮轴承非线性系统的控制中，通过实验验证了该设计方法的有效性。     

Takagi-Sugeno tracking control of a fermentation process with respect to asymmetric constraints

This article deals with the tracking problem for nonlinear biological process with asymmetric constraints on the controller. Using the fuzzy logic Takagi-Sugeno (TS), the nonlinear process is modeled by a fuzzy model and a parallel distributed compensation (PDC) controller with respect asymmetric constraints is designed. The main contribution of this work is to extend the available results, in the context of a TS formulation, for symmetrical constraints to asymmetrical ones. Hence, sufficient conditions are obtained for the first time, in terms of linear matrix inequalities (LMIs), for the existence of an asymmetrical constrained PDC controller. Moreover, fuzzy observer based controller with unmeasured premise variables is designed. The performance and effectiveness of the method are illustrated in simulation by considering a fermentation process.     

Fuzzy bilinear state feedback control design based on TS fuzzy bilinear model for DC–DC converters

This paper proposes a fuzzy bilinear state feedback controller based on Tagaki–Sugeno (TS) fuzzy bilinear model for DC–DC converters. The DC–DC converters can be approximated to bilinear model via Taylor series expansion. For achieving the output voltage regulation, we formulate the extended system of bilinear DC–DC converter model, one of whose state variables is the error between the output voltage and the reference output voltage. The extended system can be described to TS fuzzy bilinear model. We design a fuzzy bilinear state feedback controller to track the reference output voltage. The closed loop system is globally asymptotically stable via the proposed controller. Lyapunov theory is employed to guarantee the stability of the closed loop system. Numerical examples are given to demonstrate the validity of our proposed control approach with comparative results.     

Robust nonlinear control of wind energy conversion systems

This paper presents stability analysis for a class of uncertain nonlinear systems and a method for designing robust fuzzy controllers to stabilize the uncertain nonlinear systems. First, the Takagi–Sugeno (TS) fuzzy model is adopted for fuzzy modeling of the uncertain nonlinear system. Next, new stability conditions for a generalized class of uncertain systems are derived from robust control techniques such Linear Matrix Inequalities (LMIs). The derived stability conditions are used to analyze the stability of Takagi and Sugeno’s fuzzy control systems with uncertainty which can be regarded as a generalized class of uncertain nonlinear systems. The design method employs the so-called Parallel Design Approach (PDA). TS fuzzy systems are classified into three families based on the input matrices and a robust fuzzy controller’s synthesis procedure is given for each family. In each family, sufficient conditions are derived for robust stabilization in the sense of Taylor series stability, for the TS fuzzy system with parametric uncertainties. Important issues for the stability analysis and design are remarked. The effectiveness of the proposed controller design methodology is finally demonstrated through the two different models of Wind Energy Systems (WES) to illustrate the effectiveness of the proposed method.     

输入受限的非线性系统模型预测控制

基于模糊T—S模型对输入受限的非线性离散系统,提出了模型预测控制,导出了预测控制性能指标上界,将稳定性约束、输入约束变换成容易求解的线性矩阵不等式(LMIs)形式。采用了状态反馈控制器和并行补偿分布控制器(PDC),基于李雅普诺夫函数和线性矩阵不等式方法给出滚动时域优化的充分条件,证明了闭环系统的稳定性。仿真结果验证了所提方法的有效性。     

带电压调节功能的非线性鲁棒控制器

提出了一种既可增加多机电力系统暂态稳定性又可达到机端输出电压调节功能的非线性鲁棒控制器。该控制器由一个直接反馈线性化（DFL）控制器和一个比例积分（PI）控制器组成。DFL控制器用于降低多机电力系统的非线性程度以及各机之间的相互作用。所提控制器设计方法既可保证系统稳定性又可达到调节电压的目的,同时在实现时不需要测量发电机功角。仿真结果表明,所提出的方案可在很宽的运行范围内增加系统的阻尼及稳定性。     

Power system transient stability enhancement by STATCOM with nonlinear H∞ stabilizer

A robust control design is presented for a single machine infinite bus system (SMIB) with a STATCOM. The controller for the nonlinear system is designed using the recently developed nonlinear H_∞ theory. The approach combines state feedback exact linearization with linear H_∞ principle, which avoids the difficulty of solving Hamilton–Jacoby–Issacs inequality. Simulation results with a number of disturbances like torque pulses and three-phase faults on the generator show that the proposed robust controller can ensure transient stability of the power system over a wide range of operating points     

A decentralized nonlinear feedback controller with prescribed degree of stability for damping power system oscillations

Nonlinear feedback linearization techniques are being used for transforming nonlinear power system dynamics into closed loop systems, whose dynamics are linear over wide range of operating conditions. This facilitates use of linear techniques for designing feedback controllers to damp out oscillations. The advantage of using such feedback controllers is that they do not depend on the system operating conditions unlike the conventional controllers, for example a conventional power system stabilizer. A nonlinear feedback law is proposed in this work, which converts a nonlinear power system into closed loop decentralized linear time varying systems. A feedback controller has been designed using linear quadratic regulator with prescribed degree of stability to stabilize the decentralized linear time varying systems. The performance of the proposed method has been tested on a 16-machine, 68-bus system representing interconnected New England Test system (NETS) and New York Power System (NYPS).     

The optimal fuzzy robust regulator for TS discrete‐time systems: An LMI approach

In this work, the problem of designing an optimal regulator for discrete‐time nonlinear systems when the plant can be modelled by a Takagi–Sugeno (TS) fuzzy system is addressed. The approach analyzed in this paper, under certain conditions, guarantees the tracking of references and allows the performance of the controller to be improved by means of the inclusion of some cost functions. The main result is given in terms of linear matrix inequality techniques, meaning that the design of the controller can be obtained in a practical way. Finally, numerical simulations are carried out in order to illustrate the validity of the fuzzy regulator. Copyright © 2008 John Wiley & Sons, Ltd.     

Adaptive TS‐FNN control for a class of uncertain multi‐time‐delay systems: The exponentially stable sliding mode‐based approach

This paper presents an adaptive Takagi–Sugeno fuzzy neural network (TS‐FNN) control for a class of multiple time‐delay uncertain nonlinear systems. First, we develop a sliding surface guaranteed to achieve exponential stability while considering mismatched uncertainty and unknown delays. This exponential stability result based on a novel Lyapunov–Krasovskii method is an improvement when compared with traditional schemes where only asymptotic stability is achieved. The stability analysis is transformed into a linear matrix inequalities problem independent of time delays. Then, a sliding mode control‐based TS‐FNN control scheme is proposed to achieve asymptotic stability for the controlled system. Since the TS‐FNN combines TS fuzzy rules and a neural network structure, fewer numbers of fuzzy rules and tuning parameters are used compared with the traditional pure TS fuzzy approach. Moreover, all the fuzzy membership functions are tuned on‐line even in the presence of input uncertainty. Finally, simulation results show the control performance of the proposed scheme. Copyright © 2008 John Wiley & Sons, Ltd.     

Nonlinear single-loop control of the parallel converters for a fuel cell power source used in DC grid applications

This paper presents an innovative control law for a multiphase interleaved converter in the distribution of power supply in fuel cell (FC) generators. Traditionally, to control the DC output power, voltage, or current in a converter, a linear multiple-loop feedback control technique is used. The nonlinear multiple-loop feedback control approach offers several techniques that help to improve the system response. In this paper, an alternative nonlinear single-loop feedback control scheme is proposed. This scheme is based on the differential flatness concept, which provides a solution to achieve the preferred response using a less sophisticated algorithm. To validate the proposed technique, a prototype of a FC power converter (a 600-W two-phase interleaved boost DC–DC converter) was constructed in the laboratory, and the control algorithm was implemented to control the prototype using a dSPACE 1104 controller card. The control scheme exhibited excellent experimental results for use with a 1.2-kW Nexa Ballard polymer electrolyte membrane fuel cell (PEMFC) regarding the steady state and dynamic responses as well as the control robustness.     

参数不确定Chen混沌系统鲁棒模糊控制器的设计

基于TS(Takagi-Sugeno)模糊模型，研究具有参数不确定性Chert混沌系统的鲁棒控制器设计。首先构建含有参数不确定性的TS模糊模型：然后利用并行分布补偿的方法，设计使模糊系统在平衡点附近渐近稳定的鲁棒模糊控制器。该设计通过解一组线性矩阵不等式(LMI)得到局部区域控制器，进而设计TS模糊系统的鲁棒控制器。该鲁棒模糊控制器的渐近稳定性条件更为宽松，能够降低控制器设计的保守性。最后的仿真结果表明所设计的鲁棒模糊控制器对参数不确定Chert混沌系统具有良好的控制效果。     

Decentralized nonlinear H∞ controller for large scale power systems

The aim of this paper is to design nonlinear decentralized controllers for multi-machine power systems. The design procedure is based on H_∞ control theory and consists of two parts. First, the feedback linearization technique is used. Then, a robust controller is designed using the linear matrix inequalities (LMI) approach. The controller has two blocks. One, is a nonlinear function of some local measurable signals such as the generator active and reactive powers, the rotor speed and the armature current. The other block is a PID controller. The linear H_∞ theory is used to tune the PID parameters. The method results in a controller which is easy for implementing in practice. The performance of the controller is tested on a sample multi-machine power system model. Simulation results show the effectiveness, robustness and good performance of the proposed controller.     

多机系统快速汽门非线性控制研究

首先介绍了最优控制系统综合的李雅普诺夫方法和一种简单实用的非线性系统大 范围线性化方法，然后将之成功地应用于同步发电机快速汽门控制器的设计，避免了构造 非线性系统李雅普诺夫函数的困难，为电力系统暂态稳定控制的研究作出了新的探索。获得 的控制器完全基于当地量的反馈，易于工程上在线实现。     

具有非线性输入的鲁棒自适应模糊滑模控制

针对一类具有死区非线性输入的SISO非线性系统,基于滑模控制原理,提出了一种稳定自适应模糊控制器设计方案.该方案通过使用积分型Lyapunov函数避免了反馈线性化方法中可能出现的控制器奇异性问题,运用两阶段法构造两个Lyapunov函数,确定出用于建模的有界闭区域,再证明跟踪误差收敛到零.通过理论分析,证明了闭环控制系统全局一致终结有界;仿真结果表明了该方法的有效性.     

考虑非线性负荷的静止无功补偿器控制研究

针对电力系统具有非线性负荷的情况下，在经典的非线性系统几何结构理论的发展基础上，结合非线性系统微分几何理论，提出了关于微分代数系统的M导数、M括号等一些新的概念和定义，并详细推导了微分代数系统的完全精确线性化设计。然后将其应用于具有非线性负荷的电力系统静止无功补偿器的控制，得到了非线性控制规律。仿真结果表明，所设计的静止无功补偿器非线性控制器与常规PID控制相比，具有较好的阻尼特性和电压维持能力，同时，由于该设计计及了负荷的变化，从而更接近于实际情况。     

Direct adaptive neural control of nonlinear strict‐feedback systems with unmodeled dynamics using small‐gain approach

In this paper, a novel direct adaptive neural control approach is presented for a class of single‐input and single‐output strict‐feedback nonlinear systems with nonlinear uncertainties, unmodeled dynamics, and dynamic disturbances. Radial basis function neural networks are used to approximate the unknown and desired control signals, and a direct adaptive neural controller is constructed by combining the backstepping technique and the property of hyperbolic tangent function. It is shown that the proposed control scheme can guarantee that all signals in the closed‐loop system are semi‐globally uniformly ultimately bounded in mean square. The main advantage of this paper is that a novel adaptive neural control scheme with only one adaptive law is developed for uncertain strict‐feedback nonlinear systems with unmodeled dynamics. Simulation results are provided to illustrate the effectiveness of the proposed scheme. Copyright © 2015 John Wiley & Sons, Ltd.     

基于模糊控制补偿的支持向量机逆模型控制

支持向量机(SVM)具有很强的非线性逼近能力与泛化能力,文章研究了基于SVM的非线性系统逆模型辨识,并设计了基于模糊控制补偿的SVM逆控制系统.由SVM辨识的逆模型作为前馈控制器,形成直接逆模型控制器.同时,设计模糊控制器构成反馈补偿控制,克服逆模型的建模误差,提高系统鲁棒稳定性.仿真研究表明,SVM具有优良的逆模型辨识能力,基于模糊控制补偿的支持向量机逆控制系统的动态性能好、跟踪精度高、鲁棒稳定性强.     

Design and implementation of partial feedback linearizing controller for grid-connected fuel cell systems

This paper presents an approach to design a nonlinear controller for grid-connected fuel cell (FC) systems in order to provide ancillary services to low or medium voltage power networks. In this paper, these ancillary services mainly refer to the delivery of both active and reactive power from the FC to the grid under different operating conditions. The controller is designed based on the dynamical model of a proton exchange membrane fuel cell (PEMFC) which is developed from the electrical equivalent circuit of a grid-connected PEMFC through a voltage source converter (VSC). Partial feedback linearization technique is then employed to obtain the control laws with an aim of regulating respective currents related to both active and reactive power through the switching action of VSCs. The stability of the internal dynamics of the PEMFC system is also analyzed in this paper as the proposed control scheme cannot be implemented for unstable internal dynamics. A rate limiter is used with the proposed partial feedback linearizing controller to ensure the suitability under the worst-case conditions as well as to prevent the over-modulation in the rate of change of power references. The applicability and performance of the proposed controller is justified on a simple system as well as on a 12-bus balanced test distribution system and the CIGRE low voltage test distribution network under different grid events. The simulation results show the superiority of the proposed controller as compared to the vector controller.     

一类切换T-S型模糊系统二次镇定保成本控制

针对一类不确定切换T-S型模糊系统,对保成本鲁棒控制问题进行了研究。利用单Lyapunov函数法,给出了混杂状态反馈保成本控制器的设计方案,使得闭环系统对所有允许的不确定性,在所设计的混杂状态反馈控制器下是二次稳定的,应用线性矩阵不等式的可解性给出闭环系统二次稳定的充分条件,同时给出了二次型成本函数的一个上界。模型中的每个切换系统的子系统是不确定模糊系统,取常用的平行分布补偿PDC控制器,主要条件以凸组合的形式给出,具有较强的可解性。仿真结果验证了所设计方法的有效性。