Analytical analysis and feedback linearization tracking control ofthe general Takagi-Sugeno fuzzy dynamic systems

The Takagi-Sugeno (TS) fuzzy modeling technique, a black-box discrete-time approach for system identification, has widely been used to model behaviors of complex dynamic systems. The analytical structure of TS fuzzy models, however, is unknown, causing at two major problems. First, the fuzzy models cannot be utilized to design controllers of the physical systems modeled. Second, there is no systematic technique for designing a controller that is capable of controlling any given TS fuzzy model to achieve the desired tracking or setpoint control performance. In this paper, we provide solutions to these problems. We have proved that a general class of TS fuzzy models is a nonlinear time-varying ARX (Auto-Regressive with eXtra input) model. We have established a simple condition for analytically determining the local stability of the general TS fuzzy dynamic model. The condition can also be used to analytically check the quality of a TS fuzzy model and invalidate the model if the condition warrants. We have developed a feedback linearization technique for systematically designing an output tracking controller so that the output of a controlled TS fuzzy system of the general class achieves perfect tracking of any bounded time-varying trajectory. We have investigated the stability of the tracking controller and established a condition, in relation to the stability of non-minimum phase systems, for analytically deciding whether a stable tracking controller can be designed using our method for any given TS fuzzy system. Three numerical examples are provided to illustrate the effectiveness and utility of our results and techniques     

Experimental design of a fuzzy controller for improving power factor of boost rectifier

This article presents the design and the implementation of dSPACE DS1104 controller board-based PI and fuzzy logic peak current-mode controllers in the voltage loop and two controllers in the current loop based first on a standard fixed hysteresis band control, followed by a variable hysteresis band control to achieve constant switching frequency for a single-phase active power factor corrector in the continuous conduction mode. All these controllers have been verified via simulation in Simulink and a real-time implementation is performed on an experimental test bench utilising a rapid prototyping tool. The controllers are experimentally compared for steady-state performance and transient response. It is shown that the PI and fuzzy logic controllers give a superior steady-state performance, whereas the fuzzy logic inference based controller can achieve better dynamic response than its PI counterpart under large load disturbance and plant uncertainties. Furthermore, the variable hysteresis band control in the current loop gives a low total harmonic distortion of the input current compared to a standard fixed hysteresis band control.     

红外搜索跟踪系统伺服机构模糊-PID控制器设计及仿真研究

针对红外搜索跟踪系统中伺服机构常用的PID控制方法参数不易整定的缺点,将模糊控制和PID结合起来,构造一种模糊-PID控制器,使PID参数能进行在线调整,通过MATLAB下的仿真,从仿真结果中得出结论:模糊-PID比传统PID控制器具有更好的动态响应品质.响应时间、超调量、稳态精度及动、静态性能都得到了很大提高.从而验证了其有效性及实用性.     

Fuzzy Multi-model Switching H-Infinity Control for Helicopters in a Full Envelope

This paper presents a fuzzy multi-model switching H-infinity control law for a helicopter in a full envelope. The space of the nonlinear model for a helicopter is partitioned to some sub-spaces of the multiple linearized models using the fuzzy set theory. We use the genetic algorithm to design a local H-infinity controller for each linearized model of the helicopter at the different equilibrium point. The fuzzy logic strategy can handle smoothly the controller switching of the linearized models of the helicopter. The flight controller for the helicopter is synthesized using the proposed control law design technique. The simulation and performance evaluation show that the designed helicopter flight control can guarantee the smooth switching of control laws of the helicopter.     

一种基于PLC的模糊自适应PID控制器设计

通过对模糊自适应PID控制器设计过程的详细分析,提出了一种基于PLC查表方式实现模糊自适应PID控制器的方法,实现了基于PLC的自适应模糊PID控制器的设计,并应用于实际的控制系统中。结果表明,用PLC实现模糊自适应PID控制简单实用,适于工业控制系统应用。     

Multiobjective control of a vehicle with triple trailers

We consider the backing-up control of a vehicle with triple trailers using a model-based fuzzy-control methodology. First, the vehicle model is represented by a Takagi-Sugeno fuzzy model. Then, we employ the so-called "parallel distributed compensation" design to arrive at a controller that guarantees the stability of the closed-loop system consisted of the fuzzy model and controller. The control-design problem is cast in terms of linear matrix inequalities (LMIs). In addition to stability, the control performance considerations such as decay rate, constraints on input and output, and disturbance rejection are incorporated in the LMI conditions. In application to the vehicle with triple trailers setup, we utilize these LMI conditions to explicitly avoid the saturation of the steering angle and the jackknife phenomenon in the control design. Both simulation and experimental results are presented. Our results demonstrate that the fuzzy controller effectively achieves the backing-up control of the vehicle with triple trailers while avoiding the saturation of the actuator and "jackknife" phenomenon.     

基于单片机的双模糊温度控制器设计

传统的温度控制存在难以建立精确的数学模型以及控制性能较差等缺点,为此,在基本模糊控制理论基础上提出一种双输入单输出的双模糊温度控制器,根据系统不同的工作状态采用不同的模糊温度控制器。并结合单片机技术,设计了体积小、功能强的双模糊温度控制器,给出了温度控制器的硬件及软件设计思想与方法。该控制器简单易行,能有效改善温度控制性能,提高温度控制的稳定性。     

Using fuzzy controller for improvement of power decoupling performance in PV systems

ABSTRACT

In photovoltaic systems in order to ensure the stable operation of the module, ripple value of the input voltage should be mitigated to a small value; for this purpose, the power decoupling circuit can be used. In this work, considering the four-switch-based power decoupling circuit developed, the conventional Proportional-Integral (PI) controller has been replaced with well-known fuzzy controller, which enjoys a wide range of control gain variation, both linear and nonlinear rules' capability, robustness and more flexibility. The operating modes of the circuit are addressed and accordingly the space state model is derived. Then, the proposed controller has been replaced and the performance of the system will be analysed. The power decoupling circuit along with the proposed controller is implemented by MATLAB/Simulink software. The simulation results show the ability of the proposed fuzzy controller to improve the performance of the system in comparison to the conventional PI controller. A deeper comparison of two controllers confirms that the system would experience more accuracy, faster response and lower total harmonic distortion (THD) in presence of the proposed fuzzy controller.     

A QoS-provisioning neural fuzzy connection admission controller formultimedia high-speed networks

This paper proposes a neural fuzzy approach for connection admission control (CAC) with QoS guarantee in multimedia high-speed networks. Fuzzy logic systems have been successfully applied to deal with traffic-control-related problems and have provided a robust mathematical framework for dealing with real-world imprecision. However, there is no clear and general technique to map domain knowledge on traffic control onto the parameters of a fuzzy logic system. Neural networks have learning and adaptive capabilities that can be used to construct intelligent computational algorithms for traffic control. However, the knowledge embodied in conventional methods is difficult to incorporate into the design of neural networks. The proposed neural fuzzy connection admission control (NFCAC) scheme is an integrated method that combines the linguistic control capabilities of a fuzzy logic controller and the learning abilities of a neural network. It is an intelligent implementation so that it can provide a robust framework to mimic experts' knowledge embodied in existing traffic control techniques and can construct efficient computational algorithms for traffic control. We properly choose input variables and design the rule structure for the NFCAC controller so that it can have robust operation even under dynamic environments. Simulation results show that compared with a conventional effective-bandwidth-based CAC, a fuzzy-logic-based CAC, and a neural-net-based CAC, the proposed NFCAC can achieve superior system utilization, high learning speed, and simple design procedure, while keeping the QoS contract     

一种模糊-PI双模控制系统的仿真与设计

为了提高系统的控制性能,综合了模糊控制和PID控制的优点,提出一种基于模糊-PI双模控制器设计方法。典型的二维模糊控制器因缺少积分环节,难以消除稳态误差,控制的精度常常不能满足系统要求;而PI控制器具有良好的消除稳态误差的作用,所以将其与模糊控制器结合构成复合控制器。通过Matlab/Simulink仿真,结果表明,与经典的PID控制方式相比较,该控制方式在快速性、稳态性及准确性方面都有较大提高。     

基于改进Fuzzy-PID控制理论的无人机纵向飞控律设计

针对无人机飞行中存在大量的随机干扰和不确定误差等问题,常规的PID控制器不能满足高精度、高灵活性和强适应性的要求,提出了基于改进Fuzzy-PID控制理论的飞控律设计。该设计使用模糊规则下的切换开关来完成PID控制和Fuzzy控制输出量的加权,使控制具有两者的优点。通过调整模糊隶属度函数参数,可以得到系统的最佳控制方案。仿真结果表明:基于改进Fuzzy-PID控制理论的飞控律明显优于常规控制理论,具有较强的适应性和灵活性,在提高无人机的飞行控制系统性能上具有实际意义。     

十字路口模糊交通控制器的设计

介绍了一种基于模糊控制理论的十字路口模糊交通控制器的设计。针对当前城市交通系统中的被控对象具有较大的随机性和偶然性,引入了不需要建立精确数学模型的模糊控制。首先根据进道口的检测器测得车量的多少,由第1级模糊控制器确定下一执行相位;然后根据当前相位车量的多少以及下一相位车辆的多少由第2级模糊控制器确定当前执行相位的绿灯延长时间。较好地解决了交通流量不均衡、不稳定所带来的车辆延误等问题,提高了道路的通行能力。     

Evolutionary algorithms for fuzzy control system design

This paper provides an overview on evolutionary learning methods for the automated design and optimization of fuzzy logic controllers. In a genetic tuning process, an evolutionary algorithm adjusts the membership functions or scaling factors of a predefined fuzzy controller based on a performance index that specifies the desired control behavior. Genetic learning processes deal with the automated design of the fuzzy rule base. Their objective is to generate a set of fuzzy if-then rules that establishes the appropriate mapping from input states to control actions. We describe two applications of genetic-fuzzy systems in detail: an evolution strategy that tunes the scaling and membership functions of a fuzzy cart-pole balancing controller and a genetic algorithm that learns the fuzzy control rules for an obstacle-avoidance behavior of a mobile robot     

模糊控制在垂直发射导弹滚转回路中的应用

针对导弹在垂直发射过程中燃气舵复杂及非线性的特点,设计了一种模糊PID控制器控制三回路,该控制器将工作人员的经验结合其中,利用模糊控制理论能够在线实时整定PID参数,克服了传统PID控制器的一些缺点,通过Simulink仿真表明,该控制器可使性能得到明显改善。证明了该方法的有效性。     

A Novel FPSM Controller for DC-DC Switching Converters

This paper presents a novel fuzzy pulse skip modulation （FPSM） controller for switching direct current to direct current （DC-DC） converters based on fuzzy ratiocination modeling approach. Owing to the optimal consideration during the design and the nonlinear characteristics of the controller, improved dynamic responses of the FPSM controller can be achieved over conventional controllers. Compared with conventional proportion integral derivative （PID） control, FPSM control has 60% lower overshoot and 10% lower setting time under the same input voltage and output load change. The presented approach is general and can be applied to other types of DC-DC converters.     

智能PID控制器在仪表中的应用

针对传统PID在智能仪表中难以实现准确的参数自整定问题,提出了一种基于单层神经网络的模糊自适应PID控制器的设计方案,该方案将单层神经网络用于模糊规则的建立和推理,使模糊控制具有自学习功能,可更好地适应复杂控制系统的参数自整定.通过MATLAB/SIMULINK平台,对其进行了仿真研究,仿真结果表明,该方案具有较好的鲁棒性、稳定性和实时性.     

Fuzzy fundamentals

An orderly design procedure that can save time and help prevent problems in the development of fuzzy logic systems is presented. The nature of fuzzy logic is examined, and the design of fuzzy control systems is discussed. The architecture of a simple fuzzy controller for a steam turbine is used as an example, to show how fuzzy control models work. A four-step methodology for fuzzy system design is described     

A two-layered fuzzy logic controller for systems with deadzones

Existing fuzzy control methods do not perform well when applied to systems containing nonlinearities arising from unknown deadzones. In particular, we show that a usual "fuzzy PD" controller applied to a system with a deadzone suffers from poor transient performance and a large steady-state error. In this paper, we propose a novel two-layered fuzzy logic controller for controlling systems with deadzones. The two-layered control structure consists of a fuzzy logic-based precompensator followed by a usual fuzzy PD controller. Our proposed controller exhibits superior transient and steady-state performance compared to usual fuzzy PD controllers. In addition, the controller is robust to variations in deadzone nonlinearities. We illustrate the effectiveness of our scheme using computer simulation examples.<>     

基于PLC的线性插值模糊控制器的设计

通过对喷淋式除尘系统采用的常规模糊控制器在实际应用中存在的问题进行分析,提出一种分段线性插值的设计方法,并将该方法在模糊控制器中应用。该设计采用PLC及其常规DI/DO模块组成的模糊控制器,用STL指令实现其控制功能。最后在喷淋式除尘系统中进行应用,并和常规模糊控制器的控制效果进行比较。实验结果证明:分段线性插值模糊控制器能缩短系统调节时间,提高模糊控制器的控制精度,具有一定的实用价值。     

Design of a fuzzy traffic controller for ATM networks

This paper presents the design of a fuzzy traffic controller that simultaneously manages congestion control and call admission control for asynchronous transfer mode (ATM) networks. The fuzzy traffic controller is a fuzzy implementation of the two-threshold congestion control method and the equivalent capacity admission control method extensively studied in the literature. It is an improved, intelligent implementation that not only utilizes the mathematical formulation of classical control but also mimics the expert knowledge of traffic control. We appropriately choose input linguistic variables of the fuzzy traffic controller so that the controller is a closed-loop system with stable and robust operation. We extract knowledge of conventional control methods from numerous analytical data using a clustering technique and then use this knowledge to set parameters of the membership functions and fuzzy control rules via fuzzy set manipulation (linguistically stated but mathematically treated) with the aid of an optimization technique named genetic algorithm (GA). Simulation results show that the proposed fuzzy admission control improves system utilization by a significant 11%, while maintaining the quality of service (QoS) contract comparable with that of the conventional equivalent capacity method. The performance of the proposed fuzzy congestion control method is also 4% better than that of the conventional two-threshold congestion control method