Decentralized model reference adaptive sliding mode control based on fuzzy model

A new design scheme of decentralized model reference adaptive sliding mode controller for a class of MIMO nonlinear systems with the high-order interconnections is propcsed. The design is based on the universal approximation capability of the Takagi - Seguno （T-S） fuzzy systems. Motivated by the principle of certainty equivalenteontrol, a decentralized adaptive controller is designed to achieve the tracking objective without computafion of the T-S fuzz ymodel. The approach does not require the upper bound of the uncertainty term to be known through some adaptive estimation. By theoretical analysis, the closed-loop fuzzy control system is proven to be globally stable in the sense that all signalsinvolved are bounded, with tracking errors converging to zero. Simulation results demonstrate the effectiveness of the approach.

Design of a Kind of Model Reference Adaptive Missile Control System

目的设计能够适应环境变化和目标机动的导弹控制系统．方法将模型参考自适应控制理论应用于导弹控制系统的设计，针对反坦克导弹的具体特点做了相应的改进．结果大量仿真得出所设计的控制系统能够满足击顶反坦克导弹的战技要求．结论将模型参考自适应控制应用于导弹控制系统设计是成功的，与常规控制系统相比具有明显的优点。

MULTIVARIABLE MODEL REFERENCE ADAPTIVE CONTROL FOR A TURBOFAN ENGINE

A decentralized model reference adaptive control (MRAC) scheme is proposed and applied to design a multivariable control system of a dual-spool turbofan engine.Simulation studies show good static and dynamic performance of the system over the fullflight envelope. Simulation results also show the good effectiveness of reducing interactionin the multivariable system with significant coupling. The control system developed has awide frequency band to satisfy the strict engineering requirement and is practical for engineering applications.

Robustness Analysis of Discrete-time Indirect Model Reference Adaptive Control with Normalized Adaptive Laws

For a class of discrete-time systems with unmodeled dynamics and bounded disturbance, the design and analysis of robust indirect model reference adaptive control （MRAC） with normalized adaptive law are investigated. The main work includes three parts. Firstly, it is shown that the constructed parameter estimation algorithm not only possesses the same properties as those of traditional estimation algorithms, but also avoids the possibility of division by zero. Secondly, by establishing a relationship between the plant parameter estimate and the controller parameter estimate, some similar properties of the latter are also established. Thirdly, by using the relationship between the normalizing signal and all the signals of the closed-loop system, and some important mathematical tools on discrete-time systems, as in the continuous-time case, a systematic stability and robustness analysis approach to the discrete indirect robust MRAC scheme is developed rigorously.

A Systematic Analysis Approach to Discrete-time Indirect Model Reference Adaptive Control

这份报纸论述间接模型引用的设计和分析有为分离时间的系统的一个类的规范的适应法律的适应控制(MRAC ) 。主要工作包括三部分。第一，构造工厂参数评价算法不仅拥有传统的评价算法的象那些的一样的性质而且在零避免分割的可能性。第二，由发现在工厂参数之间的关系，估计和控制器参数估计并且用工厂参数的性质估计，控制器参数估计的类似的性质也被建立。第三，基于关系，在使正常化之间的性质发信号并且在靠近环的系统并且在分离时间的系统上的一些重要数学工具上的所有信号作为在连续时间的盒子中，到分离间接 MRAC 计划的系统的稳定性和集中分析途径严厉地被开发。

Discrete-time Direct Model Reference Adaptive Control： A Systematic Approach

为直接模型引用的分离时间的系统，设计和分析的一个类，有规范的适应法律的适应控制(MRAC ) 被调查。我们责骂在输入和产量之间的 p 和 2 个关系性质上的分离时间的结论，和分离时间的交换词根 1 和 2。我们也建立分离时间的适应法律的性质，定义使正常化的信号，并且联系有在靠近环的系统的所有信号的信号。因此，分离时间的 MRAC 计划的稳定性和集中性质作为在连续时间的案例中以一种系统的方式严厉地被分析。

Model Reference Adaptive Control for Switched Systems with Closed-loop Reference Model Under Arbitrary Switching

This paper explores the model reference adaptive control problem for a class of switched linear systems under arbitrary switching with no need for the measurability of the system state.Based on the state of reference model and the measurable output error, adaptive laws and controllers are designed for switched systems.Each subsystem may have its individual reference model and controller, which increases the design flexibility.The introduction of the closed-loop reference model is to get a better transient performance of the whole switched systems.A numerical example is provided to verify the effectiveness of the main results.

Direct model reference adaptive control using K_p = LDU factorization for multivariable discrete-time plants

For a large class of discrete-time multivariable plants with arbitrary relative degrees, the design and analysis of the direct model reference adaptive control scheme are investigated under less restrictive assumptions. The algorithm is based on a new parametrization derived from the high frequency gain matrix factorization Kp=LDU under the condition that the signs of the leading principal minors of/fp are known. By reproving the discrete-time Lp and L2σ norm relationship between inputs and outputs, establishing the properties of discrete-time adaptive law, defining the normalizing signal, and relating the signal with all signals in the closed-loop system, the stability and convergence of the discrete-time multivariable model reference adaptive control scheme are analyzed rigorously in a systematic fashion as in the continuous-time case.

System Design of a Reference Model Adaptive Control for Radial Plasma Position on HL-2A Tokamak

The design of the control system for radial plasma position on HL-2A based on model reference adaptive control (MRAC) principle is presented in this paper. The simulated results show that it can be used to improve the performance of the system greatly. Compared with the classical PID control system, it has obvious advantages in the better dynamic response, the smaller quantity of calculation and the better robustness.

New model reference adaptive control with input constraints

A new scheme of adaptive control is proposed for a class of linear time-invariant（ LTI） dynamical systems,especially in aerospace,with matched parametric uncertainties and input constraints. Based on a typical and conventional direct model reference adaptive control scheme,various modifications have been employed to achieve the goal. ＂C omposite model reference adaptive control＂of higher performance is seam-lessly combined with ＂positive μ-mod＂,which consequently results in a smooth tracking trajectory despite of the input constraints. In addition,bounded-gain forgetting is utilized to facilitate faster convergence of parameter estimates. The stability of the closed-loop systemcan be guaranteed by using Lyapunov theory.The merits and effectiveness of the proposed method are illustrated by a numerical example of the longitudinal dynamical systems of a fixed-wing airplane.

Controlling chaos using Takagi-Sugeno fuzzy model and adaptive adjustment

In this paper, an approach to the control of continuous-time chaotic systems is proposed using the Takagi-Sugeno （TS） fuzzy model and adaptive adjustment. Sufficient conditions are derived to guarantee chaos control from Lyapunov stability theory. The proposed approach offers a systematic design procedure for stabilizing a large class of chaotic systems in the literature about chaos research. The simulation results on Rossler＇s system verify the effectiveness of the proposed methods.

Fuzzy Model Free Adaptive Control for Rotor Blade Full-Scale Static Testing

To eliminate the node traction coupling during wind turbine blade full-scale static testing,a model free adaptive control algorithm is presented based on fuzzy control performance function compensation. Based on the universal model theory,the fuzzy model free adaptive control( FMFAC) algorithm is designed by configuring the spot static testing experiences as compensation function F( ·). Then the algorithm implementation process is provided and its quick convergence is proved. Using software to establish static load coupling model of multi-nodes,simulate and verify the validity of FMFAC algorithm,which is applied to wind turbines blade full-scale static testing. The results show that the adaptive decoupling ability of FMFAC is better. The traction of four load points can stay steady and change coordinately. Process error is not over ± 6 k N. The error rate is lower than 1% in special phase.This algorithm effectively eliminates the traction coupling of the static testing process,and makes wind turbine blade testing steadily.

FUZZY ADAPTIVE CONTROL MODEL FOR PROCESS IN NICKEL MATTE SMELTING FURNACE

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Fuzzy Adaptive Tracking Control of Uncertain Strict-Feedback Nonlinear Systems with Disturbances Based on Generalized Fuzzy Hyperbolic Model

In this paper, a fuzzy adaptive tracking control for uncertain strict-feedback nonlinear systems with unknown bounded disturbances is proposed. The generalized fuzzy hyperbolic model (GFHM) with better approximation performance is used to approximate the unknown nonlinear function in the system. The dynamic surface control (DSC) is used to design the controller, which not only avoids the “explosion of complexity” problem in the process of repeated derivation, but also makes the control system simpler in structure and lower in computational cost because only one adaptive law is designed in the controller design process. Through the Lyapunov stability analysis, all signals in the closed loop system designed in this paper are semi-globally uniformly ultimately bounded (SGUUB). Finally, the effectiveness of the method is verified by a simulation example.

FUZZY MODEL-FOLLOWING ADAPTIVE CONTROL DESIGN FOR ROBOT MANIPULATORS

The increasing demand on robotic system performance leads to the use of advanced con- trol strategies. This paper proposes a method of nonlinear feedback control introducing fuzzy infer- ence into model-following adaptive control for the nonlinear robot manipulator systems. The fuzzy inference is introduced to treat the nonlinearities of the control systems. Furthermore, the stability of the system is discussed by the fuzzy stability theory based on the Lyapunov's direct method. In the closed loop, the robotic system asymptotically converge to the reference trajectory with a pre- scribed transient response.

Robust adaptive fuzzy control scheme for nonlinear system with uncertainty

In this paper, a robust adaptive fuzzy control scheme for a class of nonlinear system with uncertainty is proposed. First, using prior knowledge about the plant we obtain a fuzzy model, which is called the generalized fuzzy hyperbolic model （GFHM）. Secondly, for the case that the states of the system are not available an observer is designed and a robust adaptive fuzzy output feedback control scheme is developed. The overall control system guarantees that the tracking error converges to a small neighborhood of origin and that all signals involved are uniformly bounded. The main advantages of the proposed control scheme are that the human knowledge about the plant under control can be used to design the controller and only one parameter in the adaptive mechanism needs to be on-line adjusted.

Fuzzy adaptive PID control on hydraulic servo system of quadruped robot

Quadruped robot driven by high power density hydraulic device works in unstructured en- vironment. With variable load and various external disturbance, the hydraulic servo system has fea- tures such as nonlinear, time-varying parameters. Traditional control method has some limitation. In order to help the hydraulic servo system of the quadruped robot to adapt to harsh environments, and to obtain high control quality and control precision, an incremental fuzzy adaptive PID controller based on position feedback is designed to solve the related technical problems. Matlab/Simulink sim- ulation and experimental results show that the incremental fuzzy adaptive PID controller improves the dynamic performance of the system, enhances the respond speed and precision of the hydraulic ser- vo system, and has some theory significance and practical value.

Adaptive predictive functional control based on Takagi-Sugeno model and its application to pH process

In order to obtain accurate prediction model and compensate for the influence of model mismatch on the control performance of the system and avoid solving nonlinear programming problem,an adaptive fuzzy predictive functional control(AFPFC) scheme for multivariable nonlinear systems was proposed.Firstly,multivariable nonlinear systems were described based on Takagi-Sugeno(T-S) fuzzy models;assuming that the antecedent parameters of T-S models were kept,the consequent parameters were identified on-line by using the weighted recursive least square(WRLS) method.Secondly,the identified T-S models were linearized to be time-varying state space model at each sampling instant.Finally,by using linear predictive control technique the analysis solution of the optimal control law of AFPFC was established.The application results for pH neutralization process show that the absolute error between the identified T-S model output and the process output is smaller than 0.015;the tracking ability of the proposed AFPFC is superior to that of non-AFPFC(NAFPFC) for pH process without disturbances,the overshoot of the effluent pH value of AFPFC with disturbances is decreased by 50% compared with that of NAFPFC;when the process parameters of AFPFC vary with time the integrated absolute error(IAE) performance index still retains to be less than 200 compared with that of NAFPFC.

SOFC temperature evaluation based on an adaptive fuzzy controller

The operating temperature of a solid oxide fuel cell (SOFC) stack is a very important parameter to be controlled, which impacts the performance of the SOFC due to thermal cycling. In this paper, an adaptive fuzzy control method based on an affine nonlinear temperature model is developed to control the temperature of the SOFC within a specified range. Fuzzy logic systems are used to approximate nonlinear functions in the SOFC system and an adaptive technique is employed to construct the controller. Compared with the traditional fuzzy and proportion-integral-derivative (PID) control, the simulation results show that the designed adaptive fuzzy control method performed much better. So it is feasible to build an adaptive fuzzy controller for temperature control of the SOFC.

VARIABLE STRUCTURE MODEL－FOLLOWING ADAPTIVE CONTROL DESIGN FOR ROBOT MANIPULATORS

The increasing demand on robotic system performance leads to the use of advanced control strategies. A variable structure model-following adaptive control design is presented for the nonlinear robot manipulator systems, when subjected to fast and wide ranges of unknown-but-bounded parameter variations and disturbances. The design does not require any knowledge of a nonlinear robotic system. The system is robust and insensitive to the parameter variation, disturbances, as well as to the unmodeled dynamics. This insensitive property enables the elimination of interactions among the various joints of the robotic manipulator. In the closed loop, the robotic system asymptotically converges to the reference trajectory with a Prescribed transient resPOnse. The problem of chattering is discussed with the introduction of the special approaches: boundary layer, smoothing law, and nonlinear compensation.