A novel Takagi-Sugeno-based robust adaptive fuzzy sliding-mode controller

In this paper, a nonlinear dynamic system is first approximated by N fuzzy-based linear state-space subsystems. To track a trajectory dominant by a specific frequency, the reference models with desired amplitude and phase features are established by the same fuzzy sets of the system rule. Similarly, the same fuzzy sets of the system rule are employed to design robust fuzzy sliding-mode control (RFSMC) and adaptive fuzzy sliding-mode control (AFSMC). The difference between RFSMC and AFSMC is that AFSMC contains an updating law to learn system uncertainties and then an extra compensation is designed. It is different from the most previous papers to learn the whole nonlinear functions. As the norm of the sliding surface is inside of a defined set, the updating law starts; simultaneously, as it is outside of the other set, the updating law stops. For the purpose of smoothing the possibility of discontinuous control input, a transition between RFSMC and AFSMC is also assigned. Under the circumstances, the proposed control [robust adaptive fuzzy sliding-mode control (RAFSMC)] can automatically tune as a RFSMC or an AFSMC; then the advantages coming from the RFSMC and AFSMC are obtained. Finally, the stabilities of the overall system of RFSMC, AFSMC, and RAFSMC are verified by Lyapunov stability theory. The compared simulations among RFSMC, AFSMC, and RAFSMC are also carried out to confirm the usefulness of the proposed control scheme.     

MIMO adaptive fuzzy terminal sliding-mode controller for robotic manipulators

A new design approach of a multiple-input-multiple-output (MIMO) adaptive fuzzy terminal sliding-mode controller (AFTSMC) for robotic manipulators is described in this article. A terminal sliding-mode controller (TSMC) can drive system tracking error to converge to zero in finite time. The AFTSMC, incorporating the fuzzy logic controller (FLC), the TSMC, and an adaptive scheme, is designed to retain the advantages of the TSMC while reducing the chattering. The adaptive law is designed on the basis of the Lyapunov stability criterion. The self-tuning parameters are adapted online to improve the performance of the fuzzy terminal sliding-mode controller (FTSMC). Thus, it does not require detailed system parameters for the presented AFTSMC. The simulation results demonstrate that the MIMO AFTSMC can provide a reasonable tracking performance.     

Fully distributed adaptive sliding-mode controller design for containment control of multiple Lagrangian systems

In this paper, we study the containment control problem for multiple Lagrangian systems with multiple dynamic leaders in the presence of parametric uncertainties and external disturbances with fully distributed controllers under an undirected graph. We first propose a fully distributed adaptive sliding-mode control algorithm combined with distributed sliding-mode estimators, without requiring the upper bounds of the derivatives of the leaders’ states and any other global information to be known by each follower. To reduce the effect on the varying gain during the adaption mainly caused by the initial error, fully distributed adaptive time-varying sliding-mode control is presented for controller design. To tackle the chattering effect caused by the discontinuous controller, we further propose a fully distributed continuous adaptive controller, under which both the containment errors and the adaptive gains are ultimately bounded. Simulation results are given to illustrate the theoretical results.     

A stable adaptive fuzzy sliding-mode control for affine nonlinearsystems with application to four-bar linkage systems

In this paper, a stable adaptive fuzzy sliding-mode control for affine highly nonlinear systems is developed. First, the external part of a transformed system via a feedback linearizing control evolves a linear dynamic system with uncertainties. A reference model with the desired amplitude and phase properties is given to obtain an error model. Since the uncertainties are assumed to be large, a fuzzy model is employed to model these uncertainties. A learning law with e-modification for the weight of a fuzzy model is considered to ensure the boundedness of learning weight without the requirement of persistent excitation condition. Then, an equivalent control using the known part of system dynamics and the learning fuzzy model is designed to achieve the desired control behavior. Furthermore, the uncertainties caused by the approximation of fuzzy model and the error of learning weight are tackled by a switching control. Finally, the stability of the overall system is verified by the Lyapunov theory. Simulations and experiments of the velocity control of a four-bar-linkage system are presented to verify the usefulness of the proposed control     

A sliding-mode based smooth adaptive robust controller for friction compensation

In this paper, a new approach employing both adaptive and robust methodologies is proposed for stick–slip friction compensation for tracking control of a one degree-of-freedom DC-motor system. It is well known that the major components of friction are Coulomb force, viscous force, exponential force (used to model the downward bend of friction at low velocity) and position-dependent force. Viscous force is linear and Coulomb force is linear in parameter; thus, these two forces can be compensated for by adaptive feedforward cancellation. Meanwhile, the latter two forces, which are neither linear nor linear in parameters, can only be partially compensated for by adaptive feedforward cancellation. Therefore, a robust compensator with an embedded adaptive law to ‘learn’ the upper bounding function on-line is proposed to compensate the uncancelled exponential and position-dependent friction. Lyapunov's direct method is utilized to prove the globally asymptotic stability of the servo-system under the proposed friction compensation method. Numerical simulations are presented as illustrations. © 1998 John Wiley & Sons, Ltd.     

EP-based kinematic control and adaptive fuzzy sliding-mode dynamic control for wheeled mobile robots

This paper proposes a complete control law comprising an evolutionary programming based kinematic control (EPKC) and an adaptive fuzzy sliding-mode dynamic control (AFSMDC) for the trajectory-tracking control of nonholonomic wheeled mobile robots (WMRs). The control gains for kinematic control (KC) are trained by evolutionary programming (EP). The proposed AFSMDC not only eliminates the chattering phenomenon in the sliding-mode control, but also copes with the system uncertainties and external disturbances. Additionally, the convergence of trajectory-tracking errors is proved by the Lyapunov stability theory. Computer simulations are presented to confirm the effectiveness of the proposed complete control law. Finally, real-time experiments are done in the test field to demonstrate the feasibility of real WMR maneuvers.     

Authors' reply [fuzzy adaptive sliding-mode control for MIMO nonlinear systems]

We have studied the comment about our original paper and we agree that a minor mistake was made in Eq. 37 of our original paper (see ibid., vol. 11, no. 3, p. 354-60 (2003)).     

基于滑模与自适应观测器的感应电机非线性控制新策略

提出一种结合滑模变结构和自适应观测技术的感应电机非线性控制新方法. 以定子电流与定子磁链为状态变量建立感应电机模型, 采用非线性分析方法建立转矩与磁链误差方程, 使用自适应滑模技术设计转矩与磁链控制器, 推导出定子电压控制量. 基于模型参考技术设计自适应观测器, 向控制器提供准确的转速辨识与磁链观测值,并给出了控制系统的稳定性证明. 该方法具有转矩脉动小、定子磁链畸变不明显的优点, 低速时也具有良好的控制性能, 且对参数与负载变化有较强的鲁棒性. 仿真与实验结果证明了该控制策略的正确性与有效性.     

A new approach to adaptive fuzzy control: the controller outputerror method

The controller output error method (COEM) is introduced and applied to the design of adaptive fuzzy control systems. The method employs a gradient descent algorithm to minimize a cost function which is based on the error at the controller output. This contrasts with more conventional methods which use the error at the plant output. The cost function is minimized by adapting some or all of the parameters of the fuzzy controller. The proposed adaptive fuzzy controller is applied to the adaptive control of a nonlinear plant and is shown to be capable of providing good overall system performance.     

An adaptive fuzzy sliding mode controller for robotic manipulators

This paper proposes an adaptive fuzzy sliding mode controller for robotic manipulators. An adaptive single-input single-output (SISO) fuzzy system is applied to calculate each element of the control gain vector in a sliding mode controller. The adaptive law is designed based on the Lyapunov method. Mathematical proof for the stability and the convergence of the system is presented. Various operation situations such as the set point control and the trajectory control are simulated. The simulation results demonstrate that the chattering and the steady state errors, which usually occur in the classical sliding mode control, are eliminated and satisfactory trajectory tracking is achieved.     

具有模糊监督控制器的积分变结构间接自适应控制

针对一类不确定非线性系统, 基于变结构控制原理, 并利用具有非线性可调参数的模糊系统去逼近过程未知函数, 提出一种具有模糊监督控制器的积分变结构间接自适应控制方案. 该方案通过监督控制器保证闭环系统所有信号有界. 进一步, 通过引入最优逼近误差的自适应补偿项来消除建模误差的影响. 理论分析证明了跟踪误差收敛到零. 仿真结果表明了该方法的有效性.     

小型无人机纵向姿态模糊自适应PID控制与仿真

针对某小型实验无人机智能自主飞行的要求,提出了一种无人机纵向姿态的模糊控制方法,设计了模糊自适应PID控制器,可有效实现该无人机的纵向姿态控制和纵向航迹跟踪.仿真结果表明,所设计的模糊自适应PID控制器较传统的PID控制器具有更好的控制性能,其响应快、超调小、精度高,而且鲁棒性和自适应能力也较强,可满足自主飞行的要求.     

An adaptive fuzzy design for fault-tolerant control of MIMO nonlinear uncertain systems

This paper presents a novel control method for accommodating actuator faults in a class of multiple-input multiple-output (MIMO) nonlinear uncertain systems.The designed control scheme can tolerate both the time-varying lock-in-place and loss of effectiveness actuator faults.In each subsystem of the considered MIMO system,the controller is obtained from a backstepping procedure;an adaptive fuzzy approximator with minimal learning parameterization is employed to approximate the package of unknown nonlinear functions in each design step.Additional control effort is taken to deal with the approximation error and external disturbance together.It is proven that the closed-loop stability and desired tracking performance can be guaranteed by the proposed control scheme.An example is used to show the effectiveness of the designed controller.     

船舶航迹控制鲁棒自适应模糊设计

研究了船舶直线航迹控制问题.基于Lyapunov稳定性理论,将Nussbaum增益技术融入Backstepping设计方法之中,利用模糊系统逼近系统中的未知非线性,提出一种鲁棒自适应模糊控制算法.该算法保证了闭环系统的信号是一致最终有界的,使得系统输出收敛到零的一个较小邻域,从而能够实现船舶的直线航迹控制;而且,该算法不需要高频增益符号的任何信息,还解决了可能存在的控制器奇异值问题.计算机仿真结果验证了控制器的有效性.     

An adaptive fuzzy controller based on sliding mode for robotmanipulators

This paper considers adaptive fuzzy control of robotic manipulators based on sliding mode. It is first shown that an adaptive fuzzy system with the system representative point (RP, or as is often termed, a switching function in variable structure control (VSC) theory) and its derivative as inputs, can approximate the robot nonlinear dynamics in the neighborhood of the switching hyperplane. Then a new method for designing an adaptive fuzzy control system based on sliding mode is proposed for the trajectory tracking control of a robot with unknown nonlinear dynamics. The system stability and tracking error convergence are also proved by Lyapunov techniques.     

Fuzzy neural networks for estimation and fuzzy controller design: simulation study for a pulp batch digester

A structural implementation of a fuzzy inference system through connectionist network based on MLP with logical neurons connected through binary and numerical weights is considered. The resulting fuzzy neural network is trained using classical backpropagation to learn the rules of inference of a fuzzy system, by adjustment of the numerical weights. For controller design, training is carried out off line in a closed loop simulation. Rules for the fuzzy logic controller are extracted from the network by interpreting the consequence weights as measure of confidence of the underlying rule. The framework is used in a simulation study for estimation and control of a pulp batch digester. The controlled variable, the Kappa number, a measure of lignin content in the pulp, which is not measurable is estimated through temperature and liquor concentration using the fuzzy neural network. On the other hand a fuzzy neural network is trained to control the Kappa number and rules are extracted from the trained network to construct a fuzzy logic controller.     

An adaptive controller design for linear state-delay systems with actuator failures

In this paper, an adaptive fault tolerant controller is developed for a class of linear state delay systems against actuator failures. To design the controller, all parameters of the system are considered to be unknown, but the time delay value is assumed to be known. Actuator failures are characterized by some unknown system inputs are stuck at some unknown fixed values and at unknown time instants. The adaptive controller is designed based on SPR-Lyapunov approach for the cases with the relative degrees of one and two. Closed-loop system stability and asymptotic output tracking are proved using a suitable Lyapunov-Krasovskii functional for each case and the effectiveness of the proposed results has been illustrated through simulation studies.     

An arithmetic controller design for numerical control

This paper provides an arithmetic controller comprising: an arithmetic logic unit having a plurality of arithmetic instructions, such as ADD (Addition), SUB (Subtraction), MUL (Multiplication), and DIV (Division) instructions. This arithmetic processor was implemented by a cell-based flow and supports the basic mathematical operations, and numerical control.     

控制方向未知的SISO非仿射系统间接自适应模糊输出反馈控制

针对一类单输入单输出(SISO)非仿射非线性系统控制方向未知时出现的控制器奇异问题,提出了一种间接自适应模糊控制方案.利用中值定理将非仿射系统转化为仿射系统,通过模糊逻辑系统逼近该仿射系统中的未知函数,并构造模糊控制器,同时利用Lyapunov稳定性定理设计自适应律,最终克服了控制器的奇异问题;在此基础上,通过构造观测器估计跟踪误差,设计输出反馈自适应模糊控制器,解决了状态不可测时系统控制器设计难题,采用Lyapunov稳定性定理证明控制器能使得跟踪误差收敛同时闭环系统所有信号均有界.仿真结果验证了所设计控制方案的可行性与有效性.     

An adaptive fuzzy sliding mode controller for remotely operated underwater vehicles

Sliding mode control is a very attractive control scheme because of its robustness against both structured and unstructured uncertainties as well as external disturbances. In this way, it has been widely employed for the dynamic positioning of remotely operated underwater vehicles. Nevertheless, in such situations the discontinuities in the control law must be smoothed out to avoid the undesirable chattering effects. The adoption of properly designed boundary layers has proven effective in completely eliminating chattering, however, leading to an inferior tracking performance. This work describes the development of a dynamic positioning system for remotely operated underwater vehicles. The adopted approach is primarily based on the sliding mode control strategy and enhanced by an adaptive fuzzy algorithm for uncertainty/disturbance compensation. Using the Lyapunov stability theory and Barbalat’s lemma, the boundedness and convergence properties of the closed-loop signals are analytically proven. The performance of the proposed control scheme is also evaluated by means of numerical simulations.