自适应模糊滑模软切换的PMSM无速度传感器鲁棒无源控制

针对永磁同步电机(PMSM)转速调节和估计问题,提出一种无速度传感器的PMSM调速系统.利用双曲正切函数代替符号函数,设计了自适应模糊滑模软切换控制器,实现了软切换连续控制,削弱了抖动现象.通过设计鲁棒无源控制器,得到了旋转坐标系下的u_d和u_q.建立了自适应滑模观测器,并给出了速度辨识律,观测器的增益通过求解线性矩阵不等式得到.仿真结果表明了该控制策略与观测器配合的有效性,且控制系统具有良好的动、稳态性能.     

Adaptive robust controller based on integral sliding mode concept

ABSTRACT

This paper proposes, for a class of uncertain nonlinear systems, an adaptive controller based on adaptive second-order sliding mode control and integral sliding mode control concepts. The adaptation strategy solves the problem of gain tuning and has the advantage of chattering reduction. Moreover, limited information about perturbation and uncertainties has to be known. The control is composed of two parts: an adaptive one whose objective is to reject the perturbation and system uncertainties, whereas the second one is chosen such as the nominal part of the system is stabilised in zero. To illustrate the effectiveness of the proposed approach, an application on an academic example is shown with simulation results.     

A novel continuous fractional sliding mode control

A new fractional-order controller is proposed, whose novelty is twofold: (i) it withstands a class of continuous but not necessarily differentiable disturbances as well as uncertainties and unmodelled dynamics, and (ii) based on a principle of dynamic memory resetting of the differintegral operator, it is enforced an invariant sliding mode in finite time. Both (i) and (ii) account for exponential convergence of tracking errors, where such principle is instrumental to demonstrate the closed-loop stability, robustness and a sustained sliding motion, as well as that high frequencies are filtered out from the control signal. The proposed methodology is illustrated with a representative simulation study.     

Vector control for induction motor drives based on adaptive variable structure control algorithm

This paper presents a new adaptive robust control for induction motor drives. The proposed control scheme is based on the so‐called field oriented control theory that allows to control the induction motor like a separately excited direct current motor drive, where the field flux (produced by the field current) and the armature flux (produced by the armature current) are decoupled. The robust control law is based on the sliding mode control theory, but unlike the traditional sliding mode control schemes, the proposed design incorporates an adaptive switching gain that avoids the need of calculating an upper limit of the system uncertainties. Moreover the proposed control law is smoothed out in order to avoid the high control activity inherent to the switching control laws. The resulting closed loop system is proven to be stable using the Lyapunov stability theory. Copyright © 2010 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society     

An adaptive solution for robust control based on integral high‐order sliding mode concept

A new high‐order sliding mode controller is proposed. The main features are gain adaptivity and the use of integral sliding mode concept. The gain adaptation allows a reduction of the chattering and gives a solution to control uncertain nonlinear systems whose the uncertainties/perturbations have unknown bounds. The concept of real high‐order sliding mode detector is introduced given that it plays a key role in the adaptation law of the gain. This new control approach is applied by simulation to an academic example to evaluate its efficiency. Copyright © 2014 John Wiley & Sons, Ltd.     

Optimality conditions and a solution scheme for fractional optimal control problems

We formulate necessary conditions for optimality in Optimal control problems with dynamics described by differential equations of fractional order (derivatives of arbitrary real order). Then by using an expansion formula for fractional derivative, optimality conditions and a new solution scheme is proposed. We assumed that the highest derivative in the differential equation of the process is of integer order. Two examples are treated in detail.     

Robust H∞ sliding mode control scheme for uncertain fractional stochastic systems: Nonlinear analysis and design

This paper investigates the $H_{\infty }$ sliding mode control (SMC) design for fractional stochastic systems. We study a very general category of stochastic systems that are nonlinear and driven by fractional Brownian motion (fBm). A robust $H_{\infty }$ SMC scheme is presented for a fractional stochastic model with external disturbance, state- and disturbance-dependent noise, and uncertainties, which ensures that the closed-loop system is stochastically stable. We propose a novel sliding surface and then prove its reachability in the state space. Furthermore, the conditions for the stochastic stability of the sliding motion are derived via nonlinear Hamilton–Jacobi (HJ)-type inequalities. In addition, an $H_{\infty }$ SMC method is developed for a special class of fractional stochastic models, and two sets of linear matrix inequality (LMI) conditions are obtained, which are sufficient for stochastic stability. Eventually, the validity of the results is validated via a simulation example.     

Adaptive sensorless robust control of AC drives based on sliding mode control theory

This paper focuses in the design of a new adaptive sensorless robust control to improve the trajectory tracking performance of induction motors. The proposed design employs the so‐called vector (or field oriented) control theory for the induction motor drives, being the designed control law based on an integral sliding‐mode algorithm that overcomes the system uncertainties. This sliding‐mode control law incorporates an adaptive switching gain in order to avoid the need of calculating an upper limit for the system uncertainties. The proposed design also includes a new method in order to estimate the rotor speed. In this method, the rotor speed estimation error is presented as a first‐order simple function based on the difference between the real stator currents and the estimated stator currents. The stability analysis of the proposed controller under parameter uncertainties and load disturbances is provided using the Lyapunov stability theory. The simulated results show, on the one hand that the proposed controller with the proposed rotor speed estimator provides high‐performance dynamic characteristics, and on the other hand that this scheme is robust with respect to plant parameter variations and external load disturbances. Finally, experimental results show the performance of the proposed control scheme. Copyright © 2006 John Wiley & Sons, Ltd.     

Nonlinear robust adaptive sliding mode control of influenza epidemic in the presence of uncertainty

In this paper, a nonlinear robust adaptive sliding mode control strategy is presented for the influenza epidemics in the presence of model uncertainties. The nonlinear epidemiological model of influenza with five state variables (the numbers of susceptible, exposed, infected, asymptomatic and recovered individuals) and two control inputs (vaccination and antiviral treatment) is considered. The objective of the proposed controller is decreasing the number of susceptible and infected humans to zero by tracking the desired scenarios. As a result of this decreasing, the number of exposed and asymptomatic individuals is also decreased and converged to the zero. Accordingly, it is shown that the number of recovered humans is increased to its maximum steady state value. The stability and tracking convergence of the control system are proved via the Lyapunov stability theorem. For the first time, a robust controller is designed and investigated for the uncertain process of influenza treatment in a population. Through a comprehensive evaluation, the effects of treatment period and the uncertainty amount on the performance of the controlled system are studied. According to the results, the nonlinear sliding mode controller guarantees the robust performance against a wide range of parametric uncertainties. Moreover, it is shown that much less rates of vaccination and antiviral treatment are required as the treatment interval is increased.     

FPGA‐based adaptive dynamic sliding‐mode neural control for a brushless DC motor

In the adaptive neural control design, since the number of hidden neurons is finite for real‐time applications, the approximation errors introduced by the neural network cannot be inevitable. To ensure the stability of the adaptive neural control system, a switching compensator is designed to dispel the approximation error. However, it will lead to substantial chattering in the control effort. In this paper, an adaptive dynamic sliding‐mode neural control (ADSNC) system composed of a neural controller and a fuzzy compensator is proposed to tackle this problem. The neural controller, using a radial basis function neural network, is the main controller and the fuzzy compensator is designed to eliminate the approximation error introduced by the neural controller. Moreover, a proportional‐integral‐type adaptation learning algorithm is developed based on the Lyapunov function; thus not only the system stability can be guaranteed but also the convergence of the tracking error and controller parameters can speed up. Finally, the proposed ADSNC system is implemented based on a field programmable gate array chip for low‐cost and high‐performance industrial applications and is applied to control a brushless DC (BLDC) motor to show its effectiveness. The experimental results demonstrate the proposed ADSNC scheme can achieve favorable control performance without encountering chattering phenomena. Copyright © 2010 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society     

Design of internal model control based fractional order PID controller

This article presents a design of the internal model control(IMC)based single degree of freedom(SDF) fractional order(FO)PID controller with a desired bandwidth specification for a class of fractional order system(FOS). The drawbacks of the SDF FO-IMC are eliminated with the help of the two-degree of freedom(TDF)FO PID controller. The robust stability and robust performance of the designed controller are analyzed using an example.     

基于自适应模糊滑模控制的分数阶混沌系统的投影同步

基于模糊控制理论和滑模控制理论以及自适应控制理论,研究了一类含有外部扰动的不确定分数阶混沌系统的混合投影同步问题.提出了一种自适应模糊滑模控制的分数阶混沌系统投影同步方法.模糊逻辑系统用来逼近未知的非线性函数和外部扰动,并且对逼近误差采用了自适应控制,同时构造了一种具有较强鲁棒性的分数阶积分滑模面.应用分数阶Barbalat引理设计了自适应模糊滑模控制器和参数自适应律.最后数值仿真结果验证了所提控制方法的有效性.     

Certainty equivalence adaptation combined with super-twisting sliding-mode control

ABSTRACT

In this paper, a Lyapunov-based control concept is presented that combines variable structure and adaptive control. The considered system class consists of nonlinear single input systems which are affected by matched structured and unstructured uncertainties. Resorting to the certainty equivalence principle, the controller exploits advantages of both the sliding-mode and the adaptive control methodology. It is demonstrated that the gains of the discontinuous control action may be reduced remarkably when compared with pure sliding-mode-based approaches. The efficiency of the presented concept is demonstrated in detail, using results of numerical simulations.     

Nonlinear robust sliding mode control of a quadrotor unmanned aerial vehicle based on immersion and invariance method

We present an asymptotic tracking controller for an underactuated quadrotor unmanned aerial vehicle using the sliding mode control method and immersion and invariance based adaptive control strategy in this paper. The control system is divided into two loops: the inner‐loop for the attitude control and the outer‐loop for the position. The sliding mode control technology is applied in the inner‐loop to compensate the unmatched nonlinear disturbances, and the immersion and invariance approach is chosen for the outer‐loop to address the parametric uncertainties. The asymptotic tracking of the position and the yaw motion is proven with the Lyapunov based stability analysis and LaSalle's invariance theorem. Real‐time experiment results performed on a hardware‐in‐the‐loop‐simulation testbed are presented to validate the good control performance of the proposed scheme. Copyright © 2014 John Wiley & Sons, Ltd.     

基于边界层的不确定机器人自适应迭代学习控制

针对不确定的多连杆机械手的跟踪控制问题,提出一种基于边界层的自适应迭代学习控制方法.自适应控制用来估计系统的未知参数的上界,本文主要特征是基于边界层设计自适应迭代学习控制器,避免了传统方法设计控制器的不连续性,削弱抖振现象的同时也提高系统的鲁棒性.理论证明系统所有信号有界,系统误差渐进收敛到边界层邻域内.仿真表明了算法的有效性.     

基于滑模变结构的倒立摆系统稳定控制

利用滑模变结构控制对一级倒立摆系统进行了有效控制.首先对一级倒立摆系统的模型进行线性化处理,再利用滑模变结构控制方法对此模型中摆的镇定、台车位置的调节和系统参数不确定性设计了具体的控制规律,并使用饱和函数的方法抑制系统的抖振.最后在Matlab/Simulink上进行了仿真实验,实验结果说明滑模变结构控制方法是有效的.     

On adaptive sliding mode control without switching gain overestimation

This paper presents some further results on adaptive sliding mode control (ASMC) for a class of nonlinear systems with bounded uncertain parameters. Given a large initial tracking error, current ASMC design generally produces an unnecessarily large switching gain, consequently leading to a serious chattering problem or a large‐amplitude control jump for the continuous counterpart. To solve such an overadaptation problem, the switching gain adaptation mechanism is first analyzed in this paper, and the adaptation induced by the initial tracking error is suggested to be removed. Then, by exploiting the global sliding mode feature of time‐varying sliding mode control and integral sliding mode control, we present two effective methodologies for ASMC design. The proposed ASMC algorithms ensure that there is no overestimation of the switching gain and the system response is not slowed down when a small switching gain is generated. The validity of the proposed methods is verified by both theoretical analysis and simulation results. Copyright © 2012 John Wiley & Sons, Ltd.     

Further results on sampled-data design for robust control of a single qubit

This paper presents further results on the robust control method for qubit systems in Dong et al. (2013) Dong, D., Petersen, I.R., &; Rabitz, H. (2013). Sampled-data design for robust control of a single qubit. IEEE Transactions on Automatic Control, 58, 2654–2659.[Crossref], [Web of Science ®] , [Google Scholar]. Based on the properties of an antisymmetric system, an alternative method is presented to analyse and exclude singularity intervals in the proof of partial original results. For the case of amplitude damping decoherence, a larger sampling period is presented when the upper bound of the probability of failure is small enough. For the case of phase damping decoherence, a larger sampling period is given when the lower bound of the target coherence is large enough. Furthermore, we provide improved sampling periods for amplitude damping decoherence and phase damping decoherence without the above prior constraints.     

Implementation of robust impedance and force control

In this paper, we discuss the problem of implementing impedance control in the presence of model uncertainties and its application to robot force control. We first propose a sliding mode-based impedance controller. The implementation of the targeted impedance, and the preservation of stability in the presence of model uncertainties, are the key issues in the proposed approach. Using sliding mode control, a simple and robust algorithm is obtained so that the targeted impedance can be accurately implemented without the exact model of the robot. The controller is designed in terms of the task space coordinates. The chattering in the sliding mode control is eliminated by using a continuous function. The problem of force control is also addressed for the impedance controlled robot. An off-line estimation method of the environment model is suggested and used in the force control scheme. The proposed impedance and force control schemes have been experimentally verified on a two degree-of-freedom direct-drive robot arm. The experimental results are presented in this paper.     

基于反步滑模算法的无人机姿态鲁棒控制系统设计

针对传统无人机姿态鲁棒控制系统易受到外部干扰影响,无法精准控制姿态角、左侧舵面角和右侧舵面角,导致系统不稳定的问题,设计了基于反步滑模算法的无人机姿态鲁棒控制系统;使用TMS320F28335芯片的串级PID控制器,控制无人机中央处理机;选择MS-S3型伺服驱动器保证电机高速运动时的高转矩运行;使用STM32f407VGT6型号姿态控制器,控制旋翼姿态;在软件流程设计过程中,构建无人机动力学模型,引入反步滑模算法构建考虑姿态角动态方程,选择Lyapunov函数计算误差变量,设计滑模控制律,借助Visual C++6.0实现软件程序编写,完成无人机姿态鲁棒控制系统设计;由实验结果可知,在时间为5 s时,该系统姿态角达到6°、左侧舵面达到0.40°、右侧舵面角达到0.20°,与实际控制结果一致,具有精准控制效果。