基于自回归小波神经网络的感应电动机滑模反推控制

为了提高感应电动机控制的鲁棒性, 提出了一种新颖的感应电动机解耦模型. 基于感应电动机的解耦模型, 利用滑模控制和反推控制设计电动机的虚拟转矩和磁链电压控制器. 滑模开关增益的大小是造成系统抖振的关键, 采用自回归小波神经网络(Self-recurrent wavelet neural networks, SRWNN)在线估计滑模开关增益的大小可以有效降低滑模控制造成的抖振. 仿真结果表明基于SRWNN在线估计滑模开关增益的滑模反推控制方案可以有效提高感应电动机控制的鲁棒性, 同时降低了滑模控制造成的抖振.     

神经网络在感应电动机调速系统中的应用研究

研究感应电动机凋速系统解耦控制问题.感应电动机调速系统是一个非线性、多变量和强耦合控制对象,传统的线性方法无法找到合适的描述模型,导致解耦控制性能相当的差.在体现适应性、实时性和鲁棒性的问题上,为了提高感应电动机调速系统解耦控制性能,将逆系统方法与神经网络相结合,提出了一种基于神经网络逆系统的感应电动机调速解耦控制方法.首先根据感应电动机调速系统的特点,建立合适的数学模型,并进行伪线性系统构造;然后采用神经网络对逆系统模型进行辨识,通过神经网络自学习实现高性能解耦控制;最后在matlab平台下进行了仿真和对比实验.实验结果表明,方法能很好实现解耦控制,使传统解耦控制方法的缺陷得到克服,具有较强适应性和鲁棒性.     

基于逆系统原理的感应电动机滑模速度控制

针对目前逆系统原理应用于感应电动机调速系统中时往往忽略参数不确定性的问题,从感应电动机的非线性模型出发,采用逆系统理论建立了转子电阻与负载参数不确定的感应电动机伪线性控制系统模型;提出了一种采用变指数趋近律实现的防抖动自适应滑模变结构控制方法,并将该控制方法应用于感应电动机伪线性控制系统中。仿真结果表明,基于逆系统原理的感应电动机滑模速度控制方法能够有效抑制系统参数的不确定性,提高系统的稳定性和控制精度。     

采用模糊控制的感应电动机解耦变结构系统的研究

感应电动机的解耦变结构控制是一种新型的交流控制系统,但解耦变结构控制在实际系 统中会引起抖振问题,从而影响了控制系统的性能.将模糊控制引入感应电动机解耦变结构系统 可以有效地抑制抖振,从而提出了采用模糊控制的感应电动机解耦变结构控制系统.     

机械手的模糊逆模型鲁棒控制

提出一种基于模糊聚类和滑动模控制的模糊逆模型控制方法,并将其应用于动力学 方程未知的机械手轨迹控制.首先,采用C均值聚类算法构造两关节机械手的高木-关野 (T-S)模糊模型,并由此构造模糊系统的逆模型.然后,在提出的模糊逆模型控制结构中, 离散时间滑动模控制和时延控制(TDC)用于补偿模糊建模误差和外扰动,保证系统的全局 稳定性并改进其动态和稳态性能.系统的稳定性和轨迹误差的收敛性可以通过稳定性定理来 证明.最后,以两关节机械手的轨迹跟随控制为例,揭示了该设计方法的控制性能.     

基于滑模变结构的感应电动机直接转矩控制

针对感应电动机常规直接转矩控制中存在磁链、转矩脉动大,低速控制不精确等问题,在建立α-β坐标系感应电动机数学模型的基础上,提出了一种基于滑模变结构的新型直接转矩控制方法。该方法利用转速滑模变结构控制器代替常规直接转矩控制中的PI控制器,可有效减小常规直接转矩控制中的磁链和转矩脉动,增强了系统的稳定性。仿真结果证明了该方法的正确性。     

基于Inte1196的感应电动机软起动器

提出了一种以Intel196单片机为控制核心的感应电动机软起动控制与保护系统,通过控制主回路上三对反并联晶闸管的导通角度,实现交流感应电动机的平滑起动和停机.根据电动机拖动负载的不同特点,设计了多种软起动方式.试验结果表明,该软起动器具有优良的性能.     

矿山变频矢量控制系统效率优化方案研究

针对矿山变频调速系统感应电动机采用恒定磁通控制,存在损耗严重、运行效率低的问题,提出了一种矿山变频矢量控制系统的效率优化控制方案。该方案在两相旋转d-q坐标系下,建立了考虑定、转子铜损和铁损的系统损耗模型,推导得到不同运行工况下电动机损耗与转子磁链之间的对应关系;为改善因弱磁运行而造成的系统动态响应过慢问题,通过优化转矩电流和磁链电流比重关系,获得电动机电磁转矩的快速响应和转速跟踪。基于DSP+FPGA控制系统搭建22kW三电平感应电动机调速系统实验平台,实验结果表明,该优化方案可以降低感应电动机矢量控制系统运行损耗,提高系统运行效率,并保证系统的稳态性能和动态响应性能。     

基于在线搜索的感应电动机模糊节能控制

针对传统的按转子磁链定向的感应电动机间接矢量控制系统在轻载情况下效率低的问题,提出了一种将基于在线搜索的模糊节能控制方法引入到传统的感应电动机控制系统中的设计方案。该方案在感应电动机瞬态运行时采用按转子磁链定向的间接矢量控制方法;在感应电动机稳态运行时采用基于在线搜索的模糊节能控制方法,以测得的直流输入功率作为控制量进行模糊寻优控制,可使电动机在最大效率处运行。仿真结果验证了该方案的正确性和有效性。     

广义非线性系统的变结构控制理论

利用几何方法,从广义非线性系统本身出发,研究了广义非线性控制的变化结构控制理论,给出了系统存在变结构控制的充分实际没动模式的近似定理。从所得结论可知,滑动条件仅能保证实际滑动模的慢变状态赵近于理想滑动模的慢变状态,而不能保证实际滑动模的状态趋近于理想滑动模的快变状态,研究正常非线性系统的方法已不能简单地被利用到广义非线性系统。     

基于滑模位置控制的机器人灵巧手模糊自适应阻抗控制

提出一种基于滑模位置控制的模糊自适应阻抗控制策略。该控制方案通过模糊控制器实时地调整阻抗参数,不但可使系统稳定,而且具有良好的动态品质;同时内环的滑模位置控制器可增强系统的鲁棒性,最后以机器人灵巧手单关节为对象进行仿真研究,证明了该控制策略的有效性和可行性。     

基于函数滑模控制器的机械手轨迹跟踪控制

提出一种基于函数滑模控制器(FSMC)的控制策略,用于不确定机械手的轨迹跟踪控制。首先,由动力学模型和滑模函数得到系统的不确定项;然后,利用RBF神经网络逼近系统不确定项,由于神经网络逼近存在误差,而且在初始阶段误差较大,设计函数滑模控制器和鲁棒补偿项对神经网络逼近误差进行补偿,以克服普通滑模控制器容易引起的抖振问题,同时提高系统的跟踪控制性能。基于李亚普诺夫理论证明了闭环系统的全局稳定性,仿真实验也验证了方法的有效性。     

Quadrotor Control Via Robust Generalized Dynamic Inversion and Adaptive Non‐Singular Terminal Sliding Mode

A robust two‐loops structured control system design for quadrotor's position/attitude trajectory tracking is proposed. The aim of the outer loop is to provide the roll/pitch tilting commands to the inner loop, which in turns generates the tilting angles that control the quadrotor's center of gravity in the horizontal plane. The outer loop utilizes Robust Generalized Dynamic Inversion (RGDI) of a prescribed asymptotically stable differential equation in the deviation function of the horizontal position coordinates from their reference trajectories. The inner loop employs an Adaptive Non‐singular Terminal Sliding Mode (ANTSM) to control the tilting angles, in addition to controlling the yaw attitude angle and the vertical position coordinate. The proposed scheme solves the singularity avoidance problems of generalized inversion and terminal sliding mode control. The stability of outer and inner loop is ensured by utilizing positive definite Lyapunov energy function for stable tracking performance against parametric variations and bounded unknown external disturbances. Numerous simulations are conducted on a six Degrees of Freedom (DoF) quadrotor model in the presence of parametric variations, un modeled dynamics, and external disturbances.     

Adaptive switching gain for a discrete-time sliding mode controller

Sliding mode control is a well-known technique capable of making the closed loop system robust with respect to certain kinds of parameter variations and unmodelled dynamics. The sliding mode control law consists of a continuous component which is based on the model knowledge and discontinuous component which is based on the model uncertainty. This paper extends two known adaption laws for the switching gain for continuous-time sliding mode controllers to the multiple input case. Because these adaption laws have some fundamental problems in discrete-time, we introduce a new adaption law specifically designed for discrete-time sliding mode controllers.     

基于滑模变结构控制的电动助力转向系统

针对汽车电动助力转向系统，提出滑模变结构控制方法，建立其运动方程，确定了滑模变结构控制器。台架实验结果表明这种滑模变结构控制器与PD控制器相比，其控制方法简单，同时具有更好控制效果。     

On estimation of the domain of attraction for sliding mode control of underactuated nonlinear systems

A system is considered underactuated if the number of the actuator inputs is less than the number of degrees of freedom for the system. Sliding mode control for underactuated systems has been shown to be an effective way to achieve system stabilization. It involves exponentially stable sliding surfaces so that when the closed‐loop system trajectory reaches the surface, it moves along the surface while converging to the origin. In this paper, a general framework that provides sufficient conditions for asymptotic stabilization of underactuated nonlinear systems using sliding mode control in the presence of system uncertainties is presented. Specifically, it is shown that the closed‐loop system trajectories reach the sliding surface in finite time, and a constructive methodology to determine exponential stability of the closed‐loop system on the sliding surface is developed, which ensures asymptotic stability of the overall closed‐loop system. Furthermore, the aforementioned framework provides the basis to determine an estimate of the domain of attraction for the closed‐loop system with uncertainties. Finally, the results developed in the paper are experimentally validated using a linear inverted pendulum testbed to show a good match between the actual domain of attraction of the upward equilibrium state of the pendulum and its analytical estimate.Copyright © 2012 John Wiley & Sons, Ltd.     

Backstepping - Sliding Mode Controllers Applied to a Fixed-Wing UAV

This paper deals with the design of five controllers, based on Backstepping and Sliding Modes, which are applied to a fixed-wing unmanned aerial vehicle (UAV). We are interested to realize a comparative analysis of such methodologies in order to know what controller has a better performance when they are used to the autonomous flight (altitude, yaw and roll) of a fixed-wing UAV. The designed controllers are: Backstepping, Sliding Mode control (SMC), Backstepping with Sliding Mode control, Backstepping with two Sliding Mode control, and Backstepping with high order Sliding Mode (HOSM) control. Simulation results are obtained in order to analyze the controllers performance. We finally present an experimental result, in open-loop, with the purpose of validate the magnitude of the control signals obtained in the simulations.     

A robust control scheme for nonlinear non-isothermal uncertain jacketed continuous stirred tank reactor

A Non-isothermal Jacketed Continuous Stirred Tank Reactor (CSTR) is extensively used in chemical as well as in other process industries to manufacture different products. The dynamics of non-isothermal CSTR are highly nonlinear and open-loop unstable in nature. Moreover, it may have parametric uncertainties, disturbances and un-modeled side reactions which may cause the reactor temperature to deviate from the reference value. This deviation may degrade quality of the product because the chemical reaction inside the CSTR depends on reactor temperature. For such a nonlinear, unstable and uncertain process, designing a control scheme with the ability to reject the effects of disturbances along with a good reference tracking capability is a challenging control engineering problem. In this work, a novel robust sliding mode control technique named as Improved Integral Sliding Mode Control (IISMC) has been presented for uncertain non-isothermal jacketed CSTR process. Moreover, a variety of recently developed sliding mode control techniques such as Classical Integral Sliding Mode Control (CISMC) and Super Twisted Algorithm based Sliding Mode Control (STA-SMC) have also been devised and compared with the proposed approach in order to investigate the effectiveness of the proposed scheme. A Lyapunov based analysis has also been provided to assure the robust stability of the closed loop process. Furthermore, in order to extend the state feedback approach to the output feedback scheme, two robust observers; High Gain Observer (HGO) and Extended High Gain Observer (EHGO), are also designed for the very process. They have also been compared with each other and have been investigated for robust stability using Lyapunov based approach. Finally, an output feedback control scheme using IISMC and EHGO has been presented and its performance has been examined and compared with the IISMC based state feedback approach. The simulation results show that the proposed control scheme effectively rejects the uncertainties and disturbances without leading the process to instability and offers good reference tracking capabilities.     

超空泡航行体的自适应模糊滑模控制研究

针对超空泡航行体动态中的非线性项和未建模动态,以及由空泡形状改变引起的扰动问题,提出了一种基于自适应模糊滑模的纵平面运动控制器设计方法。该方法利用自适应模糊系统逼近超空泡航行体模型中的非线性不确定项;利用滑模控制对干扰的鲁棒性,克服逼近误差和干扰;最后用Lyapunov定理证明了闭环系统的稳定性。仿真结果表明,设计的控制器可有效克服滑行力的计算误差以及水动力参数的不确定性。     

Sliding mode learning control for T-S fuzzy system and an application to hypersonic flight vehicle

Sliding mode-based learning control is presented for T-S fuzzy system. A T-S fuzzy model with both uncertainties and unmodeled dynamics is proposed firstly, in which the information of uncertainties and unmodeled dynamics are assumed to be unknown. Then, according to a given reference model, state-tracking error system is built. Respecting facts, the input matrices of the built T-S fuzzy model are different from each other. An extended state observer is built for estimating the unknown uncertainties and unmodeled dynamics, and a corresponding sliding surface is proposed. A learning controller is then presented for the closed loop system. Moreover, a numerical simulation result on hypersonic flight vehicles is considered to testify the controller's availability.