空天飞行器姿态运动的模糊滑模鲁棒控制研究

针对空天飞行器(ASV)的姿态系统的非线性、强耦合和不确定性,提出了一种分散模糊滑模变结构控制方法.首先基于反馈线性化方法将ASV姿态系统解耦成3个独立的子系统;然后应用模糊滑模变结构控制方法分别设计了各子系统的姿态控制器.通过结合模糊控制与滑模变结构控制,有效抑制了ASV姿态系统的建模误差以及外部干扰.理论分析和仿真研究表明,所提方法具有控制精度高、鲁棒性强、便于工程实现等优点.     

基于神经网络仿射非线性系统滑模自适应控制

研究了一类单输入单输出仿射非线性系统的自适应控制问题.采用反馈线性化方法设计控制器,用神经网络逼近系统中的未知非线性函数,并在神经网络权值的自适应律中引入权值误差的概念,以改善系统的动态性能.同时采用滑模控制方法设计补偿器,提高了系统的鲁棒性.理论分析及仿真结果表明,所设计的控制器,不仅能解决该系统的轨迹跟踪控制问题,...     

基于模糊神经网络滑模控制器的一类非线性系统自适应控制

本文研究了一类不确定性非线性系统的自适应控制,在模糊神经网络滑模控制器（Ｆｕｚｚｙ ｎｅｒｕａｌ Ｎｅｔｗｏｒｋｓ sｌｉｄｉｎｇ Ｍｏｄｅ Ｃｏｎｔｒｏｌｌｅ ）的基础上提出了一种设计方法,将ＦＮＮＳＭＣ与带死区的滑模控制器（Ｓｌｉｄｉｎｇ ｍｏｄｅ Ｃｏｎｔｒｏｌｌｅｒ ｗｉｔｈ Ｄｅａｄ Ｚｏｎｅ）有机结合,通过平滑切换实现自适应控制,这种方法使系统不仅有好的鲁棒性而且能有效地消除离频动,同时     

空天飞行器模糊自适应轨迹线性化控制器设计

针对一类单输入单输出非线性不确定系统,提出了模糊自适应轨迹线性化控制(TLC)方法并应用于空天飞行器(ASV)飞行控制系统设计.利用模糊系统具有以任意精度逼近非线性系统的能力对未知干扰和不确定进行估计,以减小其对系统性能的影响,并通过鲁棒控制项来克服模糊系统的逼近误差.采用Lyapunov方法,证明了闭环系统所有信号一致最终有界.最后利用提出的控制方案设计了空天飞行器飞行控制系统,并在高超声速条件下进行了仿真验证,仿真结果表明了该方法的有效性和鲁棒性.     

基于滑模控制的四旋翼飞行器控制器设计

基于四旋翼飞行器的结构和飞行原理,本文建立了其飞行动力学数学模型,并采用反馈线性化原理对该模型进行精确线性化;同时,本文采用基于趋近律的滑模变结构控制方法,进行飞行控制器设计,并用simulink对设计的控制器进行仿真,实现了四旋翼飞行器的定高悬停控制,提高了其飞行性能和鲁棒性。     

BTT导弹再入飞行滑模控制器设计研究

针对导弹再入段的非线性模型以及三通道问的较强耦合,给出了倾斜转弯BIT导弹再入飞行鲁棒控制方法.在给定可用制导指令和干扰、不确定性的上界条件下,综合利用快慢双回路连续滑模控制方法,生成气动舵面的控制指令,得到了在建模误差和外界干扰存在的情况下拥有高精度、鲁棒性和解耦特性的气动角和姿态角速率跟踪结果.采用了两种方法抑制滑模的抖振现象:一是构筑滑模干扰观测器,自适应调节增益;二是利用高阶滑模控制方法,有效消除了控制抖振,保证了工程实际应用的能力.以某型BTT导弹为例,仿真结果表明,在考虑到模型不确定性、风扰动以及测量噪声的情况下,两种方法均可靠,满足再入控制的要求.     

三罐耦合系统滑模控制器设计与性能分析

文中针对多输入、多输出的非线性三罐耦合系统，提出了一种基于积分滑模的液位控制方法，该方法能够使系统底部储液罐的液位在动态中达到设定的目标点并保持稳定。在控制器设计过程中，采用积分滑模技术，其引入了滑模变量函数，使得系统可以免受来自内部及外部干扰的影响。通过李雅普诺夫方法，从理论上证明了滑动平面的稳定性。仿真结果验证了该方法对于三罐耦合系统液位控制的有效性。     

模糊变结构控制器的设计与仿真

为解决变结构控制中的抖振问题, 将模糊控制引入变结构控制, 运用MATLAB软件进行仿真。仿真结果验证了该控制器抗扰动能力强, 能够有效减小控制系统的抖动, 提高控制系统的稳定性, 改善控制系统的动态性, 从而减弱变结构系统存在的抖振问题。     

适用于制导控制一体化的反馈线性化滑模控制方法

为提高导弹在打击大机动,高速目标时的稳定性、准确性,提高燃油利用率,在此设计了一种适用于制导控制一体化的小波神经网络反演方法(WNNBM)。首先,将包含目标运动学特性的视线角速度与包含导弹自身动力学的系统模型相结合,建立并简化了俯仰通道制导控制一体化模型,综合设计制导律与控制器;其次,利用线性化反馈的方法对一体化控制器进行设计,并针对一体化模型简化程度高,不确定性明显,未建模动态难以确定的特点,在线性化反馈控制中加入了滑模项,保证系统整体的鲁棒性;最后,进行弹道仿真。结果表明,该方法可以有效打击目标,反馈线性化的滑膜控制方法可以有效提高系统性能。     

空空导弹三维自适应模糊滑模制导律设计

提出了一种基于自适应模糊滑模控制的空空导弹三维制导律,解决了一般滑模控制中存在的抖振问题.该制导律在非线性系统的精确模型未知的情况下,通过模糊系统对非线性模型进行逼近,并根据Lyapunov方法设计了参数自适应律.仿真结果表明,该制导律与比例制导相比有较大的性能改善.     

航空发动机模糊滑模变结构控制研究

针对航空发动机是一个具有时变不确定性的非线性系统,结合模糊控制和滑模变结构控制的特点,提出了一种基于模糊滑模变结构控制的航空发动机控制方法.采用线性滑模面和指数趋近律设计变结构控制器,应用模糊逻辑系统自适应调节切换增益,避免了传统滑模变结构控制系统在到达阶段对不确定性的敏感性,消除了滑模控制中的抖振.通过数字仿真,结果表明所设计的模糊滑模变结构控制器对系统的参数摄动和外部干扰具有不变性,使被控系统在整个控制阶段都具有较强的鲁棒性.     

Adaptive sliding controller with self-tuning fuzzy compensation for vehicle suspension control

Since the hydraulic actuating suspension system has nonlinear and time-varying behavior, it is difficult to establish an accurate dynamic model for a model-based sliding mode control design. Here, a novel model-free adaptive sliding controller is proposed to suppress the position oscillation of the sprung mass in response to road surface variation. This control strategy employs the functional approximation technique to establish the unknown function for releasing the model-based requirement. In addition, a fuzzy scheme with online learning ability is introduced to compensate the functional approximation error for improving the control performance and reducing the implementation difficulty. The important advantages of this approach are to achieve the sliding mode controller design without the system dynamic model requirement and release the trial-and-error work of selecting approximation function. The update laws for the coefficients of the Fourier series functions and the fuzzy tuning parameters are derived from a Lyapunov function to guarantee the control system stability. The experimental results show that the proposed control scheme effectively suppresses the oscillation amplitude of the vehicle sprung mass corresponding to the road surface variation and external uncertainties, and the control performance is better than that of a traditional model-based sliding mode controller.     

Enhanced fuzzy sliding mode controller for active suspension systems

We proposed a fuzzy sliding mode controller (FSMC) to control an active suspension system and evaluated its control performance. The FSMC employed the error of the sprung mass position and the error change to establish a sliding surface, and then introduced the sliding surface and the change of the sliding surface as input variables of a traditional fuzzy controller (TFC) in controlling the suspension system. However, no substantial improvement in the ride comfort could be obtained with the FSMC relative to the TFC because the dynamic effect of the sprung mass acceleration from the bouncing tire during tire rotation was not eliminated. We have developed an enhanced fuzzy sliding mode controller (EFSMC) that maintained not only the original FSMC property but also introduced an assisted FSMC to address and compensate for this problem, and to enhance the road-holding capability of the vehicle. The assisted FSMC differs from the original FSMC only in using the sprung mass acceleration instead of the sprung mass position as a variable of the controller design. The EFSMC exhibits better control performance than either the TFC or the FSMC, in suppressing the acceleration of the vehicle body to improve the ride quality, and in reducing the tire deflection to increase the road-holding ability of a car, as confirmed by experimental results.     

导弹电液伺服机构的自适应模糊滑模跟踪控制

针对导弹电液伺服机构的跟踪控制问题,提出了一种自适应模糊滑模的设计方案.使用具有参数在线调节的自适应模糊控制,逼近滑模控制中的等效控制部分,并确定非线性控制项以保证系统的稳定性.根据滑模控制原理给出四条模糊规则,以平滑不连续控制,达到削弱抖振的目的.仿真结果表明了该方案的有效性.     

A fuzzy logic sliding mode controlled electronic differential for a direct wheel drive EV

In this study, a direct wheel drive electric vehicle based on an electronic differential system with a fuzzy logic sliding mode controller (FLSMC) is studied. The conventional sliding surface is modified using a fuzzy rule base to obtain fuzzy dynamic sliding surfaces by changing its slopes using the global error and its derivative in a fuzzy logic inference system. The controller is compared with proportional–integral–derivative (PID) and sliding mode controllers (SMCs), which are usually preferred to be used in industry. The proposed controller provides robustness and flexibility to direct wheel drive electric vehicles. The fuzzy logic sliding mode controller, electronic differential system and the overall electrical vehicle mechanism are modelled and digitally simulated by using the Matlab software. Simulation results show that the system with FLSMC has better efficiency and performance compared to those of PID and SMCs.