基于观测器的四旋翼飞行器自适应滑模姿态控制

针对存在建模不确定性和外部干扰时四旋翼飞行器的姿态控制问题,提出一种基于观测器的自适应滑模控制算法。在建立四旋翼飞行器姿态误差动力学模型的基础上,通过全局渐近收敛观测器获取系统的未知状态反馈量,利用自适应滑模控制抑制系统的不确定性和干扰,构建一种基于观测器的自适应滑模姿态控制器。基于Lyapunov的稳定性分析表明,该方法的跟踪误差是一致最终有界的。数值仿真实验结果表明,与现有滑模控制方法相比,所提方法具有更好的姿态跟踪性能和较高的抗干扰鲁棒性,能有效保证飞行器的姿态跟踪控制性能。     

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.     

重装空投过程的有限时间收敛自适应滑模控制

针对带有不确定性且不确定性边界未知的重装空投过程飞机运动系统,提出了一种有限时间收敛增益自适应滑模控制律。该控制律由标称控制和补偿控制两部分构成,前者用于获得有限时间的收敛性能,后者用于克服不确定性,提高系统鲁棒性。采用自适应方法在线近似补偿控制器的增益,解决了控制增益选取依赖于不确定性边界的问题,并有效抑制了滑模控制的抖振现象。理论分析表明,该方法能够保证飞机速度和俯仰角的跟踪误差有限时间收敛。仿真验证了控制方法的有效性和优越性。     

质心不重合的移动机器人自适应滑模轨迹跟踪控制

针对一类质心和几何中心不重合的移动机器人的轨迹追踪问题,结合反演滑模自适应控制算法设计移动机器人轨迹跟踪控制器.首先,设计一种新的变参数滑模趋近律,并基于该趋近律对移动机器人控制器进行设计,使得系统在给定初始误差时移动机器人仍能跟踪目标轨迹.其次,针对一类质心距离已知的情况,基于移动机器人运动学模型,采用反演滑模控制算法对移动机器人的闭环系统控制器进行设计.并在给定系统初始值的情况下,通过选用合适的参数来优化移动机器人控制系统的整体性能,使得控制系统跟踪误差渐近收敛,移动机器人跟踪给定目标轨迹.然后,针对移动机器人质心距离未知的情况,采用反演滑模控制,引入自适应控制算法对未知参数进行估计,设计轨迹跟踪控制器,并通过Lyapunov函数对移动机器人控制系统进行全局稳定性证明.最后,将设计的新型趋近律结合Backstepping控制与自适应控制通过MATLAB仿真进行对比验证,验证了所设计的控制方法的有效性.     

光电跟踪系统的区间2型模糊滑模控制方法

为了提升高精度光电跟踪系统(ETS)的跟踪精度和其处理不确定性的能力，设计了一种1型模糊滑模控制方法，模糊控制用于在线自适应调整滑模控制(SMC)切换项参数；并采用区间2型模糊滑模控制(IT2FSMC)方法来提高系统处理不确定性的能力，进而提升跟踪精度，同时降低SMC抖振；此外，用粒子群优化算法来保证选取的SMC参数相对最优，并对提出的各种控制方法进行了理论分析和实验对比。结果表明，IT2FSMC能在降低SMC抖振的同时将SMC的稳态误差降低54.43%。仿真和实验分析验证了所提出控制方法在ETS中的有效性。     

一类离散时间系统的间接自适应模糊滑模控制

提出了适用于一类不确定离散时间系统的间接自适应模糊滑模控制策略。首先,根据指数趋近律得到离散滑模控制的理想控制律,然后,用两个模糊系统近似其中的未知函数,用第三个模糊系统近似切换控制。模糊系统的参数向量由带参数投影的自适应律在线调整。证明了该控制算法可以保证闭环系统状态有界,且跟踪误差收敛到原点的小邻域内。仿真结果在表明算法有效性的同时具备减轻振颤的能力。     

一类离散时间系统的间接自适应模糊滑模控制

提出了适用于一类不确定离散时间系统的间接自适应模糊滑模控制策略。首先,根据指数趋近律得到离散滑模控制的理想控制律,然后,用两个模糊系统近似其中的未知函数,用第三个模糊系统近似切换控制。模糊系统的参数向量由带参数投影的自适应律在线调整。证明了该控制算法可以保证闭环系统状态有界,且跟踪误差收敛到原点的小邻域内。仿真结果在表明算法有效性的同时具备减轻振颤的能力。     

机械臂自适应非奇异快速终端滑模控制

针对刚性机械臂有限时间鲁棒控制问题,提出了一种新的自适应非奇异快速终端滑模控制方法.该方法将非奇异快速终端滑模控制与自适应律相结合,使用非奇异快速终端滑模面加快机械臂轨迹跟踪误差的收敛速度,解决了终端滑模中的奇异问题;通过双曲正切函数代替符号函数减小控制输入的抖振;利用自适应律对未知的外部扰动和系统的不确定性进行估计,...     

自适应滑模控制在变形翼飞行器上的应用

针对变形翼飞行器提出了一种自适应滑模控制算法。对形变造成的模型不确定性,采用自适应补偿算法消除其对系统稳定性的影响。将外界的扰动分解成匹配项和不匹配项,设计积分滑模控制完全消除匹配项对系统的影响,同时使不匹配项满足鲁棒性能指标。通过李雅普诺夫稳定性证明自适应积分滑模控制能使跟踪误差一致渐近稳定。最后,在含有不确定项的变形翼飞行器模型上进行仿真,验证算法的可行性和有效性。     

四旋翼飞行器的RBF网络自适应滑模控制

针对带有不确定性的四旋翼飞行器系统,提出一种滑模控制和神经网络自适应相结合的混合控制方法。该方法在滑模控制的基础上,考虑到实际系统中通常存在建模不精确、参数未知等不确定性,构造RBF神经网络在线逼近系统模型的未知函数,采用Lyapunov方法设计自适应律在线估计神经网络权值和模型未知参数,并通过Lyapunov定理验证了系统的稳定性。仿真结果表明,该方法相对于RBF神经网络的自适应PID控制,具有更短的调节时间、更小的超调量和更好的抗干扰能力,同时在模型参数发生变化的情况下,该控制器的鲁棒性能更强。     

不确定分数阶多驱动一响应混沌系统同步

针对一类新的多驱动一响应混沌系统同步方式,基于分数阶系统稳定性理论和Lyapunov稳定性理论,运用追踪控制和滑模自适应控制方法设计了同步控制律和参数自适应律.对象模型考虑了不确定因素的影响,首先选取一类稳定的分数阶滑模曲面,然后提出了一种鲁棒同步方案.最后数值仿真验证了方案的正确性和有效性.     

PID-type sliding mode-based adaptive motion control of a 2-DOF piezoelectric ultrasonic motor driven stage

This paper presents a new scheme of adaptive sliding mode control (ASMC) for a piezoelectric ultrasonic motor driven X–Y stage to meet the demand of precision motion tracking while addressing the problems of unknown nonlinear friction and model uncertainties. The system model with Coulomb friction and unilateral coupling effect is first investigated. Then the controller is designed with adaptive laws synthesized to obtain the unknown model parameters for handling parametric uncertainties and offsetting friction force. The robust control term acts as a high gain feedback control to make the output track the desired trajectory fast for guaranteed robust performance. Based on a PID-type sliding mode, the control scheme has a simple structure to be implemented and the control parameters can be easily tuned. Theoretical stability analysis of the proposed novel ASMC is accomplished using a Lyapunov framework. Furthermore, the proposed control scheme is applied to an X–Y stage and the results prove that the proposed control method is effective in achieving excellent tracking performance.     

Finite-time control of DC–DC buck converters via integral terminal sliding modes

This article presents novel terminal sliding modes for finite-time output tracking control of DC–DC buck converters. Instead of using traditional singular terminal sliding mode, two integral terminal sliding modes are introduced for robust output voltage tracking of uncertain buck converters. Different from traditional sliding mode control (SMC), the proposed controller assures finite convergence time for the tracking error and integral tracking error. Furthermore, the singular problem in traditional terminal SMC is removed from this article. When considering worse modelling, adaptive integral terminal SMC is derived to guarantee finite-time convergence under more relaxed stability conditions. In addition, several experiments show better start-up performance and robustness.     

An adaptive hierarchical control approach of vehicle handling stability improvement based on Steer-by-Wire Systems

This paper proposes a novel adaptive hierarchical control approach for Steer-by-Wire (SbW) vehicles to improve the handling stability. The high-level stability control scheme contains a variable steering ratio (VSR) strategy based on the adaptive-network-based fuzzy inference system (ANFIS) and an active front steering (AFS) controller designed with the integral sliding mode method by tracking the expected yaw rate, in which the desired front wheel angle is generated to enhance the cornering stability performance. Besides, an adaptive tracking controller (ATC) for the SbW system is designed by using the adaptive sliding mode control method to achieve desired steering performance in the lower level. The proposed adaptive control strategy is validated with different driving circles from ISO standards in simulation tests and hardware-in-the-loop (HiL) experiments. The results demonstrate that the designed control approach improve the vehicle handling stability significantly, even in some extreme driving conditions.     

基于投影法的不确定分数阶混沌系统自适应同步

针对一类具有未知参数、未知非线性函数及外部扰动的分数阶混沌系统,基于分数阶系统稳定性理论和Lyapunov稳定性理论,该文提出一种基于滑模自适应和投影法的同步控制策略。首先选取一类稳定的分数阶积分滑模面,运用自适应技术对不确定项进行估计,设计了同步控制器。然后对自适应设计中容易出现的增长型自适应律运用投影法进行修正,以保证参数有界,从而也保证控制输入有界。最后数值仿真证明了所设计控制器的正确性和有效性。     

Adaptive incremental sliding mode control for a robot manipulator

An adaptive incremental sliding mode control (AISMC) scheme for a robot manipulator is presented in this paper. Firstly, an incremental backstepping (IBS) controller is designed using time-delay estimation (TDE) to reduce dependence on the mathematical model. After substituting IBS controller into the nonlinear system, a linear system w.r.t. tracking errors is obtained while TDE error is the disturbance. Then, the AISMC scheme, including a nominal controller and an SMC, is developed for the resulted linear system to improve control performance. According to the equivalent control method, the SMC in the AISMC scheme is to handle TDE error. To receive optimal control performance at the sliding manifold, an LQR controller is selected as the nominal controller. The SMC is designed based on positive semi-definite barrier function (PSDBF) since it prevents switching gains from being over/under-estimated, and two practical problems are addressed in this paper: A new PSDBF is designed and conservative (large) setting bounds affecting tracking precision and/or system stability are avoided; An improved PSDBF based SMC is developed where the PSDBF and an adaptive parameter are used simultaneously to regulate switching gains, and the system is still stable when sliding variable occasionally exceeds the predefined vicinity. Moreover, finite-time convergence property of the sliding variable is strictly analyzed. Finally, real-time experiments are conducted to verify the effectiveness of the proposed control method.     

IBVS based on adaptive sliding mode control for a quadrotor target tracking under perturbations

This paper presents the design of a visual control formulated on an adaptive sliding mode controller for a quadrotor executing a target tracking task subject to disturbances. An image projection of the target from a virtual camera approach, and an image-based visual servoing technique are considered to obtain a singularity-free set of image features to control the position and yaw of the rotorcraft. While, an adaptive sliding mode strategy improves the robustness against bounded external perturbations and uncertainties and provides adaptivity to the visual servoing scheme. Furthermore, an analysis based on Lyapunov theory provides sufficient conditions that guarantee the stability of the closed-loop system. A comparison of the proposed adaptive visual servoing against two recent visual servoing strategies is provided, showing superiority in simulation results. Finally, experimental tests of a Parrot AR.Drone 2.0 tracking a static and moving target further demonstrates the advantages and performance.     

控制增益符号已知的MIMO非线性时滞系统自适应控制

针对一类具有死区模型并且控制增益符号已知的不确定多输入多输出非线性时滞系统,基于滑模控制原理提出了一种稳定的自适应神经网络控制方案。该方案通过使用Lyapunov-Krasovskii泛函抵消了因未知时变时滞带来的系统不确定性。通过利用积分型李亚普诺夫函数,并且构造逼近连续函数,闭环系统证明是半全局一致终结有界。仿真结果表明了该方法的有效性。     

车式移动机器人轨迹跟踪控制方法

针对车式移动机器人轨迹跟踪这一典型控制任务,本文提出一种滑模轨迹跟踪控制方法.该方法采用PI型滑模面设计等效控制律,利用变速函数代替符号函数获得切换控制率,并运用Lyapunov理论证明系统的稳定性.仿真结果表明该方法不但能使机器人有效跟踪任意参考轨迹,而且能减小在控制中的抖振现象,即使在外界干扰影响的情况下,也具有良好的控制品质.