一类带有加速度约束的非线性系统最优滑模控制

针对加速度受约束的非线性时变系统,设计了一种全局最优滑模控制算法.首先引入全程滑态因子,保证滑模面一开始就在零值附近,然后选取位置跟踪误差绝对值的积分为指标函数,通过求解该指标函数的最小值来确定滑模面方程的相关参数,最后设计了基于指数趋近律的滑模控制算法.仿真结果表明了该方法的有效性和强鲁棒性.     

基于模糊树模型的自适应模糊滑模控制方法

本文针对单输入–单输出仿射非线性系统提出了一种基于模糊树模型的具有监督控制器的模糊滑模控制方法. 该方法用模糊树模型逼近非线性系统中的未知非线性函数, 得到初始的控制器, 然后在线调节模糊树模型中的线性参数, 改善控制器的性能, 实现对有界参考输入信号的跟踪控制. 模糊树辨识方法自适应划分输入空间, 大大减少模糊规则的数目, 在一定程度上可以缓解困扰模糊控制中的”规则爆炸”问题. 该方法通过监督控制器保证闭环系统所有信号有界. 通过理论分析, 证明了跟踪误差收敛到零. 用倒立摆进行仿真验证, 结果表明该方法用较少的模糊规则, 就能得到满意的控制效果, 有推广应用价值.     

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.     

非仿射非线性离散系统的数据驱动二阶滑模解耦控制

针对传统二阶离散滑模变结构控制方法很难应用于模型未知系统的问题,提出了一种数据驱动二阶滑模解耦控制算法.该控制算法采用数据驱动的策略,运用系统的I/O数据,实时计算二阶离散滑模控制(2–DSMC)律.同时,运用观测器的思想,在控制器设计中引入离散扩张状态观测器(DESO),在线估计系统各回路间耦合、不确定性和外部扰动,进一步实现系统的解耦,改善控制品质.最后的理论分析和仿真结果表明,所提出的方法对于一般带有扰动和不确定性的非仿射非线性离散多入多出(MIMO)系统具有较好的解耦效果、渐进收敛的稳定性和较强的鲁棒性.     

不确定非线性系统的高阶滑模控制器设计

针对一类不确定非线性SISO系统,结合系统有限时间稳定理论与积分滑模控制理论,提出了一种新的高阶滑模控制器设计方法,改善了现有高阶滑模控制中存在的缺陷.积分滑模保证了系统初始时刻就具有抗扰能力,同时采用有限时间稳定观测器实现了高阶滑模的输出反馈控制.仿真结果表明该控制器可使系统在有限时间内收敛,并有效地减小了系统抖振.     

不确定非完整动力学系统的自适应模糊滑模控制器

为研究不确定非完整动力学系统的收敛性, 根据速度跟踪原理, 对其提出一种新的自适应模糊滑模控制器. 该控制器在存在的参数不确定性与外界干扰的情况下, 能使系统的广义坐标与广义速度收敛到预先给定的界内. 仿真算例验证了所提出方法的有效性.     

一类复杂非线性系统的模糊控制

针对一类复杂非线性系统,把模糊T-S模型和自适应模糊逻辑系统结合起来,提出了一种跟踪控制方案.首先,应用模糊T-S模型对非线性系统建模,设计观测器用来观测系统状态:其次,应用基于权值、中心和宽度3个参数可调节的自适应时延模糊逻辑系统补偿器来消除建模误差和小确定性.文中证明了闭环系统满足期望的跟踪性能.示例仿真结果表明了该方案的有效性.     

Fuzzy adaptive sliding-mode control for MIMO nonlinear systems

A stable adaptive fuzzy sliding-mode controller is developed for nonlinear multivariable systems with unavailable states. When the system states are not available, the estimated states from a semi-high gain observer are used to construct the output feedback fuzzy controller by incorporating the dynamic sliding mode. It is proved that uniformly asymptotic output feedback stabilization can be achieved with the tracking error approaching to zero. A nonlinear system simulation example is presented to verify the effectiveness of the proposed controller.     

基于分数阶滑模控制技术的永磁同步电机控制

针对传统整数阶滑模控制系统中存在的抖震问题,本文提出了分数阶滑模控制策略并应用到永磁同步电机的速度控制.传统滑模控制器中的开关函数由作用在切换流型或其整数阶导数面推广到其分数阶导数面,利用分数阶系统的特性,缓慢地传递系统的能量,有效地削减抖震.本文采用模糊逻辑推理算法,实现软开关切换增益的自整定.仿真和实验证明,本文提出的分数阶滑模控制系统不但能有效地削减抖震,而且能保持滑模控制器对系统参数变化和外部扰动的鲁棒性.     

非匹配不确定高阶非线性系统的滑模控制新方法

对具有非匹配不确定的高阶非线性系统,采用改进的高阶滑模微分器获取已知状态的任意阶微分估计值,再以恰当阶次的状态微分估计值之差,得到非匹配不确定项及其微分的估计值,证明了其误差任意小.为避免奇异性和抖振,采用两种方案设计了滑模控制器,并设计鲁棒项提高系统鲁棒性.基于Lyapunov~论证明了系统稳定性.同现有其他方法相比,该方法具有适用范围更广、收敛速度快、控制精度高、运算量小、保守性低等优点.最后仿真证明了本文所有结论.     

基于滑模观测器的多智能体一致性控制

本文针对速度不可测下的多智能体系统提出一种基于滑模观测器的有限时间一致性控制算法.首先, 利用滑模观测器在有限时间内估计每个智能体的速度信息. 然后,利用估计信息设计非奇异终端滑模控制律,该控制律能够保证智能体系统在有限时间内达到一致性. 最后,通过数值仿真验证了该一致性控制算法的有效性.     

Adaptive discrete-time sliding-mode control of nonlinear systems described by Wiener models

In this paper, we propose an adaptive control scheme that can be applied to nonlinear systems with unknown parameters. The considered class of nonlinear systems is described by the block-oriented models, specifically, the Wiener models. These models consist of dynamic linear blocks in series with static nonlinear blocks. The proposed adaptive control method is based on the inverse of the nonlinear function block and on the discrete-time sliding-mode controller. The parameters adaptation are performed using a new recursive parametric estimation algorithm. This algorithm is developed using the adjustable model method and the least squares technique. A recursive least squares (RLS) algorithm is used to estimate the inverse nonlinear function. A time-varying gain is proposed, in the discrete-time sliding mode controller, to reduce the chattering problem. The stability of the closed-loop nonlinear system, with the proposed adaptive control scheme, has been proved. An application to a pH neutralisation process has been carried out and the simulation results clearly show the effectiveness of the proposed adaptive control scheme.     

基于模糊干扰观测器的自适应二阶动态滑模控制

针对一类存在不确定性和外干扰的非线性系统滑模控制的抖振问题,本文首先证明了以高斯函数为隶属度函数的模糊基向量对状态向量的偏导在任意情况下有界,解决了模糊辨识同二阶动态滑模结合的关键问题.然后设计了二阶动态Terminal滑模,有效克服了滑模抖振,且能保证滑模面上的滑动在有限时间内收敛.再基于模糊干扰观测器的输出设计自适应鲁棒补偿项.基于李雅普诺夫理论证明了系统稳定性.最后将本文提出的控制方案用于近空间飞行器姿态角跟踪仿真,并分析了高阶动态滑模收敛时间增加的问题.结果表明本文提出的控制方案跟踪速度快、精度高,且有效去除了抖振.与常规Terminal滑模相比,二阶动态Terminal滑模增加的收敛时间非常有限,适于工程应用.     

L1 adaptive control with sliding-mode based adaptive law

This paper presents an adaptive control scheme with an integration of sliding mode control into the $\mathcal{L}_1$ adaptive control architecture, which provides good tracking performance as well as robustness against matched uncertainties. Sliding mode control is used as an adaptive law in the $\mathcal{L}_1$ adaptive control architecture, which is considered as a virtual control of error dynamics between estimated states and real states. Low-pass filtering mechanism in the control law design prevents a discontinuous signal in the adaptive law from appearing in actual control signal while maintaining control accuracy. By using sliding mode control as a virtual control of error dynamics and introducing the low-pass filtered control signal, the chattering effect is eliminated. The performance bounds between the close-loop adaptive system and the closed-loop reference system are characterized in this paper. Numerical simulation is provided to demonstrate the performance of the presented adaptive control scheme.     

不确定时滞切换系统的鲁棒滑模控制

该文研究了一类具有非匹配不确定性和非线性扰动的时滞切换系统的滑模控制问题.首先,针对每个子系统设计对应的时滞依赖滑模面,利用驻留时间方法,给出了由滑动模态方程组成的切换系统鲁棒渐近稳定的充分条件;然后设计了滑模控制器,使得闭环系统的状态能够到达滑模面上,产生滑动模态.最后,仿真实例说明所提出方法的有效性.     

带有伸缩器和饱和器的一类非线性系统模糊自适应控制设计

本文针对一类带有未知齐次函数的非线性系统,首先基于伸缩器和饱和器的概念,将T-S型模糊逻辑系统的输入–输出进行改造而形成扩展模糊逻辑系统,然后利用扩展模糊逻辑系统给出一种带有可调伸缩因子参数的模糊自适应控制器的设计方法.由于该方法不依赖模糊规则数目,因而不仅能有效减少在线估计的参数数目,而且能够保证被控系统的状态一致终极有界.最后所给数值仿真算例说明了该设计方法的有效性.     

基于滑模变结构的空间机器人神经网络跟踪控制

研究了在无需模型估计值的情况下不确定空间机器人轨迹跟踪问题,提出了滑模变结构的神经网络控制方案.首先基于Lyapunov理论设计了一种径向基函数（RBF）神经网络控制器来补偿系统中的未知非线性,该神经控制器能够保证闭环系统的稳定性,而通过利用饱和函数把神经网络和滑模控制结合起来的控制器来不仅可以进一步削弱滑模控制输入的抖振,且当神经网络控制器无效时仍能保证系统鲁棒性.仿真结果证明了该控制器能在初期及强干扰情况下均能达到较好的控制效果.     

Neural network-based nonlinear sliding-mode control for an AUV without velocity measurements

For an autonomous underwater vehicle (AUV), a nonlinear sliding-mode control based on linear-in-parameter neural network (NSMC-NN) is proposed to deal with the unknown dynamics and the external environmental disturbances and a first-order robust exact differentiator is introduced considering unknown velocities of an AUV. The sliding-mode surfaces of NSMC-NN can enter into the boundary layers after a period that depends on the design parameters. To demonstrate the feasibility of the proposed controller, simulation studies applying Omni-Directional Intelligent Navigator (ODIN) are carried out, compared with proportional–integral–derivative (PID) and the modified sliding-mode control (MSMC). The simulation results show that the presented control method can achieve the effective control performance.     

Finite-time containment control of perturbed multi-agent systems based on sliding-mode control

Aimed at faster convergence rate, this paper investigates finite-time containment control problem for second-order multi-agent systems with norm-bounded non-linear perturbation. When topology between the followers are strongly connected, the nonsingular fast terminal sliding-mode error is defined, corresponding discontinuous control protocol is designed and the appropriate value range of control parameter is obtained by applying finite-time stability analysis, so that the followers converge to and move along the desired trajectories within the convex hull formed by the leaders in finite time. Furthermore, on the basis of the sliding-mode error defined, the corresponding distributed continuous control protocols are investigated with fast exponential reaching law and double exponential reaching law, so as to make the followers move to the small neighbourhoods of their desired locations and keep within the dynamic convex hull formed by the leaders in finite time to achieve practical finite-time containment control. Meanwhile, we develop the faster control scheme according to comparison of the convergence rate of these two different reaching laws. Simulation examples are given to verify the correctness of theoretical results.