基于鲁棒控制Lyapunov 函数的非线性预测控制

针对一类约束不确定性非线性仿射系统,提出一种可保证闭环系统鲁棒镇定的非线性模型预测控制算法.利用鲁棒控制Lyapunov函数得到改进的Sontag公式,并以此为基础,构造一种计算有效的单自由度鲁棒预测控制器.以Matlab语言为仿真工具,对一开环不稳定振荡器进行了仿真研究,结果表明,利用该控制算法得到的闭环系统不仅渐近稳定于原点,而且所得控制量和系统状态都满足系统约束,从而验证了控制算法的有效性.     

基于障碍Lyapunov函数的未知控制方向非线性系统的约束鲁棒输出调节

本文研究一类不确定非线性系统的约束鲁棒输出调节问题. 在具有未知控制输入方向的情况下, 要求被控线性系统的受控输出在趋近于零的同时, 被限制在给定的范围内. 文章结合障碍Lyapunov函数和Nussbaum增益技术, 进行反馈控制器的设计. 通过MATLAB仿真验证了控制算法的合理性. 同时, 与基于二次型Lyapunov函数设计的仿真结果进行对比, 表明了控制算法的有效性     

基于量化依赖Lyapunov函数的有界丢包网络控制系统的保成本控制

研究了一类具有有界丢包的网络控制系统（Networked control systems,NCSs）的保成本控制问题,提出了一种包含量化反馈的网络控制系统数学模型,该模型将系统的镇定问题转化为镇定一系列子系统的鲁棒控制问题.在对网络控制系统的分析中,区别于常用的二次型Lyapunov函数,本文采用了一种新的且能够降低保守性的量化依赖Lyapunov函数方法.基于本文的Lyapunov函数,得到了充分考虑丢包过程的保成本控制器的设计方法.仿真算例验证了所给出方法的有效性.     

全状态约束的时滞系统神经网络输出反馈控制

针对一类严格反馈形式的单输入单输出时滞系统,研究在全状态约束下的输出反馈控制.首先,设计状态观测器估计不可测量的状态;其次,利用RBF神经网络逼近未知的非线性函数,利用障碍Lyapunov函数确保全状态约束及Lyapunov-Krasovskii方法消除时滞对系统的影响;最后,设计输出反馈控制器,并且有更少的更新参数减少了计算负荷.所设计的控制器可以保证闭环系统中所有信号半全局一致最终有界,信号误差收敛到小的领域内.仿真例子进一步验证了所提出方法的有效性.     

线性多变量系统的控制Lyapunov函数构造

提出线性多变量系统控制Lyapunov函数(CLF)构造的一般方法. 先证明可以通过解一类Lyapunov方程, 得到线性系统二次型的CLF. 接着证明了对于线性系统, 这种方法可以提供所有二次型的CLF. 最后证明了若线性系统存在CLF, 那么必存在二次型的CLF. 由此完全解决了线性系统的CLF构造问题.     

具有未建模动态和输出约束系统的自适应输出反馈控制

针对一类具有未建模动态和输出约束的输出反馈非线性系统, 提出一种自适应输出反馈动态面控制方案. 利用神经网络逼近未知连续函数, 分别设计K滤波器和动态信号估计不可测量的状态, 并处理动态不确定性. 引入障碍李雅普诺夫函数并设计自适应控制器以保证BLF有界, 从而实现输出约束. 理论分析表明, 闭环控制系统是半全局一致终结有界的, 且满足输出约束, 仿真结果验证了所提出方案的有效性.     

具有未知输出函数的非线性系统全局输出反馈控制

研究了一类具有未知输出函数的非线性系统全局输出反馈控制问题．由于输出函数未知,传统的观测器将无法实现．为解决这个问题,首先设计了一个与输出函数无关的状态补偿器,使得标称线性系统全局渐近稳定．然后,应用齐次控制方法通过适当选择增益参数,使得不确定非线性系统在有限时间内全局渐近稳定．数值算例表明该算法的有效性．     

基于快速输出采样反馈的网络控制系统滑模控制

针对网络控制系统的网络诱导时延问题,提出了一种新的滑模控制方法。通过快速采样被控对象输出,建立了具有线性时不变被控对象的网络控制系统的离散模型。在此基础上,用极点配置法给出了滑模切换面参数,设计了输出反馈离散滑模控制器。仿真结果验证了该控制方法的有效性。     

考虑输出约束的机械臂自适应神经网络鲁棒控制

在工业机械臂系统的跟踪控制过程中,由于其结构和工作环境复杂,导致难以建立精确的系统模型,针对此问题提出了基于多层前馈神经网络的自适应鲁棒控制器。通过神经网络在线估计机械臂系统动力学模型,并在控制器中进行补偿,同时设计了一个在线更新的鲁棒项克服神经网络的重构误差;考虑机械臂实际系统的输出约束,采用障碍李雅普诺夫函数设计控制律并证明系统的稳定性从而使系统满足约束条件。仿真实验结果表明:在约束条件下所提出的控制器能够实现系统的一致最终有界稳定,且跟踪性能良好,并具有很好的抗干扰和自适应能力。     

基于输出反馈的欠驱动TORA系统的有界输入控制

针对欠驱动TORA (Translational oscillations with a rotational actuator)系统, 设计了一种具有执行器饱和约束的输出反馈控制器.与其他现有方法相比, 本文方法不仅考虑了执行器饱和约束和速度信号不可测情形, 而且考虑了旋转小球可能存在的循环行为.具体而言, 首先根据TORA系统模型分析了TORA系统的控制目标; 随后, 构造了一种新颖的能量函数, 在此基础上设计了一种考虑执行器饱和约束的输出反馈控制器, 并通过严格的数学分析证明了闭环系统关于平衡点的稳定性; 最后, 借助数值仿真测试检验了所提控制器的控制性能, 并与已有方法进行了对比.仿真测试结果表明本文所提方法具有更好的控制性能.     

Tracking control for output-constrained nonlinear switched systems with a barrier Lyapunov function

This article focuses on the tracking control problem for switched nonlinear systems in strict-feedback form subject to an output constraint. In order to prevent transgression of the constraint, a barrier Lyapunov function is employed, which grows to infinity when its arguments approach domain boundaries. Under the simultaneous domination assumption, a continuous controller for the switched system is constructed. Furthermore, asymptotic tracking is achieved without violation of the constraint, and all closed-loop signals keep bounded, when a mild requirement on the initial condition is satisfied. Finally, a simulation example is provided to illustrate the effectiveness of the proposed results.     

输出受限迟滞非线性系统的反步控制器设计

针对一类含有Bouc-Wen迟滞的输出受限非线性系统设计了反步控制器.首先分析了Bouc-Wen模型的特性并得到其上界值,然后设计了对称型障碍Lyapunov函数(barrier Lyapunov function,BLF),保证了BLF有界,从而满足了输出受限的条件,最后利用反步法设计控制器.该方法消除了迟滞引起的振荡和超调并且使得系统输出约束在设定的范围内,同时解决了迟滞和系统输出受限两个方面的影响,提高了控制精度.仿真和实验结果表明了控制方法的可行性.     

Control of nonlinear systems with partial state constraints using a barrier Lyapunov function

This article addresses the problem of control design for strict-feedback systems with constraints on the states. To prevent the states from violating the constraints, we employ a barrier Lyapunov function (BLF), which grows to infinity whenever its arguments approaches some finite limits. Based on BLF-based backstepping, we show that asymptotic output tracking is achieved without violation of any constraint, provided that the initial states and control parameters are feasible. We also establish sufficient conditions to ensure feasibility, which can be checked offline without precise knowledge of the initial states. The feasibility conditions are relaxed when handling the partial state constraint problem as compared to the full state constraint problem. In the presence of parametric uncertainties, BLF-based adaptive backstepping is useful in preventing the states from transgressing the constrained region during the transient stages of online parameter adaptation. To relax the feasibility conditions, asymmetric error bounds are considered and asymmetric barrier functions are used for control design. The performance of the BLF-based control is illustrated with two simulated examples.     

Barrier Lyapunov Functions for the control of output-constrained nonlinear systems

In this paper, we present control designs for single-input single-output (SISO) nonlinear systems in strict feedback form with an output constraint. To prevent constraint violation, we employ a Barrier Lyapunov Function, which grows to infinity when its arguments approach some limits. By ensuring boundedness of the Barrier Lyapunov Function in the closed loop, we ensure that those limits are not transgressed. Besides the nominal case where full knowledge of the plant is available, we also tackle scenarios wherein parametric uncertainties are present. Asymptotic tracking is achieved without violation of the constraint, and all closed loop signals remain bounded, under a mild condition on the initial output. Furthermore, we explore the use of an Asymmetric Barrier Lyapunov Function as a generalized approach that relaxes the requirements on the initial conditions. We also compare our control with one that is based on a Quadratic Lyapunov Function, and we show that our control requires less restrictive initial conditions. A numerical example is provided to illustrate the performance of the proposed control.     

Adaptive prescribed performance sliding mode control based on time-varying barrier function

In this paper, a nonoverestimated adaptive prescribed performance sliding mode control algorithm based on time-varying barrier function is proposed, for high-order integrator systems subject to bounded but unknown disturbances. The developed algorithm has some remarkable features. Firstly, it is able to ensure that the system states are confined in a performance function from the initial instant. Secondly, it is easy-implementable and some exponential stability and practical fixed-time stability algorithms can be easily obtained. Finally, with the system states to be known, the size of the performance function is independent of the upper bound of the external disturbance. To show the efficiency of the developed algorithm, some numerical simulations are provided.     

Lyapunov function design for finite-time convergence analysis: “Twisting” controller for second-order sliding mode realization

A generalization of the Zubov method of a Lyapunov function design is presented. It is based on the characteristic method application and is related to resolving the first-order partial differential equation of a special type. A successful resolution of this equation guaranties a finite-time convergence for the corresponding dynamics given by an ordinary differential equation with a discontinuous right-hand side. The suggested method is illustrated by its application to the so-called “twisting” controller stability analysis. The constructed Lyapunov function as well as its level line sections is graphically illustrated.     

基于反步法的移动机器人鲁棒跟踪控制

以四轮移动机器人为研究对象,建立了机器人完整的数学模型,包括运动学模型、动力学模型以及驱动电机模型。在机器人数学模型的基础上,采用反步法的思想设计具有全局收敛特性的鲁棒轨迹跟踪控制器,设计中考虑了驱动电机模型使控制器更符合实际控制要求,并将其分解为运动学控制器、动力学控制器以及电机控制器三部分,降低了控制器设计的难度。构造了系统的李雅普诺夫函数,证明了该类型移动机器人在所得控制器作用下,能实现对给定轨迹的全局渐近追踪。仿真实验结果表明基于反步法的控制器是有效的。     

一类非匹配不确定非线性系统的鲁棒跟踪控制制

针对一类半严格反馈型不确定非线性系统,提出一种鲁棒反演滑模变结构控制方法.采用反演控制方法设计了使前n-1阶子系统稳定的虚拟控制律,抑制非匹配不确定性的影响;在第n步设计了一种连续可导的滑模变结构控制律,消除控制抖振,实现了对存在未知不确定性及扰动系统的鲁棒输出跟踪.通过Lyapunov定理证明了闭环系统所有信号最终有界.仿真结果验证了该方法的有效性.