一类具有积分输入到状态稳定未建模动态的高阶非线性系统的状态反馈调节

本文研究了一类具有积分输入到状态稳定(iISS)未建模动态的高阶非线性系统的状态反馈调节问题.基于反推技术和iISS的性质,通过恰当地选取设计函数和参数修正律,给出了一个状态反馈控制器的设计过程.设计的控制器保证了闭环系统所有信号的有界性,并且状态渐近调节到零.仿真例子验证了该控制方案的有效性.     

具有 iISS 逆动态的非线性系统的输出反馈调节

研究了具有积分输入状态稳定 (Integral input-to-state stability, iISS)逆动态和未知控制方向的更一般的非线性系统的输出反馈调节问题. 利用自适应反推的方法, 所设计的输出反馈控制器使得闭环系统的输出调节到原点, 并且闭环系统的其他信号有界.     

一类具有未知控制方向非线性系统的输出反馈自适应控制

研究了一类控制方向未知非线性系统的输出反馈自适应镇定问题. 首先, 通过一线性状态变换, 将未知控制系数集中起来, 从而将原系统变换为适于控制设计的新系统. 然后, 分别引入状态观测器和参数估计器, 并应用积分反推和调节函数方法, 给出了输出反馈稳定控制律的构造性设计过程. 可以证明,所设计的控制器确保原系统状态渐近收敛到原点, 而其它闭环系统状态有界. 仿真结论验证了所提出方法的有效性.     

严格反馈非线性系统的自适应神经网络输出反馈控制

基于非线性反馈函数,文章设计神经网络状态观测器,解决一类非线性系统的输出反馈控制问题.非线性反馈神经网络观测器在系统存在不确定性函数的情况下实时估计系统状态.利用所获得的状态信号,设计了自适应神经网络动态面控制器,同时保证了闭环系统的稳定性和所有信号的有界性.通过调节设计参数的取值能够达到期望的闭环跟踪性能.数值仿真表明,所设计的状态观测器不需要对原系统做状态变换,能够克服输出反馈滑模控制器带来的抖震问题.     

带有界扰动的一类非线性系统的鲁棒控制

对带有界扰动的一类非线性系统进行了状态反馈控制设计. 当状态反馈控制律作用于该系统时, 系统的状态能够收敛到原点的一个小邻域内.     

基于广义预测控制和扩展状态观测器的永磁同步电机控制

在电动汽车等工况复杂的系统中,实现永磁同步电机驱动系统的快响应和强鲁棒性控制历来是研究的重点和难题.预测控制策略可实现快速的动态响应,但依赖电机的数学模型.本文结合广义预测控制理论和扩展状态观测器,提出了一种新型的永磁同步电机转速跟踪控制方法.首先基于连续时间非线性系统的广义预测控制方法,设计了速度跟踪控制器;然后针对外部扰动引起的电机性能下降问题,设计了扩展状态观测器估计系统扰动,通过对扰动量的补偿,提高了鲁棒性;而且控制器参数容易调节.试验结果表明,电机从静止到1000 r/min,与PI控制相比,超调量小,响应速度快.特别是在电机运行过程中外加负载扰动时,转速跌落更小,且更快的恢复到给定值.     

非仿射系统的自适应观测器自抗扰控制

研究了一类单输入单输出(SISO)非仿射非线性系统的控制问题,通过微分同胚变换以及自抗扰思想将该类形式转化成含有未知非线性且控制增益未知的仿射形式.引入扩展状态自适应观测器以及Nussbaum-type增益技术,利用积分反演和调节函数技术,设计了自抗扰控制器.从理论上证明了所设计的控制器能够保证闭环系统所有信号全局一致有界,并且证明了跟踪误差渐近收敛到零点的残集内.仿真例子验证了算法的有效性.     

带有输入和状态时滞的高阶非线性前馈系统的自适应控制

本文考虑了一类高阶不确定非线性前馈系统的自适应镇定问题.将高阶非线性进一步放宽到不仅允许状态时滞,而且还具有未知增长率.通过将自适应方法、动态增益控制方法和增加幂次积分器法结合,设计了一个状态反馈控制器.所设计的控制器保证了闭环系统的所有信号有界,平衡点全局稳定,并且原状态收敛到0.     

基于状态演算的通用游戏系统的自动推理

为提高通用游戏系统的自动推理能力,提出了基于状态演算的通用游戏系统的自动推理方法,并将其作为推理模块构建了通用游戏系统模型.利用状态演算逻辑程序设计语言(state calculus executor,STEX)实现通用游戏的状态更新与动作推理,给出了基于状态演算的通用游戏系统模型的功能模块设计,最后利用prolog语言实现了各功能模块,调试系统并进行实例验证.实验结果表明,采用了基于状态演算的自动推理方法,得到较好的游戏成绩,提高了游戏系统的自动推理能力.     

基于状态空间的机械臂轨迹规划

提出一种基于状态空间的机械臂轨迹规划方法,定义并构造了机械臂系统的状态空间,根据内在机构约束与外部环境约束描述出系统状态的可达范围,并给出了任务的可实现条件.对于可实现任务,在状态空间能搜索到任务完成的最优解.如果任务无法完成,则修改系统配置或约束,在新的状态空间确定任务实现的转化条件,并对任务的设计与规划给予指导.研究了障碍约束下两连杆机械臂的点到点任务,实验结果验证了该方法的有效性.     

Adaptive state-feedback stabilization for high-order stochastic non-linear systems with uncertain control coefficients

This paper investigates the adaptive state-feedback stabilization problem for a class of high-order stochastic non-linear systems with unknown lower and supper bounds for uncertain control coefficients. Under some weaker and reasonable assumptions, a smooth adaptive state-feedback controller is designed, which guarantees that the closed-loop system has an almost surely unique solution on [0,∞, the equilibrium of interest is globally stable in probability and the states can be regulated to the origin almost surely. A simulation example is given to show the systematic design and effectiveness of the controller.     

Fixed-Time Lyapunov Criteria and State-Feedback Controller Design for Stochastic Nonlinear Systems

This paper investigates the fixed-time stability theorem and state-feedback controller design for stochastic nonlinear systems. We propose an improved fixed-time Lyapunov theorem with a more rigorous and reasonable proof procedure. In particular, an important corollary is obtained, which can give a less conservative upper-bound estimate of the settling time. Based on the backstepping technique and the addition of a power integrator method, a state-feedback controller is skillfully designed for a class of stochastic nonlinear systems. It is proved that the proposed controller can render the closed-loop system fixed-time stable in probability with the help of the proposed fixed-time stability criteria. Finally, the effectiveness of the proposed controller is demonstrated by simulation examples and comparisons.      

一类控制系数未知但等同高阶非线性系统的稳定控制设计

本文研究了一类控制系数未知但等同高阶非线性系统的状态反馈稳定控制设计问题. 尽管该类系统具有不确定性, 即控制系数未知,但本文没有采用自适应技术, 而是通过选取适当的设计参数, 从而得到了设计该类非线性系统稳定控制器的新方法, 并基于反推技术, 给出了稳定控制器的设计步骤. 所设计的状态反馈控制器使得闭环系统全局渐近稳定, 并保持在原点的平衡性.     

Periodically time-varying memory state-feedback controller synthesis for discrete-time linear systems

In this paper, we deal with discrete-time linear periodic/time-invariant systems with polytopic-type uncertainties and propose a new linear matrix inequality (LMI)-based method for robust state-feedback controller synthesis. In stark contrast with existing approaches that are confined to memoryless static controller synthesis, we explore dynamical controller synthesis and reveal a particular periodically time-varying memory state-feedback controller (PTVMSFC) structure that allows LMI-based synthesis. In the context of robust controller synthesis, we prove rigorously that the proposed design method encompasses the well-known extended-LMI-based static controller synthesis methods as particular cases. Through numerical experiments, we demonstrate that the suggested design method is indeed effective in achieving less conservative results, under both periodic and time-invariant settings. We finally derive a viable test to verify that the designed robust PTVMSFC is “exact” in the sense that it attains the best achievable robust performance. This exactness verification test works fine in practice, and we will show via a numerical example that exact robust control is indeed attained by designing PTVMSFCs, even for such a problem where the standard memoryless static state-feedback fails.     

一类高阶非线性不确定系统自适应稳定控制

研究了一类高阶非线性不确定性系统的自适应稳定控制设计问题.因该系统的非线性程度高,其控制系数不等同、符号已知、但数值未知,故在此之前其稳定控制设计问题没有得到解决.本文应用自适应技术,结合设计参数的适当选取,从而得到了设计该类非线性系统状态反馈稳定控制器的新方法,并基于反推技术,给出了稳定控制器的设计步骤.所设计的状态反馈控制器使得闭环系统的状态全局渐近收敛于零,其余闭环信号一致有界.最后通过一个仿真例子说明了控制设计方法的有效性.     

输入饱和的一类切换系统神经网络跟踪控制

针对单输入单输出系统研究一种在任意切换下的跟踪控制问题,系统包含未知扰动和输入饱和特性.首先,利用高斯误差函数描述一个连续可导的非对称饱和模型.其次,利用径向基神经网络（Radial basis function neural network,RBF NN）逼近未知的系统动态.最后,基于公共的Lyapunov函数构造状态反馈控制器.设计的控制器避免过多参数调节从而减轻计算负荷.结果展示本文给出的状态反馈控制器可以保证闭环系统的所有信号是半全局一致有界的,并且跟踪误差可收敛到零值小的领域内.最后的仿真结果进一步验证提出方法的有效性.     

Reduced-order observer-based output feedback regulation for a class of nonlinear systems with iISS inverse dynamics

Global asymptotic regulation via output feedback based on a reduced-order observer is considered for a class of nonlinear systems with integral input-to-state stable (iISS) inverse dynamics. The contributions are that: (1) we further consider the conditions on changing supply rates in iISS systems, and discuss the necessity of some conditions by constructing a counter-example; (2) For a more general class of nonlinear systems with iISS inverse dynamics, a reduced-order observer is introduced, and by the combined approach of backstepping and changing iISS supply rates, an output feedback controller is given to drive the output of system to the origin asymptotically and maintain other closed-loop signals bounded.     

一类高阶随机非线性系统的状态反馈镇定

针对一类既不可反馈线性化也不仿射于控制输入的高阶随机非线性系统,研究其状态反馈镇定问题.利用齐次占优和反推技术,所设计的状态反馈控制器使得整个闭环系统在[0,+∞)上几乎处处有唯一解,并使得闭环系统的平衡点是依概率全局渐近稳定的.主要贡献是完全取消了高阶系统的阶次限制,得到了新的结果.最后通过数值仿真验证了所提出控制方案的有效性.     

An adaptive partial state-feedback controller for RLED robotmanipulators

An adaptive partial state-feedback controller is designed for rigid-link electrically driven (RLED) robot manipulators. The controller is based on structural knowledge of the electromechanical dynamics of the RLED robot and measurements of link position and electrical winding current in each of the brushed DC link actuators. The proposed controller is designed to adapt for parametric uncertainty in the electromechanical dynamics while utilizing a dynamic filter to generate link velocity tracking error information. The controller, adaptation laws, and the pseudovelocity filter are designed via a Lyapunov-like approach, the benefit of which is that at the end of the design procedure the controller can be mathematically shown to produce semiglobal asymptotic link position tracking. The basic design approach can be extended to many types of multiphase motors