相对阶n*=3系统的鲁棒直接型模型参考自适应控制

针对相对阶n*=3的具有输入和输出未建模动态的一类系统,设计了可以实现的具有未规范化自适应律的鲁棒直接型模型参考自适应控制器,构造了满足引理1性质的自适应律.通过利用Lyapunov稳定性理论及鲁棒自适应控制分析理论,构造误差系统,严格地分析了闭环系统的稳定性和跟踪性能.     

相对阶n= 3 = 3 的鲁棒直接型模型参考自适应控制

针对相对阶n^*=3具有噪声的一类简单系统，给出了具有未规范化自适应律的鲁棒直接型模型参考自适应控制器的设计，通过引入非线性阻尼项，保证了闭环系统的所有信号都是全局稳定的，而且跟踪误差及参数估计误差均收敛于零。     

多变量系统的基于高频增益矩阵分解的直接型模型参考自适应控制

针对相对阶为2的多变量系统,利用高频增益矩阵分解,在适当的假设下,建立了新的参数模型,设计出具有未规范化自适应律的直接型模型参考自适应控制器,保证了闭环系统所有信号的有界性和跟踪误差的收敛性.仿真实例验证了控制方案的有效性.     

间接型的混杂模型参考自适应控制

针对相对阶为1的理想系统,本文考虑了具有混杂自适应律的间接型模型参考自适应控制问题.通过建立系统和控制器的离散参数估计和它们的插值四者之间关系的性质,严格地分析了闭环系统的稳定性,证明了闭环系统中所有的信号都一致有界,并且跟踪误差渐进收敛于零.     

一类直接模型参考Backstepping自适应控制

提出一种新的直接模型参考Backstepping自适应控制系统结构:谈系统在直接模型参考卓适应控制(MRAC)结构的基础上,增加了Beckstepping控制信号发生器,通过Backstepping方法的灵活设计获得良好的过渡过程品质,得到直接MRAC在稳定性和鲁棒性设计等方面的优点.采用高阶调节器设计了未具规范化的直接模型参考Backstepping自适应律,克服了传统自适应律引入规范化信号后使系统过渡过程品质下降的缺点.     

时变系统具有MT-滤波器的反推自适应控制

研究线性时变系统具有MT-滤波器的反推自适应控制问题。给出了具有MT-滤波器和σ修正自适应律的反推自适应控制器的设计，分析了闭环系统的稳定性和跟踪性能。同已有文献相比，难点在于误差系统的构造，并且稳定性的证明更加复杂。     

自适应模糊控制的自平衡机器人设计

在两轮自平衡机器人系统的平衡控制中,为解决因所建立的数学模型不准确和存在未知干扰而影响控制性能的问题,设计了一种自适应模糊控制方法;首先,运用牛顿力学法建立了系统在斜坡上运动的数学模型;基于所建立的非线性动态模型,采用单点模糊化、乘积推理机和中心平均解模糊化的方法构建了自适应模糊逻辑控制器,然后通过李雅普诺夫稳定性分析的方法,导出控制器的自适应律;对自适应模糊控制的两轮自平衡机器人的平衡情况进行了仿真,结果表明,提出的自适应模糊控制器可以实现系统平衡,并具有自适应能力和鲁棒性。     

一类直接模型参考Backstepping自适应控制

提出一种新的直接模型参考Backstepping自适应控制系统结构.该系统在直接模型参考自适应控制(MRAC)结构的基础上,增加了Backstepping控制信号发生器,通过Backstepping方法的灵活设计获得良好的过渡过程品质,得到直接MRAC在稳定性和鲁棒性设计等方面的优点.采用高阶调节器设计了未具规范化的直接模型参考Backstepping自适应律,克服了传统自适应律引入规范化信号后使系统过渡过程品质下降的缺点.

     

基于Kp=LDU分解的多变量离散时间系统鲁棒模型参考自适应控制

针对具有未建模动态且相对阶大于1的一类多变量离散时间系统,利用其高频增益矩阵分解建立新的参数模型,在较弱假设下,进一步研究了直接型鲁棒模型参考自适应控制问题.由离散时间系统的交换引理,建立了闭环系统的所有信号与规范化信号的联系.以一种系统化的方法,严格地分析了闭环系统的稳定性与鲁棒性.     

两轮自平衡机器人的自适应模糊平衡控制

在两轮自平衡机器人系统的平衡控制中,为解决因所建立的数学模型不准确和存在未知干扰而影响控制性能的问题,设计了一种自适应模糊控制方法.首先,运用牛顿力学法建立了系统在斜坡上运动的数学模型.针对所建动态模型的非线性,提出采用单点模糊化、乘积推理机和中心平均解模糊化的方法构建了自适应模糊逻辑控制器,然后通过李雅普诺夫稳定性分析的方法,导出控制器的自适应律.在MA TLAB/Simulink中,对自适应模糊控制的两轮自平衡机器人的平衡情况进行了仿真,结果表明,提出的自适应模糊控制器可以实现系统平衡,并具有自适应能力和鲁棒性,为两轮机器人优化控制提供了依据.     

The study on the model reference adaptive control with proportional derivative action

This article presents a study on the novel method of model reference adaptive control (MRAC). As a new contribution, the derivative action is included into MRAC control to improve the controller performance and efficiency. The stability is analysed using a recent technique called immersion and invariance. The simulations of derived laws are presented based on nonlinear models.     

Design and stability analysis of an indirect variable structure model reference adaptive control

This paper presents the stability and robustness analysis of an indirect adaptive control based variable structure algorithm for uncertain plants with relative degree one. The indirect approach has been proposed as a way to get an easier design of the switching laws, compared to the direct relationship between the plant transfer function parameters and the physical parameters of the system. Here, a singular perturbation approach is used to establish the robustness of the controller in the presence of unmodelled dynamics and disturbances. It is shown that, for sufficiently small parasitics, the system remains stable with respect to some small residual set.     

Auto-tuning and adaptive control of sheet metal forming

This paper describes the design and implementation of automatic controller tuning and model reference adaptive control (MRAC) to improve part quality in stamping and extends previous work on a manually-tuned fixed-gain process controller. Automatic tuning is described with a discussion of implementation issues in the presence of plant disturbances. Design of a direct MRAC, whose controller gains are continuously adjusted to accommodate changes in process dynamics and disturbances, is investigated, including simulation-based robustness analysis of the adaptation law and a consideration of constrained estimation in the recursive least squares algorithm to address practical implementation issues. The performance of the MRAC process controller designed through simulation is experimentally validated. Good tracking of the reference process variable (i.e., punch force), and significant part quality improvement in the presence of disturbances, is achieved.     

Output feedback model reference adaptive control for multi-input–multi-output plants with state delay

Two new output feedback adaptive control schemes based on Model Reference Adaptive Control (MRAC) and adaptive laws for updating the controller parameters are developed for a class of linear multi-input–multi-output (MIMO) systems with state delay. An effective controller structure established on a new error equation parametrization is proposed to achieve tracking with the error tending to zero asymptotically. To achieve exact asymptotical tracking, we introduce, in the standard MRAC structure for plants without delay, a new additional adaptive feedforward control component as an output of a dynamical system driven by the reference signal. Adaptive laws are developed using the SPR-Lyapunov design approach and two assumptions regarding the prior knowledge of the high-frequency matrix . This work is the first asymptotic exact zero tracking results for this class of systems in the framework of the certainty equivalence approach.     

Design and stability analysis of a variable structure adaptive backstepping controller

This paper presents the design and stability analysis of a Variable Structure Adaptive Backstepping Controller (VS‐ABC) for linear plants with relative degree one, using only input/output measurements. Instead of traditional integral adaptive laws for estimating the plant parameters, switching laws are proposed to increase robustness to parametric uncertainties and disturbances, as well as to improve transient response. Moreover, the controller design is more intuitive when compared with the original adaptive backstepping controller, since the relay amplitudes are related to the plant nominal parameters and their respective uncertainties. Simplified algorithm versions are also presented, named Compact and Relay VS‐ABC, which reduce the practical implementation complexity, and encourage applications in industrial environments. Copyright © 2011 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society     

鲁棒变结构模型参考自适应控制器的分析与设计(Ⅱ)

对含未建模动态且建模部分相对阶大于 1(n >1) 的SISO定常线性系统提出了一种控制增益可切换的变结构模型参考自适应控制方案 .主要结果是 :得到了系统跟踪误差与辅助误差间关系的明确表达式 ,进而证明 ,对各辅助子系统 (均为相对阶为 1的子系统 ) ,只要按相对阶为 1时所提出的变结构律进行设计 ,使它们满足预先给定的性能指标 ,就可保证系统跟踪误差在预先给定的过渡过程时间内收敛到一个残集内 ;研究结果还表明 ,当n >1时 ,平均值滤波器对系统的影响相当于一个未建模动态对系统的影响     

Stability limit of human-in-the-loop model reference adaptive control architectures

Model reference adaptive control (MRAC) offers mathematical and design tools to effectively cope with many challenges of real-world control problems such as exogenous disturbances, system uncertainties and degraded modes of operations. On the other hand, when faced with human-in-the-loop settings, these controllers can lead to unstable system trajectories in certain applications. To establish an understanding of stability limitations of MRAC architectures in the presence of humans, here a mathematical framework is developed whereby an MRAC is designed in conjunction with a class of linear human models including human reaction delays. This framework is then used to reveal, through stability analysis tools, the stability limit of the MRAC–human closed-loop system and the range of model parameters respecting this limit. An illustrative numerical example of an adaptive flight control application with a Neal–Smith pilot model is presented to demonstrate the effectiveness of developed approaches.