高频增益符号未知时的变结构模型参考自适应控制

解决了对象相对阶大于1、高频增益符号未知时的变结构模型参考自适应控制(VS-MRAC)问题．提出了一种基于监控函数的控制信号切换律, 证明只需要对首个辅助误差构造监控函数, 就可决定控制信号的切换时间;进而, 在监控函数的管理下, 控制信号经至多有限次切换后将停止切换, 闭环系统所有信号一致有界, 跟踪误差将收敛到一个残集内, 且该残集可通过减小某些设计参数而变得任意小．特别地, 我们证明, 若系统的某些初始条件为零, 则至多只需要一次切换．     

鲁棒低增益变结构模型参考自适应控制

就对象含未建模动态且其建模部分相对阶大于1时的变结构模型参考自适应控制(VS-MRAC)系统,提出了一种鲁棒低增益变结构控制方案,特点是系统变结构律在低增益状态下仍可保证所有辅助误差均在有限时间内收敛到零,从而提高了系统跟踪精度.此外,还研究了平均值滤波器对系统稳定性的影响.     

低增益变结构模型参考自适应控制器设计

就对象相对阶大于1时的变结构模型参考自适应控制（VS－MRAC）系统提出了一种低增益变结构控制方案,主要特点是：1）系统变结构律在低增益状态下仍可保证所有辅助误差在有限时间内收敛到零,从而提高了系统跟踪精度;2）进一步研究了平均值滤波器对系统稳定性的影响。     

降低鲁棒变结构模型参考自适应稳态控制增益的模糊实时分层方法

提出一种模糊实时分层方法来降低鲁棒变结构模型参考自适应稳态控制增益。利用模糊理论将一些定性经验与已提出的鲁棒变结构模型参考自适应控制相结合,可以在一定程度上克服稳态控制增益高的缺点。仿真结果表明,采用模糊实时分层方法后,稳态控制增益有所降低。     

具有未知高频增益的模型参考自适应控制的性能提高

在高频增益kp 未知的假设下, 提出了一种修改的模型参考自适应控制器. 证明了这种修改的模型参考自适应控制方案具有稳定性和鲁棒性 ;同时通过选取的控制律, 其瞬态性能也明显提高.     

具有理想跟踪特性的鲁棒变结构模型参考自适应控制

针对相对阶为1的定常线性被控对象,提出了一种控制增益可切换的鲁棒变结构模型参考自适应控制方案.该方案在对象参数及高频增益符号均未知的情形下,可确保跟踪误差满足预先给定的过渡过程性能指标,即超调量、过渡过程时间和稳态误差.     

含有不灵敏区非线性系统的增益调度自适应变结构控制

针对具有控制输入不灵敏区及有界不确定性的非线性系统,采用增益调度变结构控制策略,研究其镇定问题.利用增益调度策略和自适应参数估计方法,在同时存在参数、结构及干扰的不确定性和未知控制输入不灵敏区的情形下,提出了新的增益调度自适应变结构镇定控制律设计方法,既节省了控制能量,又消除了控制信号的颤振.所提出的控制律可以保证闭环输出为一致终结有界,并且算法比较简单,便于实现.用数字仿真方法验证了所得控制律设计方法的有效性.     

具有理想跟踪特性的多变量变结构模型参考自适应控制

考虑一个广义相对阶为1的多变量系统之变结构模型参考自适应控制器(VS-MRAC)设计问题,提出了一种切换控制方案,解决了现有多变量VS-MRAC和多变量模型参考自适应控制(MRAC)中两个尚未解决的问题:1)使系统跟踪误差的每个分量均满足预先给定的性能指标;2)无须假定对象高频增益矩阵满足通常的正定性条件.     

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     

基于未知高频增益的非线性系统自适应迭代学习控制

针对一类单输入单输出不确定非线性重复跟踪系统，提出一种基于完全未知高频反馈增益的自适应迭代学习控制，与普通迭代学习控制需要复习增益稳定性前提条不同，自适应迭代学习控制通过不断修改Nussbaum形式的高频学习增益达到收敛，经证明当迭代次数i→∞时，重复跟踪误差可一致收敛到任意小界δ。仿真结果表明了该控制方法的有效性。     

On the convergence of a model reference adaptive control algorithm with unknown high frequency gain

A model reference adaptive control algorithm is shown not to be exponentially convergent when the high frequency gain of the plant is unknown. The implication is that such an algorithm will be lacking in some way in robustness.     

A model reference robust control with unknown high‐frequency gain sign

In this paper, we discuss the model reference robust control (MRRC) for plants with unknown high‐frequency gain sign. Based on an appropriate monitoring function, a switching scheme is proposed so that after a finite number of switching, for plants with relative degree one, the tracking error converges to zero exponentially, while for plants with relative degree greater than one, it converges exponentially to a residual set that can be made arbitrarily small by properly choosing some design parameters. Copyright © 2009 John Wiley & Sons, Ltd.     

A variable structure model reference robust control without a prior knowledge of high frequency gain sign

The design of a variable structure model reference robust control without a prior knowledge of high frequency gain sign is presented. Based on an appropriate monitoring function, a switching scheme for some control signals is proposed. It is shown that after a finite number of switching, the tracking error converges to zero at least exponentially for plants with relative degree one or converges exponentially to a small residual set for plants with higher relative degree, and the input disturbance can be completely rejected without affecting the tracking performance.     

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.     

Universal output feedback adaptive control with uncertain nonlinearity and unknown high‐frequency gain sign: A new design

In this paper, we propose a new universal output feedback adaptive controller to globally (or semiglobally) stabilize nonlinear output feedback systems, whose nonlinearities are bounded either by known functions with unknown parameters or by completely unknown functions. In addition, no a priori knowledge of the sign of high‐frequency gain is required. The new design focuses on properly arranging the control gains step by step in the filter backstepping design. Instead of Lyapunov‐based argument, an inductive contradiction argument is employed in the proof of stability, which is not common in literature.     

Exponential convergence of a model reference adaptive controller for plants with known high frequency gain

A model reference adaptive controller proposed by Morse is studied. It is shown to be exponentially convergent when the high frequency gain is known and when the reference inputs satisfy a persistence of excitation assumption, which allows the inputs to be other than a linear combination of sinusoids.     

Direct adaptive control using an adaptive reference model

Direct model reference adaptive control is considered when the plant-model matching conditions are violated due to large changes in the plant or incorrect knowledge of the plant's mathematical structure. Because of the mismatch, the plant can no longer track the original reference model, but may be able to track a modified reference model that still provides satisfactory performance. The proposed approach uses a time-varying ‘adaptive’ reference model that reflects the achievable performance of the changed plant. The approach consists of direct adaptation of state feedback gains for state tracking and simultaneous estimation of the plant-model mismatch. The reference model adapts to the changed plant, and is redesigned if the estimated plant-model mismatch exceeds a bound determined via robust stability and/or performance criteria. The resulting controller offers asymptotic state tracking in the presence of plant-model mismatch as well as matched parameter deviations.     

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.     

Output feedback control for MIMO non-linear systems with unknown sign of the high frequency gain matrix

The paper presents a new output feedback adaptive control scheme for multi-input and multi-output (MIMO) non-linear systems whose non-linear terms depend only on the output variable based on the backstepping approach with vector form. The assumption on the prior knowledge of the high frequency gain matrix in existing results is reduced and the new required condition for the high frequency gain matrix can be easily checked for certain plants so that the proposed method is widely applicable. This control scheme guarantees the global stability of the closed-loop systems and makes the tracking error be arbitrary small. A simulation example is included to demonstrate the proposed algorithm.