Chanying Li's research while affiliated with Chinese Academy of Sciences and other places
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Publications (12)
Feedback systems with communication channels encounter unique challenges. Communication channels mandate signal sampling and quantization, and introduce errors, data losses, and delays. Consequently, transmitted signals must be estimated. The signal estimation introduces a dynamic system that interacts with communication channels and affects the st...
An important task in control theory is to study the limitations of feedback principle in dealing with uncertainties. Although some progresses have been achieved in this area, they are all focused on some special classes of linearly parameterized nonlinear uncertain systems. In this paper, we will present a dynamic inequality for the output process...
In this technical note, we will investigate the maximum capability and limitations of the feedback mechanism in globally stabilizing a basic class of discrete-time nonlinearly parameterized dynamical systems with multiple unknown parameters. Both “possibility” and “impossibility” theorems together with a fairly complete characterization on the capa...
State observability and observer designs are investi- gated for linear-time-invariant systems in continuous time when the outputs are measured only at a set of irregular sampling time sequences. The problem is primarily motivated by systems with limited sensor information in which sensor switching generates ir- regular sampling sequences. State obs...
This paper introduces several algorithms for signal estimation using binary-valued output sensing. The main idea is derived from the empirical measure approach for quantized identification, which has been shown to be convergent and asymptotically efficient when the unknown parameters are constants. Signal estimation under binary-valued observations...
It is fairly well known that there are fundamental differences between adaptive control of continuous-time and discrete-time nonlinear systems. In fact, even for the seemingly simple single-input single-output control system yt+1=θ1f(yt)+ut+wt+1 with a scalar unknown parameter θ1 and noise disturbance {wt}, and with a known function f(⋅) having pos...
This paper is concerned with state observer design of systems with binary-valued output measurements. First, observability of sampled systems is obtained under noise-free observations and arbitrary sampling times. It demonstrates that if the original system is observable, the sampled system is always observable whenever sampling density is larger t...
Feedback is a key concept in control systems. A fundamental theoretical problem has been to understand the maximum capability of feedback in controlling uncertain dynamical systems. This needs not only to answer what the feedback can do, but also to answer, the more difficult and basic question, what feedback cannot do. An impossibility theorem on...
It is fairly well known that there are fundamental differences between adaptive control of continuous-time and discrete-time nonlinear systems. In fact, even for the seemingly simple SISO control system y t+1 = θ 1 f (y t) + u t + w t+1 with a scalar unknown parameter θ 1 and noise disturbance {w t }, and with a known function f (·) having possible...
We consider the capability of feedback for a class of polynomial nonlinear systems with both unknown parameters and bounded noises. In the single parameter case, Li, C. and Xie, L. (2006) demonstrated that the necessary and sufficient condition for the existence of a feedback stabilizer is that the nonlinear growth rate of the system dynamics is le...
We consider adaptive control of discrete-time nonlinear systems with a single unknown parameter in this paper. We demonstrate that the necessary and sufficient condition for the existence of a feedback stabilizer that is robust to bounded noise is that the nonlinear growth rate of the system dynamics is less than 4. This result further confirms the...
In this paper, we will investigate the maximum capability of adaptive feedback in stabilizing a basic class of discrete-time nonlinear systems with both multiple unknown parameters and bounded noises. We will present a complete proof of the polynomial criterion for feedback capability as stated in "Robust stability of discrete-time adaptive nonline...
Citations
... 关于上述结论, 人们自然会问: 为什么反馈机制能力会有这样的临界值? 其背后的基本原理是什 么? 简单来讲, 这样的临界值是由关于未知参数 "最优" 估计误差的 "下降趋势" 与关于未知参数的灵 敏度函数的 "最大" 可能 "上升趋势" 共同作用的结果, 最终可转化为对某个多项式实根性质的判断. 此外, 从数学证明中也可以看出不可能性定理成立的基本原理: 首先对任何反馈控制规律, 利用贝叶 斯嵌入 (Bayes embedding) 方法, 可以将系统输出的二阶条件矩用最优预报误差的条件方差来表达, 而 后者又可以利用动态系统的条件 Cramer-Rao 型的不等式给出下界估计, 这一估计可以用 Fisher 信息 矩阵和灵敏度函数来表达, 据此通过进一步的非线性分析, 最终可以将闭环系统稳定性与多项式判据 联系起来 [88] . ...
... A decentralized adaptive synchronization problem for a particular discrete-time stochastic dynamic network with multiple agents is investigated with the following three motivations: One comes from the recent research, initiated by Guo (see [14] for a brief survey), on the capability and limitation of the feedback mechanism (e.g. [13], [21], [22], [29], [30], [34], [41], [42], [45]); one comes from the decades of studies on traditional adaptive control (e.g. [3], [8], [12], [19]) on a single plant; one comes from the hot studies since the 1980s on complex systems (e.g. ...
... State-of-the-Art: Previous research on this subject considered the estimation of systems parameters when the input sequence is known [17], [18] and when the input signal is synchronously sampled that is when the ratio between the sampling sequence period and the signal period is a rational number [19]. Several other references have addressed a wide class of similar problems in the context of system identification [20]- [27]. ...
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... Moreover, we refer to the papers (Li et al., 2009; Rodríguez-Seda, 2019) for discretisation of observable continuous time invariant systems with irregular sampling patterns. In addition, it is proved that, in some cases, observable continuous model given in Rodríguez-Seda (2019) is observable under aperiodic sampling sequence. ...
... When the input gain is unknown, our technique analysis requires essential improvement. In this regard, [2] and [4] solved it for ARMA models and [9] for nonlinear systems with two unknown parameters. But for more general settings, there still remains a lot of problems which need further research. ...
... Notably, though, discrete-time uncertain systems with bounded noises are stabilizable as well, provided their nonlinearities meet the polynomial criterion (see [11] and [12]). This means, different from the stochastic framework where the LS-STR converges to the minimal variance controller, the LS-STR in the deterministic framework performs no longer "optimal". ...
... The parameter update laws of Eq. (21) and Eq. (22) ensure that, for j = 1, 2, ..., M , ...
... One interesting study in this direction was extension of Shannon's sampling theorem on signals under periodic sampling (Nyquist frequency) to a new sampling theorem for systems under irregular sampling. The results carry similar types of bounds, but have very different meanings [19]. 5. Applications [1,20,21]: During our joint work of several decades, we have never stopped in investigating potential usage of new methods in engineering and medical systems, and pushing for technology transfer. ...
... Analogous phenomena arise in adaptive control of various discrete-time nonlinear systems. We refer the readers to [11], [13], [14], [15], [20], [21], [22]. ...
