On pole assignment in multi-input controllable linear systems

It is shown that controllability of an open-loop system is equivalent to the possibility of assigning an arbitrary set of poles to the transfer matrix of the closed-loop system, formed by means of suitable linear feedback of the state. As an application of this result, it is shown that an open-loop system can be stabilized by linear feedback if and only if the unstable modes of its system matrix are controllable. A dual of this criterion is shown to be equivalent to the existence of an observer of Luenberger's type for asymptotic state identification.     

Nonlinear control of feedforward systems with bounded signals

The stabilization problem for a class of nonlinear feedforward systems is solved using bounded control. It is shown that when the lower subsystem of the cascade is input-to-state stable and the upper subsystem not exponentially unstable, global asymptotic stability can be achieved via a simple static feedback having bounded amplitude that requires knowledge of the "upper" part of the state only. This is made possible by invoking the bounded real lemma and a generalization of the small gain theorem. Thus, stabilization is achieved with typical saturation functions, saturations of constant sign, or quantized control. Moreover, the problem of asymptotic stabilization of a stable linear system with bounded outputs is solved by means of dynamic feedback. Finally, a new class of stabilizing control laws for a chain of integrators with input saturation is proposed. Some robustness issues are also addressed and the theory is illustrated with examples on the stabilization of physical systems.     

Stabilization of exponentially unstable discrete-time linear systems by truncated predictor feedback

Predictor state feedback solves the problem of stabilizing a discrete-time linear system with input delay by predicting the future state with the solution of the state equation and thus rendering the closed-loop system free of delay. The solution of the state equation contains a term that is the convolution of the past control input with the state transition matrix. Thus, the implementation of the resulting predictor state feedback law involves iterative calculation of the control signal. A truncated predictor feedback law results when the convolution term in the state prediction is discarded. When the feedback gain is constructed from the solution of a certain parameterized Lyapunov equation, the truncated predictor feedback law has been shown to achieve asymptotic stabilization of a system that is not exponentially unstable in the presence of an arbitrarily large delay by tuning the value of the parameter small enough. In this paper, we extend this result to exponentially unstable systems. Stability analysis leads to a bound on the delay and a range of the values of the parameter for which the closed-loop system is asymptotically stable as long as the delay is within the bound. The corresponding output feedback result is also derived.     

一类线性时变系统的输出反馈控制

基于线性时不变系统能控能观标准型变换及非线性系统高增益观测器方法,本文研究了一类线性时变系统 的输出反馈控制问题. 通过引入时变的状态变量坐标变换,分别设计了线性时变系统的状态反馈控制器、状态观测器以及基于 状态观测器的输出反馈控制器. 进一步地,本文分别证明了观测器动态误差是渐近收敛于零的,而状态反馈控制器以及输出反馈控制器可以 保证闭环系统的渐近稳定性.     

具有数据丢包的非线性奇异脉冲系统量化控制

考虑网络传输中存在的数据丢包和信号量化问题, 研究了基于数据丢包的非线性奇异脉冲系统设量化反馈控制器的设计方法. 首先给出一般非线性奇异脉冲系统的数学描述, 并在此基础上建立相应的具有丢包的闭环量化反馈控制系统的数学模型. 其次, 根据李雅普诺夫稳定性理论, 给出了奇异脉冲系统的渐近稳定的充分条件以及量化反馈控制器的设计方法. 应用本设计方法, 可以选择满足代数矩阵不等式条件的量化反馈增益, 实现系统渐近稳定. 最后通过对Chua混沌系统仿真, 表明利用本文设计的量化控制器能够保证闭环非线性奇异脉冲系统在具有数据丢包的情况下渐近稳定.     

Stability of discrete-time systems with quantized input and state measurements

This note focuses on linear discrete-time systems controlled using a quantized input computed from quantized measurements. Nominally stabilizing, but otherwise arbitrary, state feedback gains could result in limit cycling or nonzero equilibrium points. Although a single quantizer is a sector nonlinearity, the presence of a quantizer at each state measurement channel makes traditional absolute stability theory not applicable in a direct way. A global asymptotic stability condition is obtained by means of a result which allows us to apply discrete positive real theory to systems with a sector nonlinearity which is multiplicatively perturbed by a bounded function of the state. The stability result is readily applicable by evaluating the location of the polar plot of a system transfer function relative to a vertical line whose abcissa depends on the one-norm of the feedback gain. A graphical method is also described that can be used to determine the equilibrium points of the closed-loop system for any given feedback gain.     

Extracting state information from a quantized output record

We consider the problem of manipulating the input to a discrete-time state space linear system with the goal of obtaining information at each time about the system's current state from a record of past quantized measurements of the system's output. We find that if the system is not excessively unstable, there exist feedback control strategies that allow one to make an asymtotically perfect determination of the current stage based on the output records that result. Even if the system is too unstable to apply such strategies, there are feedback control laws that make the system's output record more informative about the system's state evolution than one might expect. In deriving these control laws, we regard quantized measurements of real numbers more as partial observations than as strict approximations, and employ techniques from information theory and the theory of Markov chains with countable state spaces.     

A sliding sector approach to quantized feedback variable structure control

This paper is concerned with the quantized feedback quadratic stabilization problem for linear time-invariant systems. Sliding sector based quantized state feedback variable structure control schemes are established. The main benefit of the sliding sector technique is that it can avoid chattering caused by the utilization of variable structure control strategy. With the proposed discrete on-line adjustment of the quantization parameter, it is shown that the proposed sliding sector based sliding mode controllers can tackle state quantization and guarantee quadratic stability of the closed-loop system. Simulation results are given to verify the effectiveness of the proposed method.     

Stabilization of linear systems with limited information

We show that the coarsest, or least dense, quantizer that quadratically stabilizes a single input linear discrete time invariant system is logarithmic, and can be computed by solving a special linear quadratic regulator problem. We provide a closed form for the optimal logarithmic base exclusively in terms of the unstable eigenvalues of the system. We show how to design quantized state-feedback controllers, and quantized state estimators. This leads to the design of hybrid output feedback controllers. The theory is then extended to sampling and quantization of continuous time linear systems sampled at constant time intervals. We generalize the definition of density of quantization to the density of sampling and quantization in a natural way, and search for the coarsest sampling and quantization scheme that ensures stability. Finally, by relaxing the definition of quadratic stability, we show how to construct logarithmic quantizers with only finite number of quantization levels and still achieve practical stability of the closed-loop system     

On Asymptotic Stabilizability of Linear Systems With Delayed Input

This paper examines the asymptotic stabilizability of linear systems with delayed input. By explicit construction of stabilizing feedback laws, it is shown that a stabilizable and detectable linear system with an arbitrarily large delay in the input can be asymptotically stabilized by either linear state or output feedback as long as the open-loop system is not exponentially unstable (i.e., all the open-loop poles are on the closed left-half plane). A simple example shows that such results would not be true if the open-loop system is exponentially unstable. It is further shown that such systems, when subject to actuator saturation, are semiglobally asymptotically stabilizable by linear state or output feedback.     

Observer-based control of uncertain systems with non-linear uncertainties

Global asymptotic stabilization of nominally linear uncertain systems is considered where uncertain elements in the plant are modelled as cone bounded non-linearities. At first, a linear time-invariant state feedback law ensuring global asymptotic closed-loop stability is obtained. The algorithm which calculates such a feedback law is simple and straightforward. It does not involve repeated solutions of a parameter-dependent algebraic Riccati or any such non-linear equations. Any state feedback law thus developed can then be implemented via an observer specially designed to preserve the global asymptotic stability of the closed-loop system.     

一类不确定组合大系统的鲁棒分散控制

研究一类互联项与孤立了系统均含范数有界不确定性的非线性组合大系统的状态反馈鲁棒分散镇定问题,设计出线性状态反馈鲁棒分散控制器,使闭环系统在其平衡点处按指数渐近稳定,且鲁棒控制器具有全息结构,最后给出了一个数值例子,验证了所给结果的有效性。     

Observer-based feedback stabilization of linear systems with event-triggered sampling and dynamic quantization

We consider the problem of output feedback stabilization in linear systems when the measured outputs and control inputs are subject to event-triggered sampling and dynamic quantization. A new sampling algorithm is proposed for outputs which does not lead to accumulation of sampling times and results in asymptotic stabilization of the system. The approach for output sampling is based on defining an event function that compares the difference between the current output and the most recently transmitted output sample not only with the current value of the output, but also takes into account a certain number of previously transmitted output samples. This allows us to reconstruct the state using an observer with sample-and-hold measurements. The estimated states are used to generate a control input, which is subjected to a different event-triggered sampling routine; hence the sampling times of inputs and outputs are asynchronous. Using Lyapunov-based approach, we prove the asymptotic stabilization of the closed-loop system and show that there exists a minimum inter-sampling time for control inputs and for outputs. To show that these sampling routines are robust with respect to transmission errors, only the quantized (in space) values of outputs and inputs are transmitted to the controller and the plant, respectively. A dynamic quantizer is adopted for this purpose, and an algorithm is proposed to update the range and the centre of the quantizer that results in an asymptotically stable closed-loop system.     

Global stabilization of the Kuramoto–Sivashinsky equation via distributed output feedback control

This work addresses the problem of global exponential stabilization of the Kuramoto–Sivashinsky equation (KSE) subject to periodic boundary conditions via distributed static output feedback control. Under the assumption that the number of measurements is equal to the total number of unstable and critically stable eigenvalues of the KSE and a necessary and sufficient stability condition is satisfied, linear static output feedback controllers are designed that globally exponentially stabilize the zero solution of the KSE. The controllers are designed on the basis of finite-dimensional approximations of the KSE which are obtained through Galerkin's method. The theoretical results are confirmed by computer simulations of the closed-loop system.     

Stability of sampled-data piecewise affine systems: A time-delay approach

This paper addresses the stability analysis of sampled-data piecewise-affine (PWA) systems consisting of a continuous-time plant in feedback connection with a discrete-time emulation of a continuous-time state feedback controller. The sampled-data system is first considered as a continuous-time system with a variable time delay. Conditions under which the trajectories of the sampled-data closed-loop system will converge to an attracting invariant set are then presented. It is also shown that when the sampling period converges to zero, these conditions coincide with sufficient conditions for non-fragility of the stabilizing continuous-time PWA state feedback controller. The results are successfully applied to a helicopter example.     

Non-fragile state feedback H-infinity control for discrete-time systems with quantized signals

This paper presents a study on the problem of non-fragile state feedback H-infinity controller design for linear discrete-time systems with quantized signals. The quantizers considered here are dynamic and time-varying. With the consideration of controller gain variations and quantized signals at the same time, a new non-fragile H-infinity control strategy is proposed with updating quantizer＇s parameters, such that the quantized closed-loop system is asymptotically stable and with a prescribed H-infinity performance bound. An example is presented to illustrate the effectiveness of the proposed control strategy.     

Stabilization of exponentially unstable linear systems withsaturating actuators

We study the problem of stabilizing exponentially unstable linear systems with saturating actuators. The study begins with planar systems with both poles exponentially unstable. For such a system, we show that the boundary of the domain of attraction under a saturated stabilizing linear state feedback is the unique stable limit cycle of its time-reversed system. A saturated linear state feedback is designed that results in a closed-loop system having a domain of attraction that is arbitrarily close to the null controllable region. This design is then utilized to construct state feedback laws for higher order systems with two exponentially unstable poles     

A new optimal multirate control of linear periodic andtime-invariant systems

The optimal multirate design of linear, continuous-time, periodic and time-invariant systems is considered. It is based on solving the continuous linear quadratic regulation (LQR) problem with the control being constrained to a certain piecewise constant feedback. Necessary and sufficient conditions for the asymptotic stability of the resulting closed-loop system are given. An explicit multirate feedback law that requires the solution of an algebraic discrete Riccati equation is presented. Such control is simple and can be easily implemented by digital computers. When applied to linear time-invariant systems, multirate optimal feedback optimal control provides a satisfactory response even if the state is sampled relatively slowly. Compared to the classical single-rate sampled-data feedback in which the state is always sampled at the same rate, the multirate system can provide a better response with a considerable reduction in the optimal cost. In general, the multirate scheme offers more flexibility in choosing the sampling rates     

Feedback stabilization of discrete time singularly perturbed systems with communication constraints

In this paper, the quantized feedback problem for a class of discrete time singularly perturbed systems with information constraints is considered. First, a proper coder‐decoder pair is presented so that the transmission errors tend to zero exponentially under information constraints. Next, linear matrix inequalities are constructed such that the resulting closed‐loop system is input‐to‐state stable (ISS) with respect to the transmission error, and the asymptotic stability of the closed‐loop system also can be guaranteed. The theoretical results have shown that the presented method is simple and easy to operate. Moreover, the upper bound of the small perturbed parameter of the stable system can be explicitly estimated using this feasible method. Finally, two numerical examples are given to illustrate the effectiveness of the proposed method.