基于反馈线性化的MIMO非最小相位系统指数镇定

针对仿射多输入多输出非线性非最小相位系统,提出了一种新的镇定方案.用反馈线性化解耦系统输入输出关系,通过高增益状态反馈镇定系统外部动态,用模型预测控制镇定内部动态,所设计控制器能保证闭环系统的指数稳定性.仿真结果表明了所提出方法的有效性和优越性.     

基于反馈线性化的MIMO非最小相位系统指数镇定

针对仿射多输入多输出非线性非最小相位系统,提出了一种新的镇定方案.用反馈线性化解耦系统输入输出关系,通过高增益状态反馈镇定系统外部动态,用模型预测控制镇定内部动态,所设计控制器能保证闭环系统的指数稳定性.仿真结果表明了所提出方法的有效性和优越性.

     

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.     

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.     

Lur'e多非线性系统的镇定与L2-增益控制的MI方法

考虑Lur'e多非线性系统的镇定与L2-增益控制问题.对Lur'e多非线性系统表示 控制对象,设计状态反馈和输出反馈控制器使闭环系统分别是绝对稳定和L2增益有限的.基 于矩阵不等式(MI)方法给出了镇定与L2-增益控制问题的可解条件,并讨论了控制器的设计 方法.     

带两控制器刚体飞行器的姿态镇定

已知带两控制器的刚体飞行器系统不能被连续的纯状态反馈局部渐近镇定.有效的解 决方法包括时变反馈镇定方法和非连续反馈镇定方法.现有的时变反馈镇定方法设计均较为复 杂.已有的光滑时变反馈方法是非指数收敛的.本文通过引入辅助变量以及采用反馈线性化技术 设计出光滑时变的控制器.该方法设计简单且保证闭环系统状态是指数收敛的.仿真结果证明了 本文方法的有效性.     

离散输入受限系统的增益调度事件触发和自触发控制

针对离散输入受限系统,分别设计静态和动态的增益调度事件触发和自触发控制算法.首先设计一种基于离散参量Lyapunov方程的静态增益调度事件触发控制算法,该算法通过事件触发机制更新控制增益,使得在增大闭环系统收敛速率的同时节约通讯资源.为了避免对采样状态和测量误差的连续监测,设计了相应的静态增益调度自触发控制算法;同时,...     

线性区间离散时滞系统的区域镇定

针对线性离散时滞系统的区域镇定问题, 基于非奇异状态变换技术提出了区间不确定性系统区域可镇定的充分条件, 保证闭环系统的所有极点均位于给定的圆盘区域内. 所给条件可简化为LMI描述形式, 利用LMI工具求解非常方便. 所给实例表明了该方法用于判断线性区间离散时滞系统的区域可镇定性与设计区域镇定控制器的可行性.     

网络控制系统的时延相关状态反馈控制器设计

研究了具有时延、丢包和数据包时序错乱的网络控制系统镇定问题.为了有效提高系统的控制性能,本文根据网络控制系统的特点提出一种时延相关状态反馈控制方法,并将闭环网络控制系统建模为离散时间切换模型.在此基础上,通过构造依赖于参数的Lyapunov函数给出了闭环网络控制系统的稳定条件和镇定控制器设计方法.仿真结果和实验结果表明所提方法的有效性和可用性.     

以幂次趋近的离散变结构重复控制

本文提出一种离散变结构重复控制器设计方法,在趋近律中“嵌入”扰动抑制措施,构造理想切换动态,并据此导出重复控制器.为了进行控制器参数整定和刻画闭环系统的收敛性能,文中推导出准滑模带、单调收敛层和绝对收敛层边界的表达式.设计的离散变结构重复控制器能够完全抑制周期性扰动,控制器设计方法也适用于常值扰动下的定位控制.数值仿真及实验结果验证了所提出控制方案的有效性.     

Truncated predictor feedback for linear systems with long time-varying input delays

In this paper we study the problem of stabilizing a linear system with a single long time-varying delay in the input. Under the assumption that the open-loop system is stabilizable and not exponentially unstable, a finite dimensional static time-varying linear state feedback controller is obtained by truncating the predictor based controller and by adopting the parametric Lyapunov equation based controller design approach. As long as the time-varying delay is exactly known and bounded, an explicit condition is provided to guarantee the stability of the closed-loop system. It is also shown that the proposed controller achieves semi-global stabilization of the system if its actuator is subject to either magnitude saturation or energy constraints. Numerical examples show the effectiveness of the proposed approach.     

Pseudo-predictor feedback stabilization of linear systems with time-varying input delays

This paper is concerned with stabilization of (time-varying) linear systems with a single time-varying input delay by using the predictor based delay compensation approach. Differently from the traditional predictor feedback which uses the open-loop system dynamics to predict the future state and will result in an infinite dimensional controller, we propose in this paper a pseudo-predictor feedback (PPF) approach which uses the (artificial) closed-loop system dynamics to predict the future state and the resulting controller is finite dimensional and is thus easy to implement. Necessary and sufficient conditions guaranteeing the stability of the closed-loop system under the PPF are obtained in terms of the stability of a class of integral delay operators (systems). Moreover, it is shown that the PPF can compensate arbitrarily large yet bounded input delays provided the open-loop (time-varying linear) system is only polynomially unstable and the feedback gain is well designed. Comparison of the proposed PPF approach with the existing results is well explored. Numerical examples demonstrate the effectiveness of the proposed approaches.     

Stabilization of linear systems with distributed input delay and input saturation

This paper is concerned with stabilization of a linear system with distributed input delay and input saturation. Both constant and time-varying delays are considered. In the case that the input delay is constant, under the stabilizability assumption on an auxiliary system, it is shown that the system can be stabilized by state feedback for an arbitrarily large delay as long as the open-loop system is not exponentially unstable. In the case that the input delay is time-varying, but bounded, it is shown that the system can be stabilized by state feedback if the non-asymptotically stable poles of the open-loop system are all located at the origin. In both cases, stabilizing controllers are explicitly constructed by utilizing the parametric Lyapunov equation based low gain design approach we recently developed. It is also shown that in the presence of actuator saturation and under the same assumptions on the system, these controllers achieve semi-global stabilization. Some discussions on the assumptions we impose on the system are given. A numerical example illustrates the effectiveness of the proposed stabilization approach.     

Truncated predictor feedback control for exponentially unstable linear systems with time-varying input delay

The stabilization of exponentially unstable linear systems with time-varying input delay is considered in this paper. We extend the truncated predictor feedback (TPF) design method, which was recently developed for systems with all poles on the closed left-half plane, to be applicable to exponentially unstable linear systems. Assuming that the time-varying delay is known and bounded, the design approach of a time-varying state feedback controller is developed based on the solution of a parametric Lyapunov equation. An explicit condition is derived for which the stability of the closed-loop system with the proposed controller is guaranteed. It is shown that, for the stability of the closed-loop system, the maximum allowable time-delay in the input is inversely proportional to the sum of the unstable poles in the plant. The effectiveness of the proposed method is demonstrated through numerical examples.     

Uniting bounded control and MPC for stabilization of constrained linear systems

In this work, a hybrid control scheme, uniting bounded control with model predictive control (MPC), is proposed for the stabilization of linear time-invariant systems with input constraints. The scheme is predicated upon the idea of switching between a model predictive controller, that minimizes a given performance objective subject to constraints, and a bounded controller, for which the region of constrained closed-loop stability is explicitly characterized. Switching laws, implemented by a logic-based supervisor that constantly monitors the plant, are derived to orchestrate the transition between the two controllers in a way that safeguards against any possible instability or infeasibility under MPC, reconciles the stability and optimality properties of both controllers, and guarantees asymptotic closed-loop stability for all initial conditions within the stability region of the bounded controller. The hybrid control scheme is shown to provide, irrespective of the chosen MPC formulation, a safety net for the practical implementation of MPC, for open-loop unstable plants, by providing a priori knowledge, through off-line computations, of a large set of initial conditions for which closed-loop stability is guaranteed. The implementation of the proposed approach is illustrated, through numerical simulations, for an exponentially unstable linear system.     

Exponential stabilization of a class of unstable bilinear systems

Considers the control design of bilinear systems with multiplicative control inputs. Previous control designs for such systems normally assume that the open-loop bilinear system is (neutrally) stable. In this paper, a nonlinear control design is proposed for open-loop unstable bilinear systems. The new control stabilizes the bilinear system globally and exponentially if a sufficient stability condition, which can be checked by off-line computer simulations in advance of the control, is satisfied     

Quadratically saturated regulator for constrained linear systems

The problem of stabilization and null-controllability of open-loop unstable discrete-time multi-input systems with constraints on the inputs and the controls is addressed in this paper. First necessary and sufficient conditions for solvability of the problem are derived. They guarantee the existence of a linear controller leaving the state constraint set for the closed-loop system positively invariant. An optimal control law is computed, and the admissible set of initial conditions is given such that along trajectories of the closed-loop system the state and input constraints are satisfied. Then the domain of feasible initial conditions is enlarged using a saturating control if such is feasible     

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.     

Maximal controllability of input constrained unstable systems by the addition of implicit constraints

The null controllable set of a system is the largest set of states that can be controlled to the origin. Control systems that have a region of attraction equal to the null controllable set are said to be maximally controllable closed-loop systems. In the case of open-loop unstable plants with amplitude constrained control it is well known that the null controllable set does not cover the entire state-space. Further the combination of input constraints and unstable system dynamics results in a set of state constraints which we call implicit constraints. It is shown that the simple inclusion of implicit constraints in a controller formulation results in a controller that achieves maximal controllability for a class of open-loop unstable systems.     

不确定线性系统的可达集估计

本文针对线性不确定系统,研究了系统状态可达集估计问题.在已知参考输入,未知扰动有界的条件下,提出了一种新的可达集估计方法,并把所提方法推广到系统不稳定的情况,分别估计出不稳定系统的闭环可达集和开环可达集.通过分析动态系统的李雅普诺夫函数,将求取系统可达集的问题转化为线性矩阵不等式优化问题,并将可达集范围用椭球集形式表述.最后分别通过数值仿真分析,验证了所提出方法对线性系统可达集估计的有效性.