显式模型预测控制的可达分区点定位算法

显式模型预测控制(explicit model predictive control,EMPC)避免了传统的模型预测控制中最为繁琐的反复在线优化过程.显式模型预测控制系统分为离线计算获得每个分区上控制律和在线查找控制律这两个不同阶段.离线计算阶段通过多参数二次规划(multi-parametric quadratic program,mp-QP)对系统状态空间进行凸划分,并计算得到系统在每个状态分区上的分段仿射(piece-wise affine,PWA)控制律;在线计算阶段通过查表确定系统当前状态所在的分区(即进行点定位运算)从而直接得到相应的控制律.研究工作在于如何快速确定系统当前状态所在的分区,属于在线计算过程范畴.文章在离线计算所得的状态分区数据基础上,根据可达域的思想,设计可达分区点定位算法使在线计算时搜索范围大幅减少,从而显著降低在线计算所需时间,提高EMPC系统的实时性.通过两个仿真实验将可达分区算法与直接查找法相互对比,证明可达分区算法的优势.作为一个应用例子,将文章显式模型预测控制可达分区点定位算法用于直流无刷电机显式模型预测控制,表明所用方法的有效性.     

任意切换线性系统的鲁棒镇定及其DC-DC变换器切换控制

针对具有任意切换序列的不确定线性切换系统,提出一种鲁棒镇定切换控制律设计方法.通过求解一组线性矩阵不等式,计算切换系统的共同鲁棒控制Lyapunov函数,进而构造一个双自由度的切换状态反馈控制律.应用共同鲁棒控制Lyapunov函数性质和切换控制理论,证明所提切换控制律的鲁棒渐近稳定性和逆最优性及共同鲁棒扇形裕度(0.5,∞).最后以DC-DC升压变换器切换控制为例,仿真验证文章方法的有效性和实用性.     

具有饱和输入和非严格反馈结构的切换非线性系统的自适应模糊控制

针对一类具有非光滑饱和输入和非严格反馈结构的任意切换规则下的非线性切换系统,给出了一种模糊减少计算量控制算法.通过构造公共Lyapunov函数,利用模糊系统对非严格反馈结构和未知不确定函数进行建模,采用辅助函数补偿饱和输入问题,基于逼近最优估计参数的界以减少在线自适应调节参数数目.该控制算法在任意切换规则下不仅可以调节输入饱和不确定性,还可以减少自适应调节参数.基于Lyapunov稳定性理论证明闭环系统的所有信号是有界的.数值仿真结果可以有效地验证控制器和自适应律设计算法的可行性.     

一类非线性系统的输出反馈控制及全局渐近稳定性研究

考虑不可测状态是非线性的非严格三角形非线性系统的全局渐近稳定性问题.提出了一种新的反馈控制设计方法,构造一个线性动态输出补偿器,并全局稳定所控制的非线性系统.     

基于动态面技术的随机非线性关联系统的输出反馈控制

针对一类参数不确定且含有未知关联项的随机非线性关联系统,提出了一种自适应输出反馈控制方案.该方案利用K滤波器估计不可量测的系统状态,将动态面技术与输出反馈控制相结合,避免了传统后推设计过程中对虚拟控制律反复求导出现的"复杂性膨胀"问题,设计的自适应动态面控制器可以确保闭环系统中的所有信号在概率意义下半全局一致终结有界,且跟踪误差收敛到一个小的残差集内.     

基于滑模方法的倒立摆台车系统的非线性控制

以倒立摆台车系统为研究对象，将系统状态分成两组，构造出一种双层滑动面，给出一种基于滑模控制的非线性控制律，并设计了控制器参数．然后采用Lyapunov方法，证明了各级滑动平面的稳定性，实现了台车在水平方向位置及摆角的渐近跟踪．     

基于动态BP网络误差修正的广义预测控制

针对建模误差对非线性系统预测控制鲁棒性的影响 ,提出了一种基于动态 BP网络的广义预测控制算法 .该算法运用动态 BP网络对模型预测误差进行在线补偿 ,以提高预测精度 .仿真结果证明了本文提出的广义预测控制算法对于非线性系统是有效的     

基于扰动补偿趋近律的非匹配离散广义准滑模控制

研究了非匹配不确定离散广义系统准滑模控制策略的综合问题.给出了具有前级状态向量的动态切换函数,使得系统能够在切换带内稳定.设计了两种带有扰动补偿的离散广义趋近律,消除了常规滑模控制策略中不确定项必须有界的限制,且不必满足匹配条件.给出了系统准滑动模态保持逐步穿越切换面的必要条件,减小了准滑动模态切换带的带宽.所设计的滑模控制器在有限时间内可达切换面,削弱了系统抖振,有效地改善了系统动态品质.最后,数值算例验证了该控制策略的可行性.     

中立型分数阶微分滑模系统的稳定性

文章主要讨论中立型分数阶微分滑模控制系统的稳定性问题.首先介绍分数阶积分、微分及广义Gronwall不等式的一些定义,然后构造切换面,给出控制律,最后通过李雅普诺夫定理来证明切换面存在,并得出系统的稳定性成立.     

基于线性状态反馈的非线性混合系统的实用稳定化

研究非线性混合系统的实用稳定化问题,其中该系统具有时变子系统和时变跳转函数.首先,通过状态跳转函数,确定系统一条严格递增的切换时间序列.然后在该序列中的每一段时间区间内,明确地构造出相应的线性状态反馈控制律,由此实现闭环系统的实用稳定.最后,给出一个数值例子说明文中方法的有效性.     

Characterization and computation of control invariant sets for linear impulsive control systems

Impulsive control systems are suitable to describe and control a venue of real-life problems, going from disease treatment to aerospace guidance. The main characteristic of such systems is that they evolve freely in-between impulsive actions, which makes it difficult to guarantee its permanence in a given state-space region. In this work, we develop a method for characterizing and computing approximations to the maximal control invariant sets for linear impulsive control systems, which can be explicitly used to formulate a set-based model predictive controller. We approach this task using a tractable and non-conservative characterization of the admissible state sets, namely the states whose free response remains within given constraints, emerging from a spectrahedron representation of such sets for systems with rational eigenvalues. The so-obtained impulsive control invariant set is then explicitly used as a terminal set of a predictive controller, which guarantees the feasibly asymptotic convergence to a target set containing the invariant set. Necessary conditions under which an arbitrary target set contains an impulsive control invariant set (and moreover, an impulsive control equilibrium set) are also provided, while the controller performance are tested by means of two simulation examples.     

A numerical approach to design control invariant sets for constrained nonlinear discrete-time systems with guaranteed optimality

A numerical approach to design control invariant sets for constrained nonlinear discrete-time systems with guaranteed optimality is proposed in this paper. The addressed approach is based on the fact that zonotopes are more flexible for representing sets than boxes in interval analysis. Then the solver of set inversion via interval analysis is extended to set inversion via zonotope geometry by introducing the novel idea of bisecting zonotopes. The main feature of the extended solver of set inversion is the bisection and the evolution of a zonotope rather than a box. Thus the shape of admissible domains for set inversion can be broadened from boxes to zonotopes and the wrapping effect can be reduced as well by using the zonotope evolution instead of the interval evolution. Combined with global optimization via interval analysis, the extended solver of set inversion via zonotope geometry is further applied to design control invariant sets for constrained nonlinear discrete-time systems in a numerical way. Finally, the numerical design of a control invariant set and its application to the terminal control of the dual-mode model predictive control are fulfilled on a benchmark Continuous-Stirred Tank Reactor example.     

Hypercubes are minimal controlled invariants for discrete-time linear systems with quantized scalar input

Quantized linear systems are a widely studied class of nonlinear dynamics resulting from the control of a linear system through finite inputs. The stabilization problem for these models shall be studied in terms of the so-called practical stability notion that essentially consists in confining the trajectories into sufficiently small neighborhoods of the equilibrium (ultimate boundedness).We study the problem of describing the smallest sets into which any feedback can ultimately confine the state, for a given linear single-input system with an assigned finite set of admissible input values (quantization). We show that the family of hypercubes in canonical controller form contains a controlled invariant set of minimal size. A comparison is presented which quantifies the improvement in tightness of the analysis technique based on hypercubes with respect to classical results using quadratic Lyapunov functions.     

Safety preserving control synthesis for sampled data systems

In sampled data systems the controller receives periodically sampled state feedback about the evolution of a continuous time plant, and must choose a constant control signal to apply between these updates; however, unlike purely discrete time models the evolution of the plant between updates is important. In this paper we describe an abstract algorithm for approximating the discriminating kernel (also known as the maximal robust control invariant set) for a sampled data system with continuous state space, and then use this operator to construct a switched, set-valued feedback control policy which ensures safety. We show that the approximation is conservative for sampled data systems. We then demonstrate that the key operations–the tensor products of two sets, invariance kernels, and a pair of projections–can be implemented in two formulations: one based on the Hamilton–Jacobi partial differential equation which can handle nonlinear dynamics but which scales poorly with state space dimension, and one based on ellipsoids which scales well with state space dimension but which is restricted to linear dynamics. Each version of the algorithm is demonstrated numerically on a simple example.     

时延混成系统的切换控制器合成

如何设计安全、可靠的信息物理融合系统是计算机科学和控制理论面临的一个重大挑战.时延现象在信息物理融合系统中普遍存在,时延对系统的稳定性、安全性和控制性能具有实质性影响.但是在已有时延系统验证和控制器合成的工作中往往忽略时延因素,这会导致在不考虑时延情况下能保证稳定和安全的系统在实际运行时因为时延原因而不再稳定和安全.因为时延使得系统的行为演化不仅与当前状态有关,还依赖于系统的历史状态,所以时延混成系统的验证和控制合成更加困难.本文研究信息物理融合系统在考虑时延情形下切换控制器合成问题,提出基于不变式生成技术的控制器合成方法.首先,利用谱分析和线性化技术将时延系统的微分不变式生成问题归结为有界时间的可达集计算问题;然后,提出基于抽象精化的算法计算时延系统有界时间可达集的上近似;最后,实现本文算法并使用实例验证该方法的有效性.     

Conley index condition for asymptotic stability

In this paper, we use Conley index theory to develop necessary conditions for stability of equilibrium and periodic solutions of nonlinear continuous-time systems. The Conley index is a topological generalization of the Morse theory which has been developed to analyze dynamical systems using topological methods. In particular, the Conley index of an invariant set with respect to a dynamical system is defined as the relative homology of an index pair for the invariant set. The Conley index can then be used to examine the structure of the system invariant set as well as the system dynamics within the invariant set, including system stability properties. Efficient numerical algorithms using homology theory have been developed in the literature to compute the Conley index and can be used to deduce the stability properties of nonlinear dynamical systems.     

On the possibility of globally stabilizing invariant sets

In this paper we study the possibility of globally stabilizinginvariant sets of autonomous continuous nonlinear systems bythe state (output) feedback control law. We show that the topologicalstructure of invariant sets can give rise to obstruction tothe existence of a continuous control law for global stabilizationof invariant sets.     

A semi-analytical direct optimal control solution for strongly excited and dissipative Hamiltonian systems

A semi-analytical direct optimal control solution for strongly excited and dissipative Hamiltonian systems is proposed based on the extended Hamiltonian principle, the Hamilton-Jacobi-Bellman (HJB) equation and its variational integral equation, and the finite time element approximation. The differential extended Hamiltonian equations for structural vibration systems are replaced by the variational integral equation, which can preserve intrinsic system structure. The optimal control law dependent on the value function is determined by the HJB equation so as to satisfy the overall optimality principle. The partial differential equation for the value function is converted into the integral equation with variational weighting. Then the successive solution of optimal control with system state is designed. The two variational integral equations are applied to sequential time elements and transformed into the algebraic equations by using the finite time element approximation. The direct optimal control on each time element is obtained respectively by solving the algebraic equations, which is unconstrained by the system state observed. The proposed control algorithm is applicable to linear and nonlinear systems with the quadratic performance index, and takes into account the effects of external excitations measured on control. Numerical examples are given to illustrate the optimal control effectiveness.     

Invariant polytopes of linear systems

Stable linear systems possess invariant sets which have hyperellipsoidalregions associated with their Lyapunov function. In real systems,however, state and control variables are often confined in boundedpolyhedral regions(polytopes) so that a set of linear inequalitieshas to be satisfied. In this paper, necessary and sufficientconditions for the existence of positively invariant polytopesfor both discrete-time and continuous-time linear systems aregiven in terms of their spectral properties.     

Convergence analysis of a non-negative matrix factorization algorithm based on Gibbs random field modeling

Non-negative matrix factorization (NMF) is a new approach to deal with the multivariate nonnegative data. Although the classic multiplicative update algorithm can solve the NMF problems, it fails to find sparse and localized object parts. Then a Gibbs random field (GRF) modeling based NMF algorithm, called the GRF-NMF algorithm, try to directly model the prior object structure of the components into the NMF problem. In this paper, the convergence of the GRF-NMF algorithm and its advantages are investigated. Based on a classic model, the equilibrium points are obtained. Some invariant sets are constructed to prepare for the analysis of the convergence of the GRF-NMF algorithm. Then using stability theory of the equilibrium point, the convergence of the algorithm is proved and the convergence conditions of the algorithm are obtained. We theoretically present the advantages of the GRF-NMF algorithm in the end.