Backstepping controller design for a class of stochastic nonlinear systems with Markovian switching

A more general class of stochastic nonlinear systems with irreducible homogenous Markovian switching are considered in this paper. As preliminaries, the stability criteria and the existence theorem of strong solutions are first presented by using the inequality of mathematic expectation of a Lyapunov function. The state-feedback controller is designed by regarding Markovian switching as constant such that the closed-loop system has a unique solution, and the equilibrium is asymptotically stable in probability in the large. The output-feedback controller is designed based on a quadratic-plus-quartic-form Lyapunov function such that the closed-loop system has a unique solution with the equilibrium being asymptotically stable in probability in the large in the unbiased case and has a unique bounded-in-probability solution in the biased case.     

An Internal-Model Controller for a Class of Single-Input Single-Output Nonlinear Systems: Stability and Robustness

A controller design procedure for a class of nonlinear systems is presented. The structure of the control system corresponds to the so-called internal-model controller that, for linear systems, has exhibited good performance and stability robustness with respect to disturbances and to uncertainty in the plant parameters. The systems involved are single-input single-output and fully linearizable by coordinates transformation and state feedback. It is shown that the plant output converges to a constant reference, even under the presence of constant disturbances and parameter uncertainties, provided the closed-loop system has an asymptotically stable equilibrium point placed anywhere. This scheme does not need an explicit design of a nonlinear observer; instead, it uses the state of a plant model. A conservative stability robustness margin is estimated by applying standard results of Lyapunov theory.     

On the region of attraction of nonlinear quadratic systems

Quadratic systems play an important role in the modelling of a wide class of nonlinear processes (electrical, robotic, biological, etc.). For such systems, it is of mandatory importance not only to determine whether the origin of the state space is locally asymptotically stable but also to ensure that the operative range is included into the convergence region of the equilibrium. Based on this observation, this paper considers the following problem: given the zero equilibrium point of a nonlinear quadratic system, assumed to be locally asymptotically stable, and a certain polytope in the state space containing the origin, determine whether this polytope belongs to the region of attraction of the equilibrium. The proposed algorithm requires the solution of a suitable feasibility problem involving linear matrix inequalities constraints. An example illustrates the effectiveness of the proposed procedure by exploiting a population interaction model of three species.     

Almost global stabilization of fully-actuated rigid bodies

This paper addresses the problem of stabilizing a fully-actuated rigid body. The problem is formulated by considering the natural configuration space for rigid bodies, the Special Euclidean group SE(3). The proposed solution consists of a landmark-based controller for force and torque actuation that guarantees almost global asymptotic stability of the desired equilibrium point. As such the equilibrium point is asymptotically stable and only a nowhere dense set of measure zero lies outside its region of attraction. The controller uses velocity measurements and the position coordinates of a collection of landmarks fixed in the environment. As an additional feature, the control law is designed so as to verify prescribed bounds on the actuation.     

三类不动点与一类随机动力系统的稳定性

不动点理论已被成功地应用于随机动力系统零解稳定性的研究,但Krasnoselskii不动点方法使用的较少.本文在采用Banach和Schauder不动点方法研究的基础上进一步采用Krasnoselskii不动点方法研究了一类随机动力系统零解的指数均方稳定性,得出了使得该系统零解指数均方稳定的充分条件.通过实例与现有文献结论的比较表明,相比于Banach和Schauder等不动点方法,Krasnoselskii不动点方法的应用更加灵活和简便.本文的结论在一定程度上改进和拓展了相关文献的结果,完善了不动点理论在研究随机动力系统零解稳定性上的应用.     

Absolute stability and integral control

Absolute stability results of both circle criterion and Popov type are derived for finite-dimensional linear plants with non-linearity in the feedback loop. The linear plant contains an integrator (and so is not asymptotically stable). The (possibly time-varying) non-linearity satisfies a particular sector condition which allows for cases with zero lower gain (such as saturation and deadzone). The conjunction of stable, but not asymptotically stable, linear plants and non-linearities with possibly zero lower gain is a distinguishing feature of the paper. The absolute stability results are invoked in proving convergence and stability properties of low-gain integral feedback control for tracking of constant reference signals in the context of exponentially stable linear systems subject to input and output non-linearities.     

SECOND‐ORDER NONSINGULAR TERMINAL SLIDING MODE DECOMPOSED CONTROL OF UNCERTAIN MULTIVARIABLE SYSTEMS

This paper proposes a second‐order nonsingular terminal sliding mode decomposed control method for multivariable linear systems with internal parameter uncertainties and external disturbances. First, the systems are converted into the block controllable form, consisting of an input‐output subsystem and a stable internal dynamic subsystem. A special second‐order non‐singular terminal sliding mode is proposed for the input‐output subsystem. The control law is designed to drive the states of the input‐output subsystem to converge to the equilibrium point asymptotically. Then the states of the stable zero‐dynamics of the system converge to the equilibrium point asymptotically. The method proposed in the paper has advantages for higher‐dimensional multivariable systems, in the sense that it simplifies the design and makes it possible to realize a robust decomposed control. Meanwhile, because of the adoption of the second‐order sliding mode, the control signal is continuous. Simulation results are presented to validate the design.     

Stability analysis and bang-bang sliding control of a class of single-input bilinear systems

Introduces a bang-bang sliding control of a class of single-input bilinear systems. The sliding function is chosen via the well-known pole-assignment method for linear time-invariant systems. Importantly, the bang-bang sliding control generates a reaching-and-sliding region and a stable-sliding region, each expressed by a set of linear inequalities. Both regions comprise the equilibrium point, shown to be asymptotically stable. However, the stability analysis is processed under the limitation that the system state should be initially located in the reaching-and-sliding region. Two numeric examples are used for demonstration.     

基于稳定性分析的一类欠驱动系统的滑模控制器设计

从稳定分析的角度提出了一种欠驱动系统的新型滑模控制方法．该方法将各个子系统的一个变量进行组合定义成一个中间变量，然后从这个中间变量出发构造滑模函数，通过求取总的控制量保证中间变量在有限时间内收敛到平衡点；进一步利用LaSalle不变性原理证明该收敛域内只有一个平衡点且是渐近稳定的．仿真实验进一步验证了该结论．     

Stability analysis of nonlinear quadratic systems via polyhedral Lyapunov functions

Quadratic systems play an important role in the modeling of a wide class of nonlinear processes (electrical, robotic, biological, etc.). For such systems it is mandatory not only to determine whether the origin of the state space is locally asymptotically stable, but also to ensure that the operative range is included into the convergence region of the equilibrium. Based on this observation, this paper considers the following problem: given the zero equilibrium point of a nonlinear quadratic system, assumed to be locally asymptotically stable, and a certain polytope in the state space containing the origin, determine whether this polytope belongs to the domain of attraction of the equilibrium. The proposed approach is based on polyhedral Lyapunov functions, rather than on the classical quadratic Lyapunov functions. An example shows that our methodology may return less conservative results than those obtainable with previous approaches.     

Global adaptive output-feedback control of nonlinear systems. I.Linear parameterization

The problem of designing global adaptive output-feedback tracking controls for single-input single-output nonlinear systems which are linear with respect to the input and an unknown constant parameter vector is addressed. A class of systems which can be globally controlled by adaptive observer-based output-feedback compensators is identified by geometric coordinate-free conditions. The nonlinearities depend on the output only: growth conditions are not required. Each system in the class admits observers with linear error dynamics and is minimum phase, i.e., it has linear asymptotically stable zero dynamics. When the parameters are known, new sufficient conditions for global output-feedback tracking control are obtained as a special case. For linear systems the result recovers a well-known fundamental adaptive result. Three examples are discussed     

一类非线性微分代数系统的L2-增益分析及状态反馈∞控制

分析了一类非线性微分代数系统的L₂增益, 并讨论了一类状态反馈H_∞控制问题. 在一定条件下给出了控制器的设计, 并保证了闭环指数为 1且零解渐近稳定.     

Geometric optimal control techniques to optimize the production of chemical reactors using temperature control

The dynamics of mass reaction kinetics chemical systems is modeled by the Feinberg-Horn-Jackson graph and under the ”zero deficiency assumption”, the behavior of the solutions is well known and splits into two cases: if the system is not weakly reversible there exists no equilibrium, nor periodic solution and if the network is weakly reversible in each stoichiometric subspace there exists only one equilibrium point and this point is asymptotically stable. By varying the temperature, one gets a single input control system and in this article we study the problem of maximizing the production of one species during the batch time. Our aim is to present the geometric techniques and results based on the Pontryagin maximum principle to compute the closed loop optimal solution. The complexity of the problem is illustrated by using two test bed examples: a sequence of two irreversible reactions and the McKeithan scheme.     

基于鲁棒滑模观测器的两关节柔性机械手控制

柔性机械手系统为非最小相位系统, 当控制有界时, 该特性阻碍其端点位移渐近跟踪期望轨迹. 本文首先重新定义柔性机械手系统的输出, 通过输入输出线性化, 将系统分解为输入输出子系统和零动态子系统; 然后提出一种用于观测柔性模态导数的鲁棒滑模观测器, 使状态估计达到预期的指标, 解决了柔性模态导数难以获得的问题; 设计积分滑模控制策略, 使输入输出子系统在有限时间收敛到零; 选择适当的控制器参数, 使零动态子系统在 平衡点附近渐近稳定, 从而保证整个系统的渐近稳定. 本文提出的方法设计过程简单, 易于实现. 仿真结果证明了设计的有效性.     

Density Functions for Navigation-Function-Based Systems

In this paper, we present a scheme for constructing density functions for systems that are almost globally asymptotically stable (i.e., systems for which all trajectories converge to an equilibrium except for a set of measure zero) using navigation functions (NFs). Although recently-proven converse theorems guarantee the existence of density functions for such systems, such results are only existential and the construction of a density function for almost globally asymptotically stable systems remains a challenging task. We show that for a specific class of dynamical systems that are defined based on an NF, a density function can be easily derived from the system's underlying NF.     

一类线性切换系统的鲁棒状态反馈镇定

考虑一类标称系统存在共同Lyapunov函数的切换系统的鲁棒镇定问题.在不确定性不满足匹配条件下,设计出鲁棒状态反馈控制器,并在给定的切换策略下,确保闭环系统在其平衡点处渐近稳定.仿真结果表明所设计控制器是有效的.     

A stability property

In this note we obtain a stability property, not for a point of equilibrium, but for a certain family of asymptotically stable equilibria of a dynamical system with an input. We show that this property depends not only on the initial condition, but also on the (time) derivative of the input function. We suggest possible applications of this result to some control problems.     

Asymptotic regulation of minimum phase nonlinear systems usingoutput feedback

We consider a single-input/single-output (SISO) nonlinear system which has a well-defined normal form with asymptotically stable zero dynamics. We allow the system's equation to depend on constant uncertain parameters and disturbance inputs which do not change the relative degree. Our goal is to design an output feedback controller which regulates the output to a constant reference. The integral of the regulation error is augmented to the system equation, and a robust output feedback controller is designed to bring the state of the closed-loop system to a positively invariant set. Once inside this set, the trajectories approach a unique equilibrium point at which the regulation error is zero. We give regional as well as semiglobal results     

A note on multivariable generalized predictive control

This note presents a stability result for the multivariable version of the Generalized Predictive Control algorithm (Shah et al. 1989). In particular, closed-loop stability is obtained for any open-loop asymptotically stable plant by a proper selection of the future output horizon and of the control weighting matrix. The control law contains an integral action, thus guaranteeing regulation with zero steady-state error for constant exogeneous signals.     

Nonlinear regulation of a Lorenz system by feedback linearization techniques

In this paper we analyze some dynamical properties of a chaotic Lorenz system driven by a control input. These properties are the input-state and the input-output feedback linearizability, the stability of the zero dynamics, and the phase minimality of the system. We show that the controlled Lorenz system is feedback equivalent to a controllable linear system. We also show that the zero dynamics are asymptotically stable when the output is an arbitrary state. These facts allow designing control laws such that the closed-loop system has asymptotically stable equilibrium points with dynamic behavior free from chaotic transients. The controllers are robust in the sense that the closed-loop system is stable and non chaotic around a nominal set of parameter values. The results also show that the proposed controllers give better responses compared to linear algorithms obtained from standard linearization techniques, and exhibit a good performance even when the control input is bounded.