On the largest feedback linearizable subsystem

A feedback invariant set of integers is associated with any nonlinear multivariable system which is linear with respect to the inputs: it is shown to be the set of controllability indices of the largest feedback linearizable subsystem, i.e. the largest subsystem which can be made locally linear and controllable by means of nonsingular feedback transformations.     

Adaptive output feedback control for a class of planar nonlinear systems

This paper is concerned with the problem of global adaptive stabilization by output feedback for a class of planar nonlinear systems with uncertain control coefficient and unknown growth rate. The control coefficient is not supposed to have known upper bound, and this relaxes the corresponding requirement in the existing literature (see e.g. 1 , 2 . First, by the universal control method, an observer is constructed based on the dynamic high‐gain K‐filters. Then, the control design procedure is developed to obtain the stabilizing controller and dynamic compensator for the uncertainties in the control coefficient. It is shown that the global stability of the closed‐loop system can be guaranteed by the appropriate choice of the design parameters. A simulation example is also provided to illustrate the correctness of the theoretical results. © 2009 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society.     

On the convergence of nonlinear optimal control using pseudospectral methods for feedback linearizable systems

We consider the optimal control of feedback linearizable dynamic systems subject to mixed state and control constraints. In contrast to the existing results, the optimal controller addressed in this paper is allowed to be discontinuous. This generalization requires a substantial modification to the existing convergence analysis in terms of both the framework as well as the notion of convergence around points of discontinuity. Although the nonlinear system is assumed to be feedback linearizable, the optimal control does not necessarily linearize the dynamics. Such problems frequently arise in astronautical applications where stringent performance requirements demand optimality over feedback linearizing controls. We prove that a sequence of solutions obtained using the Legendre pseudospectral method converges to the optimal solution of the continuous‐time problem under mild conditions. Published in 2007 by John Wiley & Sons, Ltd.     

Robust control with uncertainty estimation for feedback linearizable systems: application to control of distillation columns

The goal of this paper is to describe a linearizing feedback adaptive control structure which leads to a high quality regulation of the output error in the presence of uncertainties and external disturbances. The controller consists of three elements: a nominal input–output linearizing compensator, a state observer and an uncertainty estimator, which provides the adaptive part of the control structure. In this way, the feedback controller, based on the disturbance observer, compensates for external disturbances and plant uncertainties. The effectiveness of the controller is demonstrated on a distillation column via numerical simulations. ©     

反馈线性的非线性系统的分步输出变结构控制

针对一类存在参数不确定性的反馈线性的非线性动态系统,通过构造两个滑模流形,即误差跟踪的线性函数和中间控制变量与其实际值之间的误差,给出了输出跟踪控制律．并设计一个变结构控制律使闭环系统的轨迹渐近趋于滑模区,对于所有滑模区上的轨迹,跟踪误差趋于零．     

Optimal exponential feedback stabilization of planar systems

This paper solves the problem of finding an optimal feedback control ensuring the maximal rate of convergence of system solutions to the origin for a general class of planar control systems including switched, bilinear systems and ones described by differential inclusions, etc. The prescribed control set is assumed to be compact but not necessarily convex. The developed approach is based on finding the minimal Lyapunov exponent of the system with an open loop control which provides an upper bound for the optimal convergence rate of the closed loop system. Then an optimal feedback controller is constructed for which the obtained bound is attained.     

Dynamic anti-windup scheme for feedback linearizable nonlinear control systems with saturating inputs

This paper proposes a dynamic compensation scheme for input-constrained feedback linearizable nonlinear systems to cope with the windup phenomenon. Given a dynamic feedback linearizing controller designed without considering its input constraint, an additional dynamic compensator is proposed to account for the constraint. This dynamic anti-windup is based on the minimization of a reasonable performance index. The proposed strategy is a nonlinear extended version of [Park, J.-K., & Choi, C.-H. (1995). Dynamic compensation method for multivariable control systems with saturating actuators. IEEE Transactions on Automatic Control, 40(9), 1635–1640] with simplified derivation of an optimization solution under relaxed assumptions. The parameter matrices and structure of the solution are explicitly decided by mathematical optimization for infinite horizon without tuning of design parameters unlike previous schemes. During input saturation, the role of the anti-windup scheme with the proposed dynamic feedback compensator is to maintain the controller states to be exactly the same as those without input saturation. The local asymptotic stability and the total stability of the resulting systems are proved. The usefulness of the proposed design method is illustrated by comparative simulations for a constrained control system.     

Output-feedback finite-time stabilization of disturbed feedback linearizable nonlinear systems

A novel methodology for designing multivariable High-Order Sliding-Mode (HOSM) controllers for disturbed feedback linearizable nonlinear systems is introduced. It provides for the finite-time stabilization of the origin of the state-space by using output feedback. Only the additional assumptions of algebraic strong observability and smooth enough matched disturbances are required. The control problem is solved in two consecutive steps: firstly, designing an observer based on the measured output and, secondly, designing of a full-state controller computed from a new virtual output with vector relative degree. The introduced notion of algebraic strong observability allows recovering the state of the system using the measured output and its derivatives. By estimating the required derivatives through the HOSM differentiator, a finite-time convergent observer is constructed.     

Output feedback hierarchical control for nonlinear systems

In this paper, we address the problem of hierarchical control for nonlinear systems and design two dynamic output feedback hierarchical control laws in a semiglobal sense and in a global sense, respectively. With the controllers applied to a class of nonlinear systems, some transient and steady properties of the system output trajectories can be satisfied simultaneously. Furthermore, the corresponding result in the global sense for linear systems is naturally derived. Finally, the effectiveness of our approach is illustrated by a single‐link robot arm system. Copyright © 2017 John Wiley & Sons, Ltd.     

Robust adaptive control of linearizable nonlinear single input systems with guaranteed error bounds

In this paper, a nonlinear robust adaptive control algorithm is designed and analyzed for a class of single-input nonlinear systems with unknown nonlinearities. The controller employs a single layer neural network to estimate the unknown plant nonlinearities on-line. The proposed controller is continuous and guarantees closed-loop semi-global stability and convergence of the tracking error to a small residual set. Furthermore, it handles the situation where the estimated plant becomes uncontrollable without any restrictive assumptions. In contrast to previous work on the same subject, the size of the residual tracking error can be specified a priori and is guaranteed by choosing certain design parameters. A procedure for choosing these parameters is presented. An example is used to demonstrate the performance and properties of the proposed scheme.     

Output feedback control of nonlinear systems subject to sensor data losses

In this work, we focus on output feedback control of nonlinear systems subject to sensor data losses. We initially construct an output feedback controller based on a combination of a Lyapunov-based controller with a high-gain observer. We then study the stability and robustness properties of the closed-loop system in the presence of sensor data losses for both the continuous and sampled-data systems. We state a set of sufficient conditions under which the closed-loop system is guaranteed to be practically stable. The theoretical results are demonstrated using a chemical process example.     

Adaptive control of feedback linearizable systems: a modelling error compensation approach

An adaptive output feedback controller for single input feedback linearizable systems is proposed. The output derivatives are estimated with a state high-gain observer, and the matched uncertainties are handled using a modelling error compensation method. Compared with existing adaptive methods, this approach avoids overparameterizations yielding an (n+1)-order compensator, where n is the system dimension. Semiglobal stability is proven with the aid of existing results on the stability of controlled nonlinear systems with high-gain state observation. Copyright © 1999 John Wiley & Sons, Ltd.     

On state representations of time-varying nonlinear systems

This work considers a nonlinear time-varying system described by a state representation, with input u and state x. A given set of functions v, which is not necessarily the original input u of the system, is the (new) input candidate. The main result provides necessary and sufficient conditions for the existence of a local classical state space representation with input v. These conditions rely on integrability tests that are based on a derived flag. As a byproduct, one obtains a sufficient condition of differential flatness of nonlinear systems.     

A two-tier control architecture for nonlinear process systems with continuous/asynchronous feedback

In this work, we introduce a two-tier control architecture for nonlinear process systems with both continuous and asynchronous sensing and actuation. This class of systems arises naturally in the context of process control systems based on hybrid communication networks (i.e. point-to-point wired links integrated with networked wired or wireless communication) and utilising multiple heterogeneous measurements (e.g. temperature and concentration). Assuming that there exists a lower-tier control system which relies on point-to-point communication and continuous measurements to stabilise the closed-loop system, we propose to use Lyapunov-based model predictive control to design an upper-tier networked control system to profit from both the continuous and the asynchronous measurements as well as from additional networked control actuators. The proposed two-tier control system architecture preserves the stability properties of the lower-tier controller while improving the closed-loop performance. The theoretical results are demonstrated using two different chemical process examples.     

Robust optimal control during feedback disruption for nonlinear systems controlled by an observer-based output feedback controller

In this paper, a robust optimal control problem during feedback disruption is considered for a class of nonlinear systems which have been controlled by an observer-based output feedback controller. It is shown that during feedback disruption, there exists an optimal control input which keeps both system states and observer errors within a specified bound for the longest time. Then, it is shown that such an optimal control input can be practically implemented by using a bang-bang control input in terms of control performance. One numerical and one practical examples are given for clear illustration.     

Stabilization of the planar vertical take-off and landing using nonlinear feedback control

This article presents a new control strategy for the well-known problem of the planar vertical take-off and landing. The total thrust is computed using a nonlinear feedback compensation so that the altitude reaches the desired altitude. The horizontal position x is then controlled by choosing the orientation angle as a smooth saturation function of x and . A proof of convergence is presented using a Lyapunov approach. The proposed control strategy is successfully tested in numerical simulations.     

The spring paradigm in tracking control of simple mechanical systems

An intrinsic formulation of geometric proportional–derivative tracking control for fully actuated mechanical systems is developed. The region of stability is determined directly from the size of the system’s injectivity radius and, for a restricted set of control problems, the system’s locus of cut points about a desired reference point. Exponential stability is obtained under certain boundedness conditions. For controlled motion along a geodesic, the proffered scheme yields a particularly simple and elegant manifestation of the underlying use of the mass–spring–damper paradigm in the control design methodology.     

切换非线性系统的输出反馈周期事件触发控制

本文针对一类在任意切换信号作用下的切换非线性系统, 研究了其输出反馈周期事件触发控制问题. 所考 虑的非线性系统采用非严格反馈形式且含有未知时变控制系数. 在本文中, 仅利用采样时刻的系统输出. 为了估计 系统的不可量测的状态, 基于采样的系统输出构造了降维状态观测器. 为了减少通信资源的利用, 提出了一种新的 输出反馈周期事件触发策略, 该策略包含仅利用事件触发时刻的信息构造的输出反馈事件触发控制器以及仅在采 样时刻间歇性监测的离散事件触发机制. 通过选取可容许的采样周期及合适的公共Lyapunov函数, 证明了闭环系统 在任意切换下全局渐近稳定. 最后, 通过将本文中所给出的控制方案应用到数值算例中验证了其有效性.