Further results on limitations of sampled-data feedback

To control continuous-time uncertain dynamical systems with sampled data-feedback is prevalent today,but the sampling rate is usually not allowed to be arbitrarily fast due to various physical and/or computational constrains.In this paper,the authors examine the limitations of sampled-data feedback control for a class of uncertain systems in continuous-time,with sampling rate not necessary fast enough and with the unknown system structure confined to a set of functions with both linear and nonlinear growth.The limitations of the sampled-data feedback control for the uncertain systems are established quantitatively,which extends the existing related results in the literature.     

State feedback stabilization for a class of nonlinear time-delay systems via dynamic linear controllers

The dynamic linear state feedback control problem is addressed for a class of nonlinear systems subject to time-delay. First, using the dynamic change of coordinates, the problem of global state feedback stabilization is solved for a class of time-delay systems under a type of nonhomogeneous growth conditions. With the aid of an appropriate Lyapunov-Krasovskii functional and the adaptive strategy used in coordinates, the closed-loop system can be globally asymptotically stabilized by the dynamic linear state feedback controller. The growth condition in perturbations are more general than that in the existing results. The correctness of the theoretical results are illustrated with an academic simulation example.     

Disturbance Attenuation State-Feedback Control for Uncertain Interconnected Systems

This paper studies the problem of robust H∞ control design for a class of uncertain interconnected systems via state feedback. This class of systems are described by a state space model, which contains unknown nonlinear interaction and time-varying norm-bounded parametric uncertainties in state equation. Using the Riccati-equation-based approach we design state feedback control laws, which guarantee the decentralized stability with disturbance attenuation for the interconnected uncertain systems. A simple example of an interconnected uncertain linear system is presented to illustrate the results.     

Adaptive Stabilization for a Class of Feedforward Systems with Zero-Dynamics

This paper investigates adaptive state feedback stabilization for a class of feedforward nonlinear systems with zero-dynamics,unknown linear growth rate and control coefficient.For design convenience,the state transformation is first introduced and the new system is obtained.Then,the estimation law is constructed for the unknown control coefficient,and the state feedback controller is proposed with a gain updated on-hne.By appropriate choice of the estimation law for the control coefficient and the dynamic gain,the states of the closed-loop system are globally bounded,and the state of the original system converges to zero.Finally,a simulation example is given to illustrate the correctness of the theoretical results.     

New Results on H∞ Control for Nonlinear Conformable Fractional Order Systems

This paper deals with H_∞ control problem for nonlinear conformable fractional order systems. The authors first derive new sufficient condition for exponential stability of nonlinear conformable fractional order systems based on Lyapunov-like function method for conformable fractional order systems and linear matrix inequalities(LMIs) approach. Then, by introducing a new concepts of H_∞ control problem for nonlinear conformable fractional order systems, the authors study H_∞ performance analysis and H_∞ state feedback controller design problems for the considered systems. In terms of LMIs, a sufficient condition is proposed to ensure the nonlinear conformable fractional order systems are not only exponentially stable, but also satisfy H_∞ performance γ. An explicit expression for state feedback controllers is also designed to make the closed-loop system is exponentially stable with H_∞performance γ. Finally, numerical examples are given to illustrate the validity and effectiveness of the proposed results.     

Model algorithm control using neural networks for input delayed nonlinear control system

The performance of the model algorithm control method is partially based on the accuracy of the system’s model. It is difficult to obtain a good model of a nonlinear system, especially when the nonlinearity is high. Neural networks have the ability to "learn"the characteristics of a system through nonlinear mapping to represent nonlinear functions as well as their inverse functions. This paper presents a model algorithm control method using neural networks for nonlinear time delay systems. Two neural networks are used in the control scheme. One neural network is trained as the model of the nonlinear time delay system, and the other one produces the control inputs. The neural networks are combined with the model algorithm control method to control the nonlinear time delay systems. Three examples are used to illustrate the proposed control method. The simulation results show that the proposed control method has a good control performance for nonlinear time delay systems.     

Novel robust control framework for morphing aircraft

This paper develops a robust control methodology for a class of morphing aircraft,which is called innovative control effector(ICE) aircraft.For the ICE morphing aircraft,the distributed arrays of hundreds of shape-change devices are employed to stabilize and maneuver the air vehicle.Because the morphing aircraft have the inherent uncertainty and varying dynamics due to the alteration of their configuration,a desired control performance can not be satisfied with a fixed feedback controller.Therefore,a novel control framework including an adaptive flight control law and an adaptive allocation algorithm is proposed.Firstly,a state feedback adaptive control law is designed to guarantee closed-loop stability and state tracking in the presence of uncertain dynamics caused by the wing shape change due to different flight missions.In the control allocation,many distributed arrays are managed in an optimal way to improve the robustness of the system.The scheme is used to an uncertain morphing aircraft model,and the simulation results demonstrate their performance.     

Adaptive NN stabilization for stochastic systems with discrete and distributed time-varying delays

A new adaptive neural network(NN) output-feedback stabilization controller is investigated for a class of uncertain stochastic nonlinear strict-feedback systems with discrete and distributed time-varying delays and unknown nonlinear functions in both drift and diffusion terms.First,an extensional stability notion and the related criterion are introduced.Then,a nonlinear observer to estimate the unmeasurable states is designed,and a systematic backstepping procedure to design an adaptive NN output-feedback controller is proposed such that the closed-loop system is stable in probability.The effectiveness of the proposed control scheme is demonstrated via a numerical example.     

Delay-dependent passive control of linear systems with nonlinear perturbation

The problem of delay-dependent passive control of a class of linear systems with nonlinear perturbation and time-varying delay in states is studied. The main idea aims at designing a state-feedback controller such that for a time-varying delay in states, the linear system with nonlinear perturbation remains robustly stable and passive. In the system, the delay is time-varying. And the derivation of delay has the maximum and minimum value. The time-varying nonlinear perturbation is allowed to be norm-bounded. Using the effective linear matrix inequality methodology, the sufficient condition is primarily obtained for the system to have robust stability and passivity. Subsequently the existent condition of a state feedback controller is given, and the explicit expression of the controller is obtained by means of the solution of linear matrix inequalities （LMIs）. In the end, a numerical example is given to demonstrate the validity and applicability of the proposed approach.     

Flight control for a flexible air-breathing hypersonic vehicle based on quasi-continuous high-order sliding mode

The focus of this paper is on control design and simulation for the longitudinal model of a flexible air-breathing hypersonic vehicle(FAHV).The model of interest includes flexibility effects and intricate couplings between the engine dynamics and flight dynamics.To overcome the analytical intractability of this model,a nominal control-oriented model is constructed for the purpose of feedback control design in the first place.Secondly,the multi-input multi-output(MIMO) quasi-continuous high-order sliding mode(HOSM) controller is proposed to track step changes in velocity and altitude,which is based on full state feedback.The simulation results are presented to verify the effectiveness of the proposed control strategy.     

OUTPUT FEEDBACK CONTROL FOR MIMO NONLINEAR SYSTEMS WITH EXOGENOUS SIGNALS

The paper addresses the global output tracking of a class of multi-input multi-output （MIMO） nonlinear systems affected by disturbances, which are generated by a known exosystem. An adaptive controller is designed based on the proposed observer and the backstepping approach to asymptotically track arbitrary reference signal and to guarantee the boundedness of all the signals in the closed loop system. Finally, the numerical simulation results illustrate the effectiveness of the ProPosed scheme.     

不确定非线性系统自适应滑模跟踪控制及应用

针对一类非匹配不确定非线性系统,设计了一种高阶鲁棒自适应反推滑模变结构控制方法。在控制器设计中,考虑存在系统建模误差和外界未知干扰,借鉴动态面思想降低控制器复杂性,引入双曲正切函数和抖振衰减因子降低控制输入抖振,设计系统建模误差自适应律增强控制器鲁棒性,并将系统的稳定性证明简化为判断一个n阶对称矩阵的正定性问题。将设计的反推滑模控制器用于F-8飞机纵向机动控制并进行仿真,实现了飞机对指定轨迹的稳定跟踪。     

Combined indirect and direct method for adaptive fuzzy output feedback control of nonlinear system

A novel control method for a general class of nonlinear systems using fuzzy logic systems (FLSs) is presertted. Indirect and direct methods are combined to design the adaptive fuzzy output feedback controller and a high-gain observer is used to estimate the derivatives of the system output. The closed-loop system is proven to be semiglobally uniformly ultimately bounded. In addition, it is shown that if the approximation accuracy of the fuzzy logic system is high enough and the observer gain is chosen sufficiently large, an arbitrarily small tracking error can be achieved. Simulation results verify the effectiveness of the newly designed scheme and the theoretical discussion.     

一类严格反馈时滞系统的自适应输出反馈控制

针对一类单输入单输出的严格反馈时滞系统研究跟踪控制问题。该控制系统包含不确定项、输出约束、未知死区特性和未知时间延迟。首先,设计一个状态观测器来估计无法测量的系统状态;其次,利用径向基函数(radial basis function,RBF)神经网络去逼近未知的系统内部动态;同时,利用障碍李雅普诺夫(Lyapunov)函数确保输出约束及Lyapunov-Krasovskii方法消除时滞项对系统的影响;最后,基于Lyapunov稳定性理论,构造一个鲁棒自适应神经网络输出反馈控制器,并且克服了过参数问题。结果显示,设计的神经网络输出反馈控制器可以保证闭环系统中的所有信号都是半全局最终一致有界的,跟踪误差能收敛到零值小的领域内。文中通过两个例子进一步验证了提出方法的有效性。     

Backstepping tracking control for nonlinear time-delay systems

1. INTRODUCTION The presence of time delay has a significant effect on system performance and destroys the stability of closed-loop system[1]. Therefore, the study on time-delay systems has important practical significance. Recen- tly,considerable progress has been made in this field[1~10]. According to the dependency of the designed contr-oller depends on the time delay, the control approa-ches for time-delay systems can be classified into two categories: delay-dependent[2~3,10] and dela…     

Multi-range controller design for highly nonlinear systems with application to unmanned aerial vehicles

A new procedure for a design of multi-range controllers for use with highly nonlinear systems is developed. The procedure involves obtaining the describing function models of the nonlinear plant by software followed by designing a controller at nominal conditions. Then, the controller parameters are optimized to yield a satisfactory closed-loop response at all operating regimes. Finally, the performance and stability of the closed-loop system comprised of the designed controller and the nonlinear plant are verified. The procedure and the associated software are applied to a nonlinear control problem of the sort encountered in aerospace, and the results are compared with two other approaches.     

基于扩张状态观测器的标量混沌信号同步系统

将扩张状态观测器与控制器的backstepping设计相结合,给出了一种标量混沌信号同步控制方案。该方案将产生参考混沌信号的驱动系统看作具有规范形或类规范形的系统,构造具有严格反馈形式的非线性系统作为响应系统,利用扩张状态观测器估计驱动系统的状态和未知结构信息,采用backstepping方法设计出控制器。应用该同步控制方案,可以在驱动系统结构和参数未知及不要求混沌参考信号连续可导的前提下,实现构造响应系统的输出渐近同步于任意标量混沌信号。理论分析与计算机仿真结果均证实了控制方案的有效性。     

一种新型的非线性随机大系统自适应镇定方法

研究了一类具有严反馈形式并含有Wiener噪声扰动的非线性随机大系统,其互联项满足线性增长约束。利用微分几何的理论,应用Backstepping算法,基于Lyapunov稳定性理论,选择了适合这类组合非线性系统的状态观测器,设计了自适应输出反馈分散控制律和自适应律,使得闭环,互联的非线性随机大系统实现了概率意义下的全局稳定,仿真结果表明了控制算法的有效性。     

基于观测器的一类不确定非线性系统自适应输出反馈控制

针对一类不确定非线性系统,基于非线性状态观测器采用回馈递推(Backstepping)设计方法提出了一种鲁棒自适应L2增益控制方案。该控制方案首先对系统的不可观测状态设计非线性状态观测器,在此基础上通过多步递推得到系统的控制律并设计了未知干扰的参数自适应律,使系统具有L2增益性能。同时把采用常规设计方法需要对过多参数进行辨识问题简化为只需对与未知干扰个数相同的参数进行辨识的问题,简化了控制器结构。最后通过仿真算例验证了所设计控制方案的有效性。