Globally uniformly asymptotical stabilisation of time-delay nonlinear systems

Globally uniformly asymptotical stabilisation of nonlinear systems in feedback form with a delay arbitrarily large in the input is dealt with based on the backstepping approach in this article. The design strategy depends on the construction of a Lyapunov–Krasovskii functional. A continuously differentiable control law is obtained to globally uniformly asymptotically stabilise the closed-loop system. The simulation shows the effectiveness of the method.     

Robust predictor feedback for discrete-time systems with input delays

This work studies the design problem of feedback stabilisers for discrete-time systems with input delays. A backstepping procedure is proposed for disturbance-free discrete-time systems. The feedback law designed by using backstepping coincides with the predictor-based feedback law used in continuous-time systems with input delays. However, simple examples demonstrate that the sensitivity of the closed-loop system with respect to modelling errors increases as the value of the delay increases. The paper proposes a Lyapunov redesign procedure that can minimise the effect of the uncertainty. Specific results are provided for linear single-input discrete-time systems with multiplicative uncertainty. The feedback law that guarantees robust global exponential stability is a nonlinear, homogeneous of degree 1 feedback law.     

Adaptive backstepping‐based control design for uncertain nonlinear active suspension system with input delay

This paper addresses the control problem of adaptive backstepping control for a class of nonlinear active suspension systems considering the model uncertainties and actuator input delays and presents a novel adaptive backstepping‐based controller design method. Based on the established nonlinear active suspension model, a projector operator–based adaptive control law is first developed to estimate the uncertain sprung‐mass online, and then the desirable controller design and stability analysis are conducted by combining backstepping technique and Lyapunov stability theory, which can not only deal with the actuator input delay but also achieve better dynamics performances and safety constraints requirements of the closed‐loop control system. Furthermore, the relationship between the input delay and the state variables of this vehicle suspension system is derived to present a simple and effective method of calculating the critical input delay. Finally, a numerical simulation investigation is provided to illustrate the effectiveness of the proposed controller.     

Inverse optimal design of input-to-state stabilisation for affine nonlinear systems with input delays

We establish robustness of the predictor feedback control law to perturbations appearing at the system input for affine nonlinear systems with time-varying input delay and additive disturbances. Furthermore, it is shown that it is inverse optimal with respect to a differential game problem. All of the stability and inverse optimality proofs are based on the infinite-dimensional backstepping transformation and an appropriate Lyapunov functional. A single-link manipulator subject to input delays and disturbances is given to illustrate the validity of the proposed method.     

带有控制饱和约束的航天器交会输出反馈控制

针对航天器交会问题存在外部干扰和输入饱和的情况, 本文提出了一个输出反馈跟踪控制器. 仅利用测量得到的相对位置信息, 设计了一个滑模观测器用来估计相对角速度, 并根据该估计值设计了一个鲁棒反步控制律. 通过引入一个辅助系统, 对输入饱和情况进行了分析. 采用Lyapunov 稳定性理论, 证明了本文提出的该控制器能够保证位置和速度跟踪误差的一致有界性. 最后通过数值分析验证了所设计的输出反馈控制器的有效性.     

Time‐varying input delay compensation for nonlinear systems with additive disturbance: An output feedback approach

This paper addresses the output feedback tracking control of a class of multiple‐input and multiple‐output nonlinear systems subject to time‐varying input delay and additive bounded disturbances. Based on the backstepping design approach, an output feedback robust controller is proposed by integrating an extended state observer and a novel robust controller, which uses a desired trajectory‐based feedforward term to achieve an improved model compensation and a robust delay compensation feedback term based on the finite integral of the past control values to compensate for the time‐varying input delay. The extended state observer can simultaneously estimate the unmeasurable system states and the additive disturbances only with the output measurement and delayed control input. The proposed controller theoretically guarantees prescribed transient performance and steady‐state tracking accuracy in spite of the presence of time‐varying input delay and additive bounded disturbances based on Lyapunov stability analysis by using a Lyapunov‐Krasovskii functional. A specific study on a 2‐link robot manipulator is performed; based on the system model and the proposed design procedure, a suitable controller is developed, and comparative simulation results are obtained to demonstrate the effectiveness of the developed control scheme.     

State‐Feedback Stabilization of Stochastic Nonlinear Systems with Time‐Varying Delay and Different Orders

This paper studies the problem of state feedback stabilization for a class of stochastic time‐varying delay nonlinear systems which are neither necessarily feedback linearizable nor affine in the control input. Based on the backstepping design method and the adding of a power integrator technique, a state feedback controller is constructed to ensure the origin of closed‐loop system is globally asymptotically stable in probability. The main design difficulty is how to deal with the different power orders, time‐varying delay and the nonsmooth system perturbations. The efficiency of the state feedback controller is demonstrated by a simulation example.     

Composite nonlinear feedback control for strict-feedback nonlinear systems with input saturation

This paper focuses on composite nonlinear feedback (CNF) controller design for tracking control problem of strict-feedback nonlinear systems with input saturation to address the improvement of transient performance. First, without considering the input saturation, a stabilisation control law is designed by using standard backstepping technique for the nonlinear system, then a feedforward control law is added to the backstepping-based stabilisation control law to construct a tracking control law. The tracking control law is tuned to drive the output of the closed-loop system to track a command input with quick response. Then, an additional nonlinear feedback law is constructed and combined with the tracking control law to obtain a CNF control law. The role of this additional nonlinear feedback law is to smoothly change the damping ratio of the closed-loop system while the system output approaches the command input, and to reduce overshoot caused by the tracking control law. It is shown that the extra-adding nonlinear feedback part does not cause the loss of stability of the closed-loop system in its attractive basin.     

Forwarding, backstepping, and finite spectrum assignment for time delay systems

The nonlinear control ideas and results of forwarding and backstepping have been recently extended to systems with time delay. In this paper we discuss how to apply these tools to design robust controls for linear delay systems. We first show that the integral cross-term forwarding produces a feedback law that achieves finite spectrum of the closed loop system. Combining it with backstepping provides a structured design method for a large class of systems with time delay. Robustness of the controller to uncertainties, including uncertain time delay, is illustrated by an example.     

基于非线性干扰观测器的翼伞鲁棒反步跟踪控制

针对干扰条件下的无人翼伞飞行器路径跟踪控制问题,提出一种基于非线性干扰观测器的反馈增益鲁棒反步控制方法.采用二阶跟踪-微分器设计干扰观测器对系统复合干扰进行估计和补偿,设计了反馈增益反步跟踪控制律,通过合理设计增益参数,消除了部分复杂非线性项,避免了虚拟量高阶导数问题,简化了控制器形式.根据Lyapunov理论设计鲁棒反馈补偿项,在保证稳定性的同时提高了系统的鲁棒性.仿真实验结果验证了所提出方法的有效性.     

垂直起降飞机的全局轨迹跟踪控制

研究垂直起降飞机在任意输入耦合作用下的轨迹跟踪控制问题．垂直起降飞机是具有3个自由度、2个控制输入的欠驱动系统．首先通过控制输入和坐标变换，使飞机的动力学方程变换成严格反馈形式；然后基于后推法的思想推导出保证系统渐近收敛于参考轨迹的时变反馈控制规律．该方法将系统分解为低阶子系统来处理，利用中间虚拟控制变量和部分Lyapunov函数筒化了控制器的设计．仿真结果表明所设计的控制器是有效的．     

具有未知参数的机器人-摄像机系统的自适应动态反馈跟踪控制

研究了不确定非完整移动机器人系统的跟踪问题.首先,基于视觉反馈和状态输入变换,展示了一种非完整移动机器人运动学系统的不确定链式模型.基于反步法思想和跟踪误差系统结构,给出了两个重要的新变换.然后运用李雅普诺夫直接方法和扩展巴巴拉引理设计了自适应控制律和动态反馈鲁棒控制器,以实现理想轨迹的跟踪控制.严格证明了闭环误差系统的渐近收敛性.最后,仿真结果证实了提出的控制策略有效.     

Adaptive backstepping control of wheeled inverted pendulum with velocity estimator

In this paper, we introduce a backstepping control design of a wheeled inverted pendulum. Based on a second-order motion equation of the body angle, an adaptive integral backstepping controller is designed to stabilize the body angle. It is shown that the σ-modification rule in the adaptive update law guarantees the boundedness of the errors in estimating the time-varying signal that is an output of a linear system with every bounded input signal. Then, the stabilizing controller for the wheel angle is constructed by a PD-type positive feedback. The derived controller requires the full-state measurements. In the output feedback case, the K filter or the observer backstepping is needed. However, the structure of the controller becomes complicated. We propose a non-model-based differentiator based on the adaptive update law. Since the non-model-based differentiator does not require any knowledge of the dynamic structure of the signal, we can use it as a velocity estimator for unknown nonlinear systems. Therefore, we replaced the velocity measurement with the estimates by the non-model-based differentiator. Finally, simulation results for the proposed controller are presented.     

考虑测量不确定和输入饱和的充液航天器自适应鲁棒控制

本文研究了三轴稳定充液航天器控制系统中同时存在测量不确定,外部未知干扰,参数不确定和控制输入饱和的鲁棒自适应姿态机动控制问题.建模过程中,将晃动液体燃料等效为粘性球摆模型,采用动量矩守恒定律推导出充液航天器的耦合动力学方程.提出了一种将反步控制方法结合非线性干扰观测器和指令滤波器的鲁棒饱和输出反馈复合控制策略,该控制策略不仅能继承反步控制方法的优点,而且通过引入非线性干扰观测器实现对未知外部干扰,参数不确定以及测量不确定的补偿,还能利用指令滤波器处理控制力矩输入饱和的不利影响.基于Lyapunov稳定性分析方法证明了系统状态变量的渐进稳定性.仿真结果验证了提出控制方法的有效性和鲁棒性.     

Observer-based adaptive control for nonlinear input-delay systems with unknown control directions

This paper investigates the problem of adaptive control for strict-feedback nonlinear systems with input delay and unknown control directions. The Nussbaum function is utilised to deal with the unknown control directions and a novel compensation system is introduced to handle the time-varying input delay. By using neural network(NN) approximation and backstepping approaches, an adaptive NN controller is designed which can guarantee the semi-global boundedness of all the signals in the closed-loop system. Two simulation examples are also given to illustrate the effectiveness of the proposed method.     

遗传优化的欠驱动船舶镇定控制

针对带有加速度非完整约束的三自由度欠驱动水面船舶镇定问题,提出了一种基于微分同胚等效变换和Lyapunov直接法的后推镇定控制算法,同时为了解决因系统输入固有饱和特性而导致控制不稳定问题,提出了基于遗传优化的欠驱动水面船舶镇定控制改进算法。并对风浪干扰进行了Lyapunov补偿,保证了控制器对外界干扰的鲁棒性。仿真实验表明了该算法的有效性,并且优化后的控制器有效地防止了因控制能量过大导致的系统不稳问题。     

Stabilization of exponentially unstable discrete-time linear systems by truncated predictor feedback

Predictor state feedback solves the problem of stabilizing a discrete-time linear system with input delay by predicting the future state with the solution of the state equation and thus rendering the closed-loop system free of delay. The solution of the state equation contains a term that is the convolution of the past control input with the state transition matrix. Thus, the implementation of the resulting predictor state feedback law involves iterative calculation of the control signal. A truncated predictor feedback law results when the convolution term in the state prediction is discarded. When the feedback gain is constructed from the solution of a certain parameterized Lyapunov equation, the truncated predictor feedback law has been shown to achieve asymptotic stabilization of a system that is not exponentially unstable in the presence of an arbitrarily large delay by tuning the value of the parameter small enough. In this paper, we extend this result to exponentially unstable systems. Stability analysis leads to a bound on the delay and a range of the values of the parameter for which the closed-loop system is asymptotically stable as long as the delay is within the bound. The corresponding output feedback result is also derived.     

Two‐stage stability control for strict‐feedback systems with input delays and input nonlinear uncertainties

In this paper, a two‐stage control procedure is proposed for stabilization of a class of strict‐feedback systems with unknown constant time delays and nonlinear uncertainties in the input. A nominal controller is first designed to compensate input time delays without considering input nonlinear uncertainties. Extended from backstepping algorithm, input delay compensation is realized by means of predicted states that are computed through integration of cascaded system dynamics, making the nominal closed‐loop system asymptotically stable. Based on the nominal controller presented for the input delay system, a multi‐timescale system is subsequently developed to estimate the unknown input nonlinearity and make the estimate approach the nominal control input as fast as possible. It is proved that the proposed control scheme can make states of the strict‐feedback systems converge to zero and all the signals of the closed‐loop systems are guaranteed to be bounded in the presence of input time delays and nonlinear uncertainties. Simulation verification is carried out to illuminate the effectiveness of the proposed control approach.     

Composite adaptive locally weighted learning control for multi-constraint nonlinear systems

A composite adaptive locally weighted learning (LWL) control approach is proposed for a class of uncertain nonlinear systems with system constraints, including state constraints and asymmetric control saturation in this paper. The system constraints are tackled by considering the control input as an extended state variable and introducing barrier Lyapunov functions (BLFs) into the backstepping procedure. The system uncertainty is approximated by a composite adaptive LWL neural networks (NNs), in which a prediction error is constructed by using a series-parallel identification model, and NN weights are updated by both the tracking error and the prediction error. The update law with composite error feedback improves uncertainty approximation accuracy and trajectory tracking accuracy. The feasibility and effectiveness of the proposed approach have been demonstrated by formal proof and simulation results.