Adaptive stabilization for ODE systems coupled with parabolic PDES

This paper is concerned with the adaptive stabilization for ODE systems coupled with parabolic PDEs. The presence of the uncertainties/unknonws and the coupling between the subsystems makes the system under investigation essentially different from those of the existing literature, and hence induces more technique obstacles in control design. Motivated by the related literature, an invertible infinite-dimensional backstepping transformation with appropriate kernel functions is first introduced to change the original system into a new one, from which the control design becomes much convenient. It is worthwhile pointing out that, since the kernel equations for which the kernel functions satisfy are coupled rather than cascaded, the desirable kernel functions are more difficult to derive than those of the closely related literature. Then, by Lyapunov method and a dynamics compensated technique, an adaptive stabilizing controller is successfully constructed, which guarantees that all the closed-loop system states are bounded while the original system states converging to zero. Finally, a simulation example is provided to validate the proposed method.     

Adaptive practical tracking control by output feedback for a class of nonlinear systems

This paper investigates the problem of adaptive practical tracking control by output feedback for a class of nonlinear systems in which the nonlinearities are restricted to be upper bounded by a constant plus a polynomial function of the output multiplied by unmeasured states. To solve the problem, an observer with a dynamic high-gain is first introduced, and then an adaptive output feedback tracking controller is successfully designed using the universal control methodology. It is shown that all the states of the closed-loop system are bounded, and the tracking error can be made arbitrarily small by an appropriate choice of the design parameters after some large enough time. A simulation example is also provided to illustrate the correctness of the theoretical results.     

四维混沌系统的自适应修正函数投影同步

研究了具有未知参数四维混沌系统的修正函数投影同步问题。基于Lyapunov稳定性理论、Barbalat引理和主动控制方法,设计自适应控制器和参数更新规则,实现了该类混沌系统的修正函数投影同步。同时,将该方法用于混沌掩盖保密通信。数值仿真表明了该方法可渐近实现函数投影同步,且在保密通信中可有效恢复信息信号。     

基于观测器的非线性系统执行器死区故障的自适应跟踪控制

研究了一类具有不对称执行器死区故障的非线性系统的跟踪控制问题。基于扩张观测器,提出了一种新的自适应跟踪控制方法。取消了系统所有状态完全可测的限制。在死区模型所有参数以及系统非线性不确定项上界均未知的情况下,所设计的自适应控制器可以很好地消除执行器死区故障的影响,保证跟踪误差有界。仿真结果表明该方法的有效性。     

基于观测器的不确定非线性系统L1自适应控制

针对一类严格块反馈型不确定非线性系统,采用反步设计方法提出了一种新的基于滑模状态观测器的L1自适应控制方案。由于系统状态不完全可测,首先设计滑模观测器对系统状态进行估计,并分析观测器的收敛性,在此基础上,通过反步法得到系统的理想控制律。为了消除反步控制中的“项数膨胀”,引入非线性跟踪微分器来提取理想控制律的微分信号。为提高系统响应的瞬态性能,消除控制输入的高频振荡,引入L1自适应控制对控制律进行改进,通过理论推导证明了闭环系统的稳定性。最后通过数值仿真算例验证了所设计控制方案具有快速的收敛性、良好的跟踪性等期望性能。     

未知非线性系统的神经网络跟踪控制与仿真研究

应用输入／输出反馈线性化方法和李亚普诺夫方法,研究了一类具有未知非线性函数的非线性动态系统的自适应鲁棒输出跟踪控制问题。首先通过坐标变换和输入变换,将非线性系统变换为部分线性可控系统。接着采用多层前向神经网络来逼近未知非线性函数,网络的权值根据李亚普诺夫原则来在线修正,这样就克服了多神经网络控制系统中存在的稳定性问题。同时,为了减少权值学习时间,应用遗传算法预先离线训练网络权值。最后提出了一个基于神经网络建模的自适应鲁棒控制律,给出了李亚普诺夫意义下的稳定性证明。所提出的控制律可确保相应闭环系统的状态及跟踪误差一致最终有界。所给的Van der pol系统的例子说明了所提控制方案的有效性与鲁棒性。     

考虑齿隙的多约束导引控制一体化设计方法

在舰炮制导炮弹进行远程对岸火力支援的末段,考虑舵机齿隙、限定攻击角以及测量视线角速率受限,提出了一种基于动态面滑模与扩张状态观测器的多约束导引控制一体化设计方法。构建了制导炮弹的导引控制一体化的严反馈串级模型,将舵机视为更符合实际的含齿隙双惯量子系统。针对视线角速率和风等未知干扰,设计扩张状态观测器对其实施迅速而准确的估计。设计具备自适应指数趋近律的非奇异终端滑模,致使视线角速率与视线角跟踪误差在有限时间内零化。在高阶串级系统中合理运用动态面滑模,有效改善微分膨胀问题。运用Lyapunov理论证明了系统一致最终有界性以及重要状态的有限时间收敛性。通过对比仿真实验,在所提方法的调控下,含有舵机齿隙的制导炮弹在打击固定与蛇形机动目标时,均具有良好的制导性能。     

严格反馈型随机非线性系统输出反馈滑模控制

研究了一类带有不确定性参数的严格反馈型随机非线性系统的输出反馈镇定问题,主要是采用变结构滑模控制方法(SMC)来设计镇定控制器。首先根据系统的结构和输出状态构造了随机非线性状态观测器,并针对结构参数的不确定性,采用梯度自适应调节律,然后基于系统的观测状态选择滑动模切换流形,给出了不含噪声激励的变结构控制律,并证明滑动模的可达性和闭环系统滑模运动的稳定性,最后讨论了滑模控制的抖振抑制问题。通过系统仿真,与其它鲁棒控制方法进行比较,证明了本方法不仅能够有效地镇定该类随机非线性系统,并且具有一些更好的控制性能。     

Global Output-Feedback Tracking for Nonlinear Cascade Systems with Unknown Growth Rate and Control Coefficients

This paper deals with the global practical tracking problem by output-feedback for a class of uncertain cascade systems with zero-dynamics and unmeasured states dependent growth.The systems investigated are substantially different from the closely related works,and have zero-dynamics,unknown growth rate,and unknown time-varying control coefficients.This makes the problem much more difficult to solve.Motivated by the authors' recent works,this paper proposes a new adaptive control scheme to achieve the global practical tracking.It is shown that the designed controller guarantees that the state of the resulting closed-loop system is globally bounded and the tracking error converges to a prescribed arbitrarily small neighborhood of the origin after a finite time.This is achieved by combining the methods of universal control and dead zone with backstepping technique,and using the framework of performance analysis in the closely related works.A numerical example demonstrates the effectiveness of the theoretical results.     

高超声速飞行器切换多胞系统自适应跟踪控制

针对保证大包线稳定飞行的高超声速飞行器轨迹跟踪控制器设计问题,提出了一种多回路切换多胞自适应跟踪控制方案。基于运动模态在频率上存在显著的时标分离特性,将高超声速飞行器的状态分成内外回路进行设计,考虑到干扰及外回路对内回路的不确定影响,采用增益调度与自适应控制结合的方法设计了内外回路控制器。该方法解决了将该飞行器切换多胞系统作为整体设计时无法综合出保证全局稳定控制器的问题,并且降低了控制器设计的复杂性。仿真结果表明,闭环跟踪系统在工作包线内具有良好的动态响应品质与稳态跟踪性能,从而验证了控制方案的有效性。     

带非线性观测器的欠驱动船舶自适应动态面输出反馈轨迹跟踪控制

针对船速与艏摇角速度均不可测的三自由度欠驱动船舶轨迹跟踪问题,考虑在海洋环境扰动未知,提出一种带非线性观测器的动态面自适应输出反馈控制方法。该方法通过对系统模型进行坐标变换,设计非线性观测器估计船舶的速度向量;采用动态面技术可处理反演法对虚拟控制量求导导致的“微分膨胀”问题,减少计算量;同时采用自适应律估计海洋环境干扰的界值,从而防止参数漂移。利用Lyapunov函数证明该控制律可保证船舶轨迹跟踪误差的一致最终有界性,仿真结果证明了所提出控制方法的有效性。     

基于回归神经网络的滑模跟踪器设计

基于回归神经网络的在线辨识 ,为实现非线性系统自适应控制提供了一种很有应有前景的方法。本文基于具有线性输入特性的神经网络 ,提出了使系统辨识误差具有指数收敛特性的学习算法。为了得到尽可能普遍的控制律 ,本文运用滑模技术设计出控制信号 ,用其补偿神经网络模型与非线性系统之间的匹配误差。以此为基础 ,提出一种新的基于回归神经网络的间接自适应控制方案。仿真结果表明 ,本控制方案具有较好的跟踪性能     

Robust Chattering-Free Finite Time Attitude Tracking Control with Input Saturation

This paper addresses the attitude tracking control problem of a rigid spacecraft in the presence of the modeling uncertainty, external disturbance, and saturated control input by designing two robust attitude tracking controllers. The basic controller is formulated using an integral sliding mode surface which is continuous and provides an asymptotic convergence rate for the closed-loop system. In this case, only the external disturbance with the prior information is considered. Then, to provide a finite time convergence rate and further improve the robustness of the control system under the unknown system uncertainty containing both the modeling uncertainty and external disturbance,a novel integral terminal sliding mode surface(ITSMS) is designed and associated with the continuous adaptive control method. Besides, a command filter is utilized to deal with the immeasurability problem within the proposed ITSMS and an auxiliary system to counteract the input saturation problem. Digital simulations are presented to verify the effectiveness of the proposed controllers.     

Dynamic Power Saving via Least-Square Self-Tuning Regulator in the Virtualized Computing Systems

In recent years,power saving problem has become more and more important in many fields and attracted a lot of research interests.In this paper,the authors consider the power saving problem in the virtualized computing system.Since there are multiple objectives in the system as well as many factors influencing the objectives,the problem is complex and hard.The authors will formulate the problem as an optimization problem of power consumption with a prior requirement on performance,which is taken as the response time in the paper.To solve the problem,the authors design the adaptive controller based on least-square self-tuning regulator to dynamically regulate the computing resource so as to track a given reasonable reference performance and then minimize the power consumption using the tracking result supplied by the controller at each time.Simulation is implemented based on the data collected from real machines and the time delay of turning on/off the machine is included in the process.The results show that this method based on adaptive control theory can save power consumption greatly with satisfying the performance requirement at the same time,thus it is suitable and effective to solve the problem.     

基于自适应动态逆的着舰控制器设计

针对舰载无人机着舰过程中存在参数不确定、舰尾流干扰等问题,设计了一种基于自适应动态逆的着舰控制律.通过动态逆消除了非线性以及多变量耦合,在此基础上加入自适应律,分别设计了俯仰姿态控制器和速度控制器,并应用Lyapunov稳定性原理修正了自适应律并用来处理动力受限时的速度控制问题,保证动力补偿系统的稳定性.仿真验证结果表...     

A note on the model reference adaptive control of linear parabolic systems with constant coefficients

The problem of constructing a model reference adaptive control law for an uncertain 1-dimensional parabolic system with one constant coefficient is considered in this paper. Adaptive control law are obtained by Lyapunov redesign method. The energy method for parabolic systems and the Agmon’s inequality are applied in the analysis, which leads to a stronger result than that of Hong and Bentsman (Automatica, 1994).     

Adaptive Numerical Approach for Optimal Control of a Single Train

This paper considers the optimal control problem of a single train, which is formulated as an optimal control problem of nonlinear systems with switching controller. The switching sequence and the switching time are decision variables to be chosen optimally. Generally speaking, it is very difficult to solve this problem analytically due to its nonlinear nature, the complexity of the controller,and the existence of system state and control input constraints. To obtain the numerical solution, by introducing binary functions for every value of the control input, relaxing the binary functions, and imposing a penalty function on the relaxation, the problem is transformed into a parameter optimization problem, which can be efficiently solved by using any gradient-based numerical approach. Then, the authors propose an adaptive numerical approach to solve this problem. Convergence results indicate that any optimal solution of the parameter optimization problem is also an optimal solution of the original problem. Finally, an optimal control problem of a single train illustrates that the adaptive numerical approach proposed by us is less time-consuming and obtains a better cost function value than the existing approaches.     

多输入非线性串级系统的自适应控制

对一大类含有未知参数的多输入非线性串级系统 ,基于 backstepping递推设计方法 ,进行了自适应控制设计。当自适应控制律作用于该系统时 ,闭环系统的所有信号是有界的 ,并且原系统的状态收敛于零.     

并联式运载器上升段广义超螺旋有限时间控制

针对受模型不确定和外部干扰影响的并联式运载器上升段姿态控制问题, 提出了一种基于广义超螺旋算法的自适应滑模有限时间控制方法。首先, 将姿态跟踪控制问题转化为跟踪误差系统的镇定问题, 建立了面向控制的模型。其次, 将单输入单输出(single input single output, SISO)固定时间广义超螺旋算法拓展应用到多输入多输出(multiple input multiple output, MIMO)耦合非线性系统上, 基于该算法设计了固定时间状态观测器和自适应滑模有限时间控制器, 利用Lyapunov稳定性理论证明了闭环系统的有限时间稳定特性。最后, 通过与传统比例-微分(proportional and differential, PD)控制器仿真对比, 验证了该方法具有更优的控制精度和鲁棒性。     

非仿射非线性系统的自适应模糊输出反馈控制

针对一类单输入单输出非仿射非线性系统,提出了基于观测器的自适应模糊输出反馈控制。该算法通过构造线性误差观测器估计系统输出误差和系统状态,利用估计状态变量和估计输出误差变量设计自适应控制律,采用模糊逻辑系统在线消除非线性系统中的不确定模型,引入监督控制消除系统逼近误差和外界干扰,并利用Lyapunov方法严格证明了在该控制律作用下闭环系统所有信号一致最终有解,闭环系统的输出能最终跟踪期望输出。仿真结果表明了该方法的有效性。