A switching adaptive controller for feedback linearizable systems

One of the main open problems in the area of adaptive control of linear-in-the-parameters feedback linearizable systems is the computation of the feedback control law when the identification model becomes uncontrollable. The authors propose a switching adaptive control strategy that overcomes this problem. The proposed strategy is applied to nth-order feedback linearizable systems in canonical form. The closed-loop system is proved to be globally stable in the sense that all the closed-loop signals are bounded and the tracking error converges arbitrarily close to zero. No assumptions are made about the type of nonlinearities of the system, except that such nonlinearities are smooth. However, the proposed controller requires knowledge of the sign and lower bound of the input vector field     

Controlling chaotic and hyperchaotic systems via a simple adaptive feedback controller

This paper investigates the problem of chaos control, and proposes a simple adaptive feedback control method for it under a reasonable assumption. In comparison with previous methods, the present control technique is simple both in the form of the controller and in its application. A numerical example using the Genesio chaotic system verifies the effectiveness and correctness of the proposed approach.     

A simple adaptive PI controller for linear systems with constantdisturbances

It is known that an adaptive controller via high-gain output feedback can globally stabilize a class of minimum phase systems with relative degree one. However, exact output regulation is difficult for systems with disturbances. In this paper, we consider linear single-input/single-output (SISO) systems with unknown constant disturbances. We present a simple adaptive output feedback controller with an integral action and show that it can asymptotically stabilize those disturbed systems. The proposed PI type adaptive controller can also deal with the output tracking problem of a step reference     

A survey on delayed feedback control of chaos

This paper introduces the basic idea and provides the mathematical formulation of the delayed feedback control （DFC） methodology, which has been widely used in chaos control. Stability analysis including the well-known odd number linfitation of the DFC is reviewed. Some new developments in characterizing the limitation of the DFC are presented. Various modified DFC methods, which are developed in order to overcome the odd number limitation, are also described. Finally, some open problems in this research field are discussed.     

垂直面欠驱动自治水下机器人定深问题的自适应输出反馈控制

针对垂直面欠驱动自治水下机器人(AUV)定深控制问题,本文仅使用可测量的深度和纵摇角信息,基于反步法设计自适应输出反馈控制器.为此首先设计观测器,实现不可测纵摇角速度反馈;再利用径向基神经网络对不确定水动力系数和纵荡、垂荡及纵摇角速度耦合产生的非线性结构进行补偿;采用自适应策略对纵荡和垂荡速度形成的有界干扰进行抑制.本文采用AUV一阶非完整模型,不以线性化为目的,放宽了纵摇角只能在小范围内变化的限制.最后通过理论证明和仿真实验表明该方法能够实现AUV深度和姿态控制,对未建模非线性动态和有界扰动具有很强的自适应性和鲁棒性.     

A survey on delayed feedback control of chaos

This paper introduces the basic idea and provides the mathematical formulation of the delayed feedback control (DFC) methodology, which has been widely used in chaos control. Stability analysis including the well_known odd number limitation of the DFC is reviewed. Some new developments in characterizing the limitation of the DFC are presented. Various modified DFC methods, which are developed in order to overcome the odd number limitation, are also described. Finally, some open problems in this research field are discussed.     

A hybrid learning/adaptive partial state feedback controller for RLED robot manipulators

In this paper, we present an adaptive partial state-feedback repetitive learning control algorithm for a rigid-link electrically-driven (RLED) robot manipulator actuated by brushed DC (BDC) motors. The proposed controller is designed to compensate for repeatable mechanical uncertainty via a learning control term while an adaptive control loop is used to compensate for parametric uncertainty in the electrical dynamics. The proposed controller guarantees semi-global asymptotic link position tracking while only requiring measurements of link position and electrical winding current (e.g. measurements of link velocity are not required).     

A simple velocity-free controller for attitude regulation of a spacecraft with delayed feedback

In this note, we consider the application of a velocity-free controller for attitude regulation of a rigid spacecraft with gas jet actuators when the effects of time-delays in the feedback loop are taken into consideration. Simple sufficient conditions for exponential stability are presented. Some structural properties of the resulting closed-loop system are studied, and relevant design tools are demonstrated.     

利用正反馈引导混沌系统到周期解

提出了一种抑制混沌的方法, 通过对混沌动力系统增加一个基于系统变量的正反馈控制项, 成功而快速引导系统从混沌运动转化为低周期运动. 利用Melnikov方法分析了该控制方法在Duffing振子中实现混沌抑制的控制机理, 得到了结论: 正反馈项可以消除混沌系统的稳定流形和不稳定流形的横截相交. 仿真表明, 该方法简单而广泛适用.     

Stability and robustness properties of a simple adaptive controller

A low-order adaptive tracking controller is proposed for linear time-invariant plants with a relative degree not exceeding two. The order of the plant is not required to be known a priori. The algorithm is robustly stable with respect to small linear time-invariant plant perturbations and bounded disturbances. The robustness is achieved by using a projection of the parameter estimates in the control law. An additional a priori information needed to design the controller is bounds on the plant parameters. In the absence of plant perturbations and disturbances, perfect tracking is obtained     

永磁同步电动机的有限时间自适应混沌控制

针对永磁同步电动机（PMSM）的混沌吸引子现象以及研究中只能实现平衡状态的周期点的混沌同步控制问题,提出了一种基于自动控制理论与有限时间控制原理的零误差系统算法。首先,通过已建立的PMSM的数学模型,经过数学公式转化得到PMSM各状态变量与其预期设定值之间形成的误差系统模型;然后,利用李雅谱诺夫稳定性理论,对所形成的误差系统模型进行同步控制器与校正率的设计,并证明误差系统在有限时间内快速地收敛至零点;最后,对误差系统施加干扰量,对算法进行鲁棒性分析。理论与仿真结果表明,所提出的算法能实现误差系统到达零点后仍一直维持在零点的平衡状态,有效地抑制PMSM系统中混沌吸引子现象的产生,灵活地调整PMSM的输入输出,在确保PMSM正常运转的基础上,PMSM系统对不定性参量与外部扰动量具有良好的鲁棒特性。     

冷带轧机厚控系统自适应鲁棒输出反馈动态控制器设计

冷带轧机厚控系统可被认为是一个受外界干扰的线性不确定时滞系统.本文首先设计了标称系统下的鲁棒输出反馈动态控制器,以改善闭环系统的动静态性能;其次,在系统不需要满足不确定性匹配条件的情况下,将参数和外部扰动不确定性综合考虑.应用Lyapunov稳定性理论设计了系统不确定性上界参数的自适应估计器和系统的自适应控制器,保证了闭环系统的渐近稳定性,减小了设计的保守性;两者结合实现了板带出口厚度的有效控制.最后通过一个仿真实例说明本文所提出的自适应鲁棒控制器的有效性.     

A composite adaptive control with flexible quantity feedback for flexible-link manipulators

This article presents a mixture of joint subsystem-based adaptive control and simple flexible quantity feedback for flexible-link manipulators. The complex full flexible-arm system is composed of two severely coupling subsystems called the joint subsystem and flexible subsystem. Linear parametrization is first used to design an adaptive law for identifying the unknown parameters of a flexible manipulator based only on the joint subsystem. Joint-angle trajectory tracking can thus be achieved using the derived stable nonlinear adaptive control with the estimates of unknown parameters. To stabilize the flexible subsystem, we can simply add the feedback of transversal acceleration or deflection at the end point and/or along the flexible beam. The suggested approach is much simpler than those based on the full dynamics model of a flexible arm in required computations. Computer simulations on a single-link and a two-link flexible arm are tested to illustrate the validity of the strategy for both trajectory tracking and active damping. © 1996 John Wiley & Sons, Inc.     

A modified high-order adaptive output feedback control algorithm for linear plants

A modified output feedback control algorithm is proposed for a linear plant subjected to parametric uncertainty; its efficiency is validated and the results of numerical simulations are presented.     

模糊PID控制器在自适应巡航控制系统中的应用

车辆的油门控制算法是自适应巡航控制系统(ACC：Adaptive Cruise Control)中的核心算法之一。这里采用的模糊PID算法(Fuzzy PID)是对常用的两输入单输出模糊控制算法的改进。通过使用Matlab／Simulink建立车辆动力学模型和控制器模型,对控制器的性能进行了仿真分析,验证了算法的合理性。     

A feedback scheduler for real-time controller tasks

The problem studied in this paper is how to distribute computing resources over a set of real-time control loops in order to optimize the total control performance. Two subproblems are investigated: how the control performance depends on the sampling interval, and how a recursive resource allocation optimization routine can be designed. Linear quadratic cost functions are used as performance indicators. Expressions for calculating their dependence on the sampling interval are given. An optimization routine, called a feedback scheduler, that uses these expressions is designed.     

A high-gain scaling technique for adaptive output feedback control of feedforward systems

In this note, we propose an adaptive output feedback control design technique for feedforward systems based on our recent results on dynamic high-gain scaling techniques for controller design for strict-feedback systems. The system is allowed to contain uncertain functions of all the states and the input as long as the uncertainties satisfy certain bounds. Unknown parameters are allowed in the bounds assumed on the uncertain functions. If the uncertain functions involve the input, then the output-dependent functions in the bounds on the uncertain functions need to be polynomially bounded. It is also shown that if the uncertain functions can be bounded by a function independent of the input, then the polynomial boundedness requirement can be relaxed. The designed controllers have a very simple structure being essentially a linear feedback with state-dependent dynamic gains and do not involve any saturations or recursive computations. The observer utilized to estimate the unmeasured states is similar to a Luenberger observer with dynamic observer gains. The Lyapunov functions are quadratic in the state estimates, the observer errors, and the parameter estimation error. The stability analysis is based on our recent results on uniform solvability of coupled state-dependent Lyapunov equations. The controller design provides strong robustness properties both with respect to uncertain parameters in the system model and additive disturbances. This robustness is the key to the output feedback controller design. Global asymptotic results are obtained.     

Robust adaptive control using a universal approximator for SISOnonlinear systems

This paper deals with the robust adaptive control of a class of nonlinear systems in the presence of parametric uncertainties and dominant uncertain nonlinearities. The proposed controller utilizes the robust adaptive control to guarantee uniform boundedness and convergence of tracking errors. In addition, an adaptive fuzzy logic system is used as a universal approximator to reduce the model uncertainties coming from uncertain nonlinearities and to improve tracking performance. The approach does not require the matching condition imposed on control systems by using the backstepping design procedure, and provides boundedness of tracking errors under poor parameter adaptation. The method can be applied to a class of single-input single-output (SISO) nonlinear systems, transformable to a parametric-strict-feedback form     

对混沌自适应控制的控制强度的讨论之二

文中对文献[1]提出的混沌自适应控制方法中给出的控制强度取值范围的计算方法作出了重要修改,指出了上文忽略的与控制矩阵的复数本征值λ±对应的控制强度,对离散系统只要满足｜λ±｜＜1亦可控制混沌,且更有效。其次指出对连续性系统仅考虑文献[1]给出的条件是不够的,控制强度还要满足λ±值的实部小于零,即微分方程的李雅普诺夫渐近稳定条件才能有效控制混沌。     

Output feedback adaptive RISE control for uncertain nonlinear systems

In this article, committed to extending the robust integral of the sign of the error (RISE) feedback control to the working condition of output feedback, a novel output feedback controller with a continuously bounded control input which combines the adaptive control and integral robust feedback will be proposed for trajectory tracking of a family of nonlinear systems subject to modeling uncertainties. A novel adaptive state observer (ASO) with disturbance rejection performance is creatively constructed to derive real-time estimation of the unmeasured state signals. Moreover, a projection-type adaption law is integrated to handle parameter uncertainties and an integral robust term is employed to deal with external disturbances. It is shown that asymptotic estimation performance and meanwhile asymptotic tracking result can eventually be derived. Simulation validations are implemented to demonstrate the high tracking performance of the presented controller. Notably, the synthesized control algorithm can be readily extended to the Euler–Lagrange systems. Typically, it can be extended to practical electromechanical equipment such as three-dimensional vector forming robots to improve the real-time forming accuracy.