Robust Adaptive Output‐Feedback Dynamic Surface Control of a Class of Nonlinear Systems with Unmodeled Dynamics

This paper presents a robust adaptive output‐feedback dynamic surface control (DSC) for a class of nonlinear systems with unmodeled dynamics or/and uncertain time‐varying disturbances. Based on traditional K‐filters, the proposed adaptive DSC scheme is able to guarantee semi‐global stability of the closed‐loop system without applying any approximation techniques. The adaptive law is necessary only at the first design step, which, together with the introduction of a first‐order filter at each design step, makes the control law easy to implement. Moreover, it is shown that the tracking error can converge to an arbitrarily small residual set by adjusting only one design parameter.     

A Robust Adaptive Terminal Sliding Mode Control for Rigid Robotic Manipulators

In this paper, a robust adaptive terminal sliding mode controller is developed for n-link rigid robotic manipulators with uncertain dynamics. An MIMO terminal sliding mode is defined for the error dynamics of a closed loop robot control system, and an adaptive mechanism is introduced to estimate the unknown parameters of the upper bounds of system uncertainties in the Lyapunov sense. The estimates are then used as controller parameters so that the effects of uncertain dynamics can be eliminated and a finite time error convergence in the terminal sliding mode can be guaranteed. Also, a useful bounded property of the derivative of the inertial matrix is explored, the convergence rate of the terminal sliding variable vector is investigated, and an experiment using a five bar robotic manipulator is carried out in support of the proposed control scheme.     

Fault-tolerant cruise control of electric vehicles with induction motors

A fault-tolerant control scheme is proposed for the cruise control of electric vehicles (trains, cars) that make use of induction motors. It relies on a rotor speed reference generator and on a flux observer which is adaptive with respect to the uncertain rotor and stator resistances and to the load torque as well. The closed loop on-line identification of those three critical uncertain parameters allows for: (i) on-line estimating and imposing the motor flux modulus reference value which minimizes power losses at steady-state and improves power efficiency; (ii) the on-line detection of speed sensor faults as well as the fast switching on redundant motor speed sensors. CarSim simulations illustrate the effectiveness of the proposed approach.     

Adaptive architectures for control of uncertain dynamical systems with actuator and unmodeled dynamics

In adaptive control of uncertain dynamical systems, it is well known that the presence of actuator and/or unmodeled dynamics in feedback loops can yield to unstable closed‐loop system trajectories. Motivated by this standpoint, this paper focuses on the analysis and synthesis of multiple adaptive architectures for control of uncertain dynamical systems with both actuator and unmodeled dynamics. Specifically, we first analyze model reference adaptive control architectures with standard, hedging‐based, and expanded reference models for this class of uncertain dynamical systems and develop sufficient stability conditions. We then synthesize a robustifying term for the latter architecture and analytically show that this term can allow for a relaxed sufficient stability condition. The proposed theoretical treatments involve Lyapunov stability theory, linear matrix inequalities, and matrix mathematics. Finally, we compare the resulting sufficient stability conditions of the considered adaptive control architectures on a benchmark mechanical system subject to actuator and unmodeled dynamics.     

Model reference robust adaptive control for a class of uncertain switched linear systems

In this paper, we proposed a model reference robust adaptive control approach for a class of uncertain switched linear systems, in which subsystems of the switched linear system are in control canonical form. The control architecture is composed of a switched reference system (SRS) and a switched adaptive controller (SAC). The SRS specifies the desired dynamics of the uncertain switched linear system, while the SAC makes the uncertain switched linear system dynamics track the SRS dynamics. By multiple Lyapunov functions method, we prove that the closed‐loop switched system is uniformly bounded under arbitrary switching laws, provided that a linear matrix inequality (LMI)‐based sufficient condition is satisfied. We apply the proposed approach to a typical servo‐hydraulic positioning system. The simulation results show that the proposed approach is fairly insensitive to disturbances, uncertainties and non‐smoothly varying dynamics, and performs better than a proportional‐derivative controller or a minimal controller synthesis controller. Copyright © 2011 John Wiley & Sons, Ltd.     

不确定多时滞系统的自适应控制

研究一类不满足匹配条件的不确定多时滞系统的自适应控制．基于时滞系统的一个新的稳定性定理，得到了时滞依赖充分性条件，并设计了自适应控制律，使得闭环系统以指定衰减度指数稳定．仿真算例验证了所提出控制策略的有效性．     

Fuzzy adaptive nonlinear sensor‐fault tolerant control for a quadrotor unmanned aerial vehicle

In this paper, a novel fuzzy adaptive nonlinear fault tolerant control design scheme is proposed for attitude dynamics of quadrotor UAV subjected to four sensor faults (bias, drift, loss of accuracy, loss of effectiveness). The sensor faults in Euler angle loop are transformed equivalently into a mismatched uncertainty vector, and other unknown items involving faults, uncertain parameters and external disturbances in angular velocity loop are lumped into an unknown nonlinear function vector. Fuzzy logic systems with adaptive parameters are used to approximate the mismatched uncertainty and lumped nonlinear function vectors. Dynamic surface control is applied to design the fault tolerant controller, and sliding mode control is introduced to improve the control accuracy. All signals of the closed‐loop control system are proved to be semi‐global uniformly ultimately bounded. Simulations demonstrate the effectiveness of the proposed approach for sensor faults.     

Learning control for induction motor servo drives with uncertain rotor resistance

The tracking control problem for induction motor servo drives with mechanical and electrical uncertainties is addressed. Under the assumptions that the reference profile for the rotor angle is periodic of known period and the rotor flux modulus reference signal is persistently exciting, a robust adaptive learning control is designed, which is adaptive with respect to the uncertain rotor resistance and is able to ‘learn’ the periodic disturbance signal due to mechanical uncertainties by identifying the Fourier coefficients of its truncated approximation.     

不匹配不确定性系统的近似变结构输出跟踪控制

针对一类具有不匹配不确定性的非线性系统,提出一种结合变结构控制方法及自适应控制方法输出跟踪控制器。首先提出一种保证不确定性系统跟踪误差指数稳定的近似变结构控制器;进而得到一种具有不确定性范数上界估计能力的自适应近似变结构控制器,并证明了所提出的自适应近似变结构控制器使跟踪误差在时间趋于无穷时收敛于零。     

Adaptive actuator failure compensation for multivariable feedback linearizable systems

A feedback linearization‐based adaptive control scheme is developed for multivariable nonlinear systems with redundant actuators subject to uncertain failures. Such an adaptive controller contains a direct adaptive actuator failure compensator to compensate the uncertain actuator failure, a nonlinear feedback to linearize the nonlinear dynamics, and a linear feedback to stabilize the linearized system. The key new design feature is the estimation of both the failure patterns and the failure values, for direct adaptive actuator failure compensation, newly developed for multivariable feedback linearizable nonlinear systems. With direct control signal adaptation, the adaptive failure compensation design ensures closed‐loop stability and asymptotic output tracking in the presence of actuator failure uncertainties. Simulation results from an application to attitude control of a near‐space vehicle dynamic model are presented to verify the desired system performance with adaptive actuator failure compensation. Copyright © 2015 John Wiley & Sons, Ltd.     

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.     

Prescribed performance adaptive neural output feedback dynamic surface control for a class of strict‐feedback uncertain nonlinear systems with full state constraints and unmodeled dynamics

This paper studies the output feedback tracking control problem for a class of strict‐feedback uncertain nonlinear systems with full state constraints and unmodeled dynamics using a prescribed performance adaptive neural dynamic surface control design approach. A nonlinear mapping technique is employed to address the state constraints. Radial basis function neural networks are utilized to approximate the unknown nonlinear functions. The unmodeled dynamics is addressed by introducing an available dynamic signal. Subsequently, we construct the controller and parameter adaptive laws using a backstepping technique. Based on Lyapunov stability theory, it is shown that all signals in the closed‐loop system are semiglobally uniformly ultimately bounded and that the tracking error always remains within the prescribed performance bound. Simulation results are presented to demonstrate the effectiveness of the proposed control scheme.     

基于无源性的异步机自适应控制

对近年来出现的一种异步机控制方法--基于无源性的控制(简称PBC)进行了发 展,从理论上取消了对定子电流反馈的要求,并针对转子电阻变化,增加了参数自调整的自 适应控制和转子磁链闭环控制.该控制器保留了PBC方法的简单、无奇异点等优点,而且抑 制了由于转子电阻变化引起的转速和磁链跟踪误差.     

A novel adaptive bilateral control scheme using similar closed‐loop dynamic characteristics of master/slave manipulators

This article presents a novel adaptive bilateral control scheme for obtaining ideal responses for teleoperation systems with uncertainties. A condition that is equivalent to getting an ideal response in teleoperation has been found to be making the closed‐loop dynamics of master and slave manipulators a similar form. An adaptive approach is applied to achieve similarity for the uncertain master and slave manipulators. Using the similar closed‐loop dynamic characteristics of master/slave teleoperation systems, excellent position and force tracking performance has been obtained without estimating the impedance of human and environment. The validity of the theoretical results is verified by experiments. © 2001 John Wiley & Sons, Inc.     

Robust adaptive output‐feedback control for nonlinear systems with output unmodeled dynamics

In this paper, for a class of uncertain nonlinear systems in the presence of inverse dynamics, output unmodeled dynamics and nonlinear uncertainties, a robust adaptive output‐feedback controller design is proposed by combining small‐gain theorem, changing supply function techniques with backstepping methods. It is shown that all the signals of the closed‐loop system are uniformly bounded in biased case, and the output can be regulated to a small neighborhood of the origin in unbiased case. Furthermore, under some additional assumptions, an asymptotical result is obtained. Copyright © 2007 John Wiley & Sons, Ltd.     

Robust Adaptive Fractional‐Order Terminal Sliding Mode Control for Lower‐Limb Exoskeleton

This paper introduces a robust adaptive fractional‐order non‐singular fast terminal sliding mode control (RFO‐TSM) for a lower‐limb exoskeleton system subject to unknown external disturbances and uncertainties. The referred RFO‐TSM is developed in consideration of the advantages of fractional‐order and non‐singular fast terminal sliding mode control (FONTSM): fractional‐order is used to obtain good tracking performance, while the non‐singular fast TSM is employed to achieve fast finite‐time convergence, non‐singularity and reducing chattering phenomenon in control input. In particular, an adaptive scheme is formulated with FONTSM to deal with uncertain dynamics of exoskeleton under unknown external disturbances, which makes the system robust. Moreover, an asymptotical stability analysis of the closed‐loop system is validated by Lyapunov proposition, which guarantees the sliding condition. Lastly, the efficacy of the proposed method is verified through numerical simulations in comparison with advanced and classical methods.     

一类非线性多变量系统的多模型自适应控制

针对一类不确定的非线性多变量离散时间动态系统,提出了一种基于切换的多模型自适应控制方法.该控制方法的特点在于以下两个方面:首先,引入一个高阶差分算子使得非线性系统的非线性项的限制条件不再要求全局有界;其次,提出的控制方法由线性自适应控制器、神经网络非线性自适应控制器以及切换机构组成:线性控制器用来保证闭环系统的输入输出信号有界,神经网络非线性控制器用来改善闭环系统的性能,基于性能指标的切换机构在每一时刻选择性能指标较好的控制器对系统进行控制.理论分析和仿真实验说明了提出的多模型自适应控制方法的有效性.     

Wavelet based control for a class of delayed nonlinear systems with input constraints

In this paper, a delay independent adaptive control strategy is presented for a class of uncertain, delayed nonlinear system subjected to actuator saturation. In proposed control scheme wavelet networks are used for approximation of unknown system dynamics as well as a wavelet based compensator is designed to deal with actuator saturation. Delayed wavelet networks are used for identification of unknown system dynamics having state delayed terms, thereby the approximation capabilities of delayed wavelet network are utilized. Adaptation laws are developed for the online tuning of wavelet parameters. Adaptation singularity problem is solved by employing a switching scheme. The stability of closed loop system and ultimate upper boundedness all closed loop signals is proved by constructing a Lyapunov–Krasovskii functional.     

基于一种修改的李亚普诺夫函数的自适应模糊滑模控制

针对一类不确定非线性系统,基于一种修改的李亚普诺夫函数并利用Ⅱ型模糊系统的 逼近能力,提出了一种稳定自适应模糊控制器设计的新方案.该方案能够避免现有的一些自适 应模糊/神经网络控制器设计中对控制增益一阶导数上界的要求.通过理论分析,证明了闭环模 糊控制系统是全局稳定的,跟踪误差收敛到零.     

全局稳定的PD+前馈机器人鲁棒自适应控制

研究应用PD+前馈控制结构的不确定性机器人轨迹跟踪问题.在忽略摩擦力和外部 扰动情况下,设计了一大类综合的自适应控制策略,能保证系统全局的渐近稳定;在摩擦力和外 部扰动存在时,提出两种新颖的鲁棒自适应混合控制方法,不仅可以保证闭环系统的全局稳定 性,同时还能给出系统清晰的暂态性能.严格的理论证明和二自由度机器人的仿真验证了控制 器的有效性.