基于自适应Backstepping设计的TCSC非线性鲁棒控制器

电力系统是强非线性的动态大系统,在运行中总要受到外部干扰和内部干扰的影响,从而对其稳定运行造成严重威胁.本文针对带有TCSC单机无穷大母线系统的三阶鲁棒模型,在考虑阻尼系数未知及系统受外部扰动的情况下,将自适应backstepping方法与非线性L₂增益干扰抑制理论融合,构造出系统的存贮函数,并获得非线性自适应鲁棒控制器及参数替换律.所得控制器不仅能够保证系统状态有界,而且能够有效抑制干扰对系统输出的影响.通过对单机系统的仿真结果表明采用该方法的控制器优于传统的控制器.     

一类非线性激励器系统的鲁棒自适应跟踪

考虑一类具有非线性激励器不确定系统的鲁棒跟踪问题，其不确定性是部分已知的。所构造的鲁棒自适应控制方案能确保系统的跟踪误差终极一致有界．与已有文献结果相比．未知参数估计的自适应律和控制器是连续的，从而使得所提出的设计方案在实际控制问题中易实现。且与具有线性激励器的系统一样具有较强的鲁棒性．最后通过数值算例进一步说明了该设计方案是有效的。     

具有输入齿隙的一类非线性不确定系统自适应鲁棒控制

针对一类具有未知输入齿隙、参数不确定以及未建模动态和干扰的非线性系统,设计了自适应鲁棒控制器.将齿隙非线性模型等价表示为具有有界建模误差的全局线性化模型,在此基础上设计了包含自适应模型补偿、反馈稳定和鲁棒反馈3部分的自适应鲁棒控制器,并给出了系统动态跟踪误差和稳态误差指标.理论分析证明,闭环控制系统信号有界且跟踪误差在任意期望的精度范围内,仿真研究验证了所提出方法的有效性.     

具有降阶模型的多变量鲁棒自适应前馈控制器

本文提出了一种多变量鲁棒自适应前馈控制器。该控制器采用低阶模型来控制参数未知的高阶多变量系统时,在可测干扰和有界不可测干扰作用下能保证自适应系统稳定运行。当可测干扰与系统输出之间存在未建模动态时,它可以对可测干扰实行有效的动静态补偿。当只有有界干扰作用时,它能使有界干扰对系统产生的影响最小。本文还给出了采用所提出的控制器控制某钢厂间歇式余热锅炉的仿真结果。     

不确定时滞组合系统的分散鲁棒镇定

讨论不确定时滞组合系统的分散自适应鲁棒镇定问题．外部扰动存在于子系统内部，可以是非线性或时变的，且不确定项和时滞存在于互联项中．不确定项和外部扰动是有界的，但上界未知．利用自适应律估计未知的上界，设计了非线性无记忆控制器．采用非线性控制器可保证闭环组合系统的解一致有界。且系统状态是一致渐近稳定的．仿真结果表明了该设计方法的有效性.     

基于神经网络MIMO非线性系统自适应输出反馈控制

针对一类具有对象不确定和外部干扰的MIMO(多输入多输出)非线性系统提出了自适应鲁棒输出跟踪控制方案.使用了高斯径向基神经网络自适应补偿对象非线性,高增益观测器被用来估计不能直接测量的输出导数.此方法所设计的控制器不仅保证闭环系统稳定,而且所有状态有界以及跟踪误差一致终值有界.仿真结果充分表明了该方案的有效性和可行性.     

一类带时滞状态扰动系统的自适应鲁棒镇定

针对一类带时滞状态扰动的系统,讨论了系统的鲁棒自适应镇定问题.当扰动有界且界未知时,运用自适应控制方法,设计出一类自适应控制器.采用Lyapunov＿Karasovskii函数方法,证明了文中所提出的控制器可鲁棒镇定该系统.     

一类不确定时滞奇异系统的鲁棒非脆弱控制

针对不确定奇异时滞系统，研究了鲁棒非脆弱控制问题。假定不确定性范数有界，设计了基于观测器的控制器，使得闭环系统在不确定性影响下保持鲁棒稳定。仅通过求解相应线性矩阵不等式就可得到鲁棒状态反馈控制器，该控制器不仅对所有容许的系统不确定性使相应的闭环系统渐近稳定，而且满足控制器本身是非脆弱的，达到抑制干扰的效果。     

具有未知高频增益的鲁棒自适应反推控制器

在高频增益未知的情况下,对一类带有未建模动态和输入、输出干扰的系统,给出了一种基于反推技术的鲁棒自适应控制器的设计方法.通过修正传统鲁棒自适应控制中的动态规范化信号和切换-σ算法,证明了闭环系统的所有信号都有界,同时可以取得较好的跟踪性能.仿真结果表明了该方法的有效性.     

一类非线性不确定系统的自适应鲁棒控制

将一类结构和参数均未知且存在外界干扰的非线性系统,等价为具有线性结构的时变系统,在此基础上设计了自适应鲁棒控制器,包括自适应模型补偿、反馈稳定控制和鲁棒反馈控制3部分,实现闭环控制系统信号有界且跟踪误差在期望的精度范围内.理论分析和仿真结果均验证了算法的有效性.     

Observer-based adaptive sliding mode control for robust tracking and model following

This paper presents a methodological approach to design an observer-based adaptive sliding mode control to realize the problem of robust tracking and modeling following for a class of uncertain linear systems. Only partial information of the system states is known. Based on Lyapunov stability theorem, it will be shown that the proposed scheme guarantees the stability of closed-loop system and achieves zero-tracking error in the presence of parameter uncertainties and external disturbances. The proposed observer-based adaptive sliding mode control scheme can be implemented without requiring a priori knowledge of upper bounds on the norm of the uncertainties and external disturbances. This scheme assures robustness against system uncertainties and disturbances. Both the theoretical analysis and illustrative example demonstrate the validity of the proposed scheme.     

Decentralized adaptive control of electrically-driven manipulators

This paper presents two new decentralized strategies for motion control of uncertain electrically-driven manipulators. The first controller is an adaptive position regulation scheme which ensures semiglobal asymptotic convergence of the position error if no external disturbances are present and semiglobal convergence of the error to an arbitrarily small neighborhood of zero in the presence of bounded disturbances. It is shown that the regulation scheme can be modified to provide accurate trajectory tracking control through the introduction of adaptive feedforward elements in the control law; this second control strategy retains the simple decentralized structure of the first controller and ensures arbitrarily accurate tracking in the presence of bounded disturbances. Each of the adaptive schemes is very efficient computationally and requires virtually no information concerning either the manipulator or actuator models. The results of computer simulations and laboratory experiments with both terrestrial and space manipulators demonstrate that accurate and robust motion control can be achieved by using the proposed approach.     

Optimal disturbance rejection control approach based on a compound neural network prediction method

A new optimal disturbance rejection control method is proposed for the system with disturbances via a compound neural network prediction approach in this paper. The disturbances caused by external disturbances and model mismatches can be estimated by a disturbance observer, and the estimation of disturbances is introduced into the neural network predictive model to make the predictive output more accurate. Then based on the new compound neural network predictive model, a controller, which ensures both optimal performance by the receding horizon optimization and strong disturbance rejection ability, is obtained. The proposed scheme is applied to control the temperature of a simplified jacketed stirred tank heater (JSTH). Simulation results demonstrate the effectiveness of the proposed control method.     

Adaptive sliding mode control for trajectory tracking of nonholonomic mobile robot with uncertain kinematics and dynamics

ABSTRACT

This article designs a novel adaptive trajectory tracking controller for nonholonomic wheeled mobile robot under kinematic and dynamic uncertainties. A new velocity controller, in which kinematic parameter is estimated, produces velocity command of the robot. The designed adaptive sliding mode dynamic controller incorporates an estimator term to compensate for the external disturbances and dynamic uncertainties and a feedback term to improve the closed-loop stability and account for the estimation error of external disturbances. The system stability is analyzed using Lyapunov theory. Computer simulations affirm the robustness of the designed control scheme.     

A New Robust Adaptive Neural Network Backstepping Control for Single Machine Infinite Power System With TCSC

For a single machine infinite power system with thyristor controlled series compensation (TCSC) device, which is affected by system model uncertainties, nonlinear time-delays and external unknown disturbances, we present a robust adaptive backstepping control scheme based on the radial basis function neural network (RBFNN). The RBFNN is introduced to approximate the complex nonlinear function involving uncertainties and external unknown disturbances, and meanwhile a new robust term is constructed to further estimate the system residual error, which removes the requirement of knowing the upper bound of the disturbances and uncertainty terms. The stability analysis of the power system is presented based on the Lyapunov function, which can guarantee the uniform ultimate boundedness (UUB) of all parameters and states of the whole closed-loop system. A comparison is made between the RBFNN-based robust adaptive control and the general backstepping control in the simulation part to verify the effectiveness of the proposed control scheme.      

分布式多无人机的时变编队非线性控制设计

研究了基于分布式通信网络的多无人机时变编队控制问题,考虑到外界扰动对多无人机协同编队系统的影响,提出一种新的连续非线性鲁棒编队控制方法.首先基于一致性方法构造了分布式无人机编队误差系统,降低了编队控制器对全局编队信息的要求;然后采用一种基于误差符号函数积分的鲁棒控制算法补偿未知外界扰动的影响,提高了无人机编队系统的鲁棒性,并基于Lyapunov分析的方法,证明了多无人机编队误差的半全局渐进收敛性;最后在四旋翼无人机编队实验平台上进行了多无人机时变编队的实时实验验证,实验结果表明,所提出的分布式编队控制算法可以实现多无人机时变编队控制,且具有较好的协同性能和抗干扰能力.     

一类受扰非线性系统存在执行器及元件故障时的容错控制

本文研究了一类受扰非线性系统存在执行器及元件故障时的镇定控制问题。新的容错控制算法不需要对执行器故障范围界值进行分析估算,因此与现存的方法相比,设计的控制策略结构更加简单,也不需要大量的在线计算。结果表明,应用所设计的控制方法,不仅保证执行器及元件故障下系统的稳定性,也能够有效抑制那些与状态相关不断增长的干扰对系统的影响。通过Lyapunov稳定性理论分析和仿真,均证明了所设计控制算法的有效性,能保证系统同时存在外界干扰、参数不确定性以及执行器/元件故障时的稳定性.     

Adaptive sliding mode observer‐based synchronization for uncertain chaotic systems

This paper investigates the synchronization problem for a class of uncertain chaotic systems. Only partial information of the system states is known. An adaptive sliding mode observer‐based slave system is designed to synchronize a given chaotic master system with unknown parameters and external disturbances. Based on the Lyapunov stability theorem, the global synchronization between the master and slave systems is ensured. Furthermore, the structure of the slave system is simple and the proposed adaptive sliding mode observer‐based synchronization scheme can be implemented without requiring a priori knowledge of upper bounds on the norm of the uncertainties and external disturbances. Simulation results demonstrate the effectiveness and robustness of the proposed scheme. Copyright © 2010 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society     

考虑输入受限的航天器安全接近姿轨耦合控制

针对存在外部扰动和输入受限的航天器安全接近的问题,当扰动上界未知时,基于积分滑模控制理论设计了抗饱和的有限时间自适应姿轨耦合控制器.控制器的设计过程中采用了新型的避碰函数限制追踪航天器运动区域进而保证接近过程中航天器的安全性,同时通过辅助系统和自适应算法分别处理了输入受限和扰动上界未知.借助李雅普诺夫理论证明了在控制器的作用下系统状态在有限时间内收敛,且能够保证追踪航天器在实现航天器接近的过程中不与目标航天器发生碰撞.最后通过数字仿真进一步验证了所设计控制器的有效性.     

Adaptive stabilization and tracking control of electrically driven manipulators

This article presents two new adaptive strategies for motion control of uncertain rigid-link, electrically driven manipulators. The first controller is a position regulation scheme that ensures (semiglobal) asymptotic convergence of the position error if no external disturbances are present, and convergence to an arbitrarily small neighborhood of zero in the presence of bounded disturbances. It is shown that the regulation scheme can be modified to provide accurate trajectory tracking control through the introduction of adaptive feedforward elements in the control law; this second control strategy retains the simple structure of the first controller and ensures arbitrarily accurate tracking in the presence of bounded disturbances. Each of the adaptive schemes is computationally efficient and requires virtually no information concerning either the manipulator or actuator models. Computer simulation results are given for a PUMA 560 manipulator and demonstrate that accurate and robust motion control can be achieved by using the proposed controllers. Experimental results are presented for an IMI Zebra Zero manipulator and confirm that the proposed approach provides a simple and effective means of obtaining high performance motion control. © 1996 John Wiley & Sons, Inc.