永磁同步电机的自适应反演滑模变结构控制

针对永磁同步电机提出一种基于反演的PMSM自适应滑模控制方案.设计基于反演的滑模变结构位置控制器,通过RBF神经网络实现系统参数变化和外部负载扰动等引起的不确定上界值的在线辨识,减小滑模控制器的控制量,并引入饱和函数来减弱系统的"抖动"现象.理论分析和仿真结果对比表明,基于RBF神经网络的自适应反演滑模控制对参数变化和外部负载扰动具有很好的鲁棒性,永磁同步电动机获得了很好的跟踪效果.     

舰船混沌运动的单输入自适应变结构控制

针对在舰船混沌运动控制中由模型不确定性及外部扰动无法确知所引起的控制结果无法保证的问题,采用自适应控制与滑模变结构控制相结合的方法,在设计切换函数时,将符号函数转移到控制输入的一阶导数当中,有效抑制了变结构控制中的抖振问题,并提出了一种单输入自适应滑模变结构控制方法.实验结果表明,与传统滑模变结构控制相比,新方法能够在系统模型具有不确定性及未知外部扰动的情况下实现舰船混沌运动的良好控制,为舰船混沌运动控制提供了一种可靠的工程实现途径.     

不确定非线性系统的自适应反演终端滑模控制

针对一类参数严格反馈型不确定非线性系统, 本文提出一种自适应反演终端滑模控制方法. 反演控制的前n-1步结合自适应律估计系统的未知参数, 第n步采用非奇异终端滑模, 使系统最后一个状态有限时间内收敛.利用微分估计器获得误差系统状态的导数, 并设计了高阶滑模控制律, 去除控制抖振, 使系统对于匹配和非匹配不确定性均具有鲁棒性. 同自适应反演线性滑模方法相比, 所提方法提高了系统的收敛速度和稳态跟踪精度, 并且控制信号更加平滑. 仿真结果验证了该方法的有效性.     

反演滑模控制在倒立摆中的应用与仿真研究

应用滑模控制中的反演设计原理,以一级倒立摆为控制对象,设计了滑模控制器,使系统在响应的全过程都具有鲁棒性,克服了传统变结构控制中到达模态鲁棒性差的缺点,对该类非线性系统,提出了新的滑模控制器的设计方法。仿真结果表明,该方法成功地实现了对输入信号的位置随动控制,并通过与传统方法进行对比,验证了反演滑模控制具有较好的快速和稳定性能,同时也削弱了抖振的发生,实现了实时跟踪控制。     

反馈线性化最优滑模变结构励磁控制

将滑模变结构控制具有对摄动的完全自适应性与反馈线性化理论和最优控制理论结合起来,针对励磁系统,提出了一种基于反馈线性化最优的滑模变结构控制方法,给出了控制器的设计过程,避免了通常设计滑模变结构控制器时参数选取的盲目性,保证系统运行在较佳状态,且按指数趋近律设计的滑模变结构控制器不易产生抖动。仿真结果表明,这种方法能够充分发挥滑模变结构控制的鲁棒性优点,对电力系统具有较好的稳定作用。     

反舰导弹的自适应全局滑模变结构控制

为了消除变结构控制的到达阶段,保证系统在整个控制过程中的鲁棒性,提出了一种自适应全局滑模变结构控制方法。该方法利用自适应控制来调节变结构控制器的参数,对系统不确定项的上界进行估计,保证了整个闭环控制系统的渐近稳定性。考虑到反舰导弹的法向过载输出存在非最小相位特性,采用了输出重定义技术来解决。在此基础上,应用自适应全局滑模变结构控制方法设计导弹的飞行控制系统,保证了导弹的新输出量渐近地跟踪其期望值。仿真结果证明了所提出的控制方法的有效性。     

基于神经网络的不确定机器人自适应滑模控制

提出一种机器人轨迹跟踪的自适应神经滑模控制。该控制方案将神经网络的非线性映射能力与变结构控制理论相结合,利用RBF网络自适应学习系统不确定性的未知上界,神经网络的输出用于自适应修正控制律的切换增益。这种新型控制器能保证机械手位置和速度跟踪误差渐近收敛于零。仿真结果表明了该方案的有效性。     

时变系统的自适应跟踪控制*

本文将基于滑模变结构控制的模型偏差补偿控制方案，应用于一类线性时变系统的自适应控制，实现了高精度的连续轨迹跟踪，并且通过对典型时变对象－飞机的俯仰控制系统的仿真，证明了该方案在实际应用中的可行性。     

独立线控转向电机转角自适应反演滑模控制

针对独立线控转向系统中转向直流电机控制精度低、响应速度慢的问题,以独立线控转向系统转向电机为控制对象,采用自适应反演滑模控制(ABSMC)算法对转向电机转角进行跟踪控制.通过反步法推导控制律,并利用Lyapunov理论证明了闭环系统的稳定性.应用Carsim与Simulink的联合仿真,以横摆角速度不变的变传动比控制为...     

基于扰动观测器的机械臂自适应反演滑模控制

机械臂的动力学模型通常包含一定的结构不确定性,并受到外界未知干扰的影响。针对现有模型的不确定性特点,提出了一种基于非线性扰动观测器的自适应反演滑模控制方法,解决机械臂的轨迹跟踪控制问题。对于外界干扰,利用非线性扰动观测器进行观测补偿,无需上界先验知识;对于结构不确定性,引入反演滑模控制,同时设计自适应律,保证闭环系统的稳定性并增强系统的动态适应性。仿真结果证明,所提出的方法可以有效克服系统不确定性,降低控制输入信号的抖振,最终实现期望轨迹的快速精确跟踪。     

小型无人直升机反步自适应控制

针对具有强非线性、高度耦合以及参数不确定性特点的小型无人直升机系统,提出一种基于小脑模型关节控制器（Cerebellar Model Articulation Control,CMAC）神经网络的自适应反步控制方法,该方法采用小脑模型关节控制器神经网络在线学习系统不确定性以及反步控制中各阶虚拟控制量的导数信息,设计鲁棒控制项克服CMAC神经网络在线学习系统不确定性的误差,控制律由反步法回归递推得到。仿真结果表明,在模型参数不确定和存在较大误差的情况下,所设计的控制律具有理想的姿态跟踪性能以及良好的鲁棒性。     

基于鲁棒自适应反步的可重复使用飞行器再入姿态控制

考虑惯性矩阵不确定和力矩扰动的影响, 设计再入可重复使用飞行器的鲁棒自适应反步姿态控制器. 首先, 设计虚拟控制时, 通过自适应实现对不确定项的未知边界的估计; 其次, 设计实际控制输入时, 为消除反步法的“计算爆炸”问题, 将虚拟控制导数作为不确定项, 引入鲁棒项消除不确定与力矩扰动的影响; 再次, 基于Lyapunov 理论证明了跟踪误差收敛到任意小邻域; 最后, 基于X-33 的六自由度模型仿真验证了所设计的控制策略的有效性.     

柔性自激异步发电系统反演自适应滑模控制

为抑制宽转速范围条件下柔性自激异步发电系统(FS-CAGS)电压定向谐波干扰,提高FS-CAGS鲁棒稳定控制能力,实现功率快速跟踪控制,采用扩展卡尔曼滤波EKF电压定向与反演自适应滑模控制相结合的方法,提出一种EKF电压定向反演自适应滑模直接功率控制新方法.军用底盘集成式直流微电网中FS-CAGS控制仿真实验结果表明,在负载冲击扰动和宽转速突变条件下,相对于传统直接电压定向精确反馈线性化鲁棒控制方法,新控制方法可加快直流输出电压稳定速度,减小电压超调,提高功率跟踪速度,FS-CAGS电流谐波抑制和鲁棒稳定能力得到加强.     

Fuzzy adaptive control for pure-feedback system via time scale separation

A fuzzy adaptive control method is proposed for a class of completely non-affine purefeedback nonlinear systems. By the combination of back-stepping control method and time scale separation, the virtual/actual control inputs are derived from the solutions of a series of fast dynamical equations. This strategy avoids the drawback of “explosion of complexity” inherently existing in the conventional back-stepping design for the pure-feedback system as the dynamic surface control (DSC) method does for the strict-feedback nonlinear system. By using mean value theorem, error system dynamic is obtained for each subsystem. Thus, Lyapunov theory can be employed for the stability analysis. It shows that the developed fuzzy adaptive control scheme achieves semi-global uniform ultimate boundedness of all the signals in the closed loop. Simulation results are presented to show the effectiveness of the approach.     

Adaptive backstepping control design for linear multivariable plants

A nonlinear backstepping scheme is developed for adaptive control of linear plants with multiple inputs and multiple outputs. Solutions to plant parametrization, state observer, and adaptive control law for the multivariable backstepping design are proposed. The developed adaptive controller has the desired properties for ensuring closed-loop signal boundedness and asymptotical tracking.     

分布式多输入系统的自律鲁棒自适应分散控制

为了实现一类分布式多输入系统的分散鲁棒自适应控制, 基于状态扩张和反演干扰抑制控制, 提出一种自律鲁棒自适应分散控制的新方法. 结合直接反馈线性化和最优控制, 给出了自律最优鲁棒自适应分散控制的设计方法. 仿真结果表明, 所提出方法能够有效实现各子系统的自律鲁棒稳定、全系统整体鲁棒稳定和不确定参数自适应, 同时通过求解LMI, 具备了最优干扰抑制的功能.

     

Adaptive neural network asymptotical tracking control for an uncertain nonlinear system with input quantisation

In this paper, the problem of adaptive neural network asymptotical tracking is investigated for a class of nonlinear system with unknown function, external disturbances and input quantisation. Based on neural network technique, an adaptive asymptotical tracking controller is provided for an uncertain nonlinear system via backstepping method. In order to reduce complexity of the control algorithm in the backstepping design process, a sliding mode differentiator is employed to estimate the virtual control law and only two parameters need to be estimated via adaptive control technique. The stability of the closed-loop system is analysed by using Lyapunov function method and zero-tracking error performance is obtained in the presence of unknown nonlinear function, external disturbances and input quantisation. Finally, an application example is employed to demonstrate the effectiveness of the proposed scheme.     

Adaptive learning tracking control of robotic manipulators with uncertainties

An adaptive learning tracking control scheme is developed for robotic manipulators by a synthesis of adaptive control and learning control approaches. The proposed controller possesses both adaptive and learning properties and thereby is able to handle robotic systems with both time-varying periodic uncertainties and time invariant parameters. Theoretical proofs are established to show that proposed controllers ensure asymptotical tracking performance. The effectiveness of the proposed approaches is validated through extensive numerical simulation results.     

Adaptive back-stepping pitch angle control for wind turbine based on a new electro-hydraulic pitch system

A new electro-hydraulic pitch system is proposed to smooth the output power and drive-train torque fluctuations for wind turbine. This new pitch system employs a servo-valve-controlled hydraulic motor to enhance pitch control performances. This pitch system is represented by a state-space model with parametric uncertainties and nonlinearities. An adaptive back-stepping pitch angle controller is synthesised based on this state-space model to accurately achieve the desired pitch angle control regardless of such uncertainties and nonlinearities. This pitch angle controller includes a back-stepping procedure and an adaption law to deal with such uncertainties and nonlinearities and hence to improve the final pitch control performances. The proposed pitch system and the designed pitch angle controller have been validated for achievable and efficient power and torque regulation performances by comparative experimental results under various operating conditions.     

Composite adaptive anti-disturbance control for MIMO nonlinearly parameterized systems with mismatched general periodic disturbances

In this paper, the problem of anti-disturbance control for a class of multi-input and multi-output (MIMO) nonlinearly parameterized systems with mismatched general periodic disturbances is investigated via a composite adaptive anti-disturbance control scheme. The composite adaptive anti-disturbance control method is presented by using disturbance observer technique, back-stepping method and adaptive control approach. A novel disturbance observer is designed to estimate the disturbances generated by a linear system with nonlinear output function. Rigorous stability analysis for the augmented closed-loop system is developed by direct Lyapunov stability theory. It is shown that the system outputs asymptotically converge to zero in the presence of mismatched general periodic disturbances. Finally, a simulation example is given to demonstrate the effectiveness of the proposed method.