一类不确定非线性系统的改进积分型滑模控制

针对一类不确定非线性系统的传统滑模控制,推导了滑模误差和稳态误差的范围．为了减小系统的稳态误差,同时防止积分饱和,设计了一种改进积分型滑模面．在边界层外,通过调节因子对积分项进行削弱,以防止在初始误差较大的条件下积分饱和引起的超调较大和调节时间较长的问题;在边界层内,采用传统积分以减小系统稳态误差．理论分析和仿真研究表明了所提改进积分型滑模控制方法的有效性．     

一类非线性系统准滑模控制的稳态误差分析

针对一类具有未知控制增益的不确定非线性系统准滑模跟踪控制,通过分析跟踪误差和滑模变量之间的关系,利用有界输入有界输出稳定的思想,分别推导了采用Slotine形式的传统滑模面和传统积分滑模面时系统的稳态跟踪误差的界.将其与现有的几种方法进行比较,该方法求得的稳态跟踪误差界更精确.根据给定的稳态跟踪误差要求,可设计出适合抑制抖振的饱和函数.通过仿真算例验证了所提出方法的有效性.     

一类不确定非线性系统的改进积分型滑模控制

针对一类不确定非线性系统的传统滑模控制,推导了滑模误差和稳态误差的范围．为了减小系统的稳态误差,同时防止积分饱和,设计了一种改进积分型滑模面．在边界层外,通过调节因子对积分项进行削弱,以防止在初始误差较大的条件下积分饱和引起的超调较大和调节时间较长的问题;在边界层内,采用传统积分以减小系统稳态误差．理论分析和仿真研究表明了所提改进积分型滑模控制方法的有效性．

     

采用幂次趋近律的滑模控制稳态误差界

对一类不确定非线性系统采用幂次趋近律的滑模跟踪控制,分别推导了采用Slotine形式的传统滑模面和积分滑模面时的稳态跟踪误差的界.首先,基于Lyapunov方法求出了滑模误差的最终界和系统不确定性、幂次趋近律参数之间定量的数学关系.其次,利用有界输入有界输出稳定的方法,分别求出了采用Slotine形式的传统滑模面和积分...     

一类非线性不确定系统的高阶积分自适应滑模控制

为有效改善传统积分滑模在一类非线性不确定系统的应用中存在的抖振问题,结合有限时间收敛理论、高阶积分滑模理论和自适应控制理论,提出了一种高阶积分自适应滑模控制方法;该方法通过选取有限时间收敛反馈量和设计高阶积分滑模面,不仅确保了系统状态误差在有限时间内的收敛性,而且还保证了系统具备对不确定性干扰的抑制能力;同时,当系统的不确定项的边界范围无法预先确定时,采用自适应方法对滑模控制的趋近速率进行估计;仿真结果表明所提方法能够有效抑制非线性不确定系统的抖动,并具有较高的控制精度.     

一类MIMO非线性系统的直接自适应模糊滑模控制

针对一类具有下三角形函数控制增益矩阵的非线性系统, 基于滑模控制原理, 并利用Ⅱ型模糊系统的逼近能力, 提出了一种直接自适应模糊滑模控制器设计的新方案. 通过引入积分型李雅普诺夫函数及逼近误差自适应补偿项, 证明了闭环系统是全局稳定的, 跟踪误差收敛到零. 仿真结果表明了该方法的有效性.     

电液位置伺服系统的多滑模神经网络控制

针对电液位置伺服系统存在的强非线性、控制增益未知和非匹配不确定性.通过引入神经网络和带饱和层的多滑模面,提出了一种多滑模神经网络控制方法.该方法运用神经网络的万能逼近特性和滑模控制优良的抗干扰特点,采用构造性方法设计控制器.运用光滑投影算法和积分李雅普诺夫技术,避免了参数漂移和控制器奇异问题.理论证明了系统跟踪误差收敛于任意设定的滑模面饱和层内.仿真实验表明了理论结果的有效性.     

双侧电驱动履带车辆运动解耦与变结构控制

针对双侧电驱动履带车辆运动控制强非线性、强耦合和不确定性的特点,提出一种解耦的控制结构,并设计各子系统控制器.首先,将运动控制系统分解为速度、横摆角速度两个独立子系统,克服传统差速控制存在的强耦合.其次,采用积分滑模控制方法,引入非线性积分滑模面,设计了能有效克服路面不确定扰动、消除积分饱和的速度控制器,实现车速的无超调、无静差的跟踪;考虑驱动电机饱和约束,结合模糊自适应与滑模控制算法,设计了能够适应转向阻力非线性变化的横摆角速度控制器,提高车辆转向运动控制的抗扰能力、降低控制量抖振.仿真结果表明,控制策略实现多种工况下车辆快速、准确的直线、转向运动控制.     

基于干扰观测器的非线性不确定系统自适应滑模控制

本文研究了一类基于非线性干扰观测器的多输入多输出非线性不确定系统的边界层自适应滑模控制方法并应用于近空间飞行器高精度姿态控制.考虑系统存在不确定性和外部干扰上界未知的情况,设计了基于干扰观测器的边界层自适应滑模控制器,以消除传统滑模控制中的"抖振"现象,使跟踪误差趋近于零.同时,利用李雅普洛夫方法严格证明了闭环系统的稳定性.最后将所研究的自适应滑模控制方法,应用于某近空间飞行器的姿态控制中,仿真结果表明在不确定性和外部干扰作用下能保证姿态控制的稳定性,对参数不确定具有较好的鲁棒性.     

非线性增益递归滑模动态面自适应NN控制

针对一类严反馈非线性不确定系统的跟踪控制问题,提出一种非线性增益递归滑模动态面 (Dynamic surface control, DSC)自适应控制方法. 通过设计一个新的非线性增益函数,并构造递归滑模动态面的控制策略和新的Lyapunov函数,同时利用神经网络在线逼近系统不确定项, 该方法有效解决了具有输入饱和约束条件下系统控制精度与动态品质间的矛盾,增强了控制器对其自身参数摄动的非脆弱性. 理论证明了闭环系统所有状态是半全局一致最终有界的,且跟踪误差可收敛至任意小.     

Adaptive integral backstepping sliding mode control for opto-electronic tracking system based on modified LuGre friction model

In order to improve the control accuracy and stability of opto-electronic tracking system fixed on reef or airport under friction and external disturbance conditions, adaptive integral backstepping sliding mode control approach with friction compensation is developed to achieve accurate and stable tracking for fast moving target. The nonlinear observer and slide mode controller based on modified LuGre model with friction compensation can effectively reduce the influence of nonlinear friction and disturbance of this servo system. The stability of the closed-loop system is guaranteed by Lyapunov theory. The steady-state error of the system is eliminated by integral action. The adaptive integral backstepping sliding mode controller and its performance are validated by a nonlinear modified LuGre dynamic model of the opto-electronic tracking system in simulation and practical experiments. The experiment results demonstrate that the proposed controller can effectively realise the accuracy and stability control of opto-electronic tracking system.     

Robust nonlinear generalised predictive control for a class of uncertain nonlinear systems via an integral sliding mode approach

In this paper, a robust nonlinear generalised predictive control (GPC) method is proposed by combining an integral sliding mode approach. The composite controller can guarantee zero steady-state error for a class of uncertain nonlinear systems in the presence of both matched and unmatched disturbances. Indeed, it is well known that the traditional GPC based on Taylor series expansion cannot completely reject unknown disturbance and achieve offset-free tracking performance. To deal with this problem, the existing approaches are enhanced by avoiding the use of the disturbance observer and modifying the gain function of the nonlinear integral sliding surface. This modified strategy appears to be more capable of achieving both the disturbance rejection and the nominal prescribed specifications for matched disturbance. Simulation results demonstrate the effectiveness of the proposed approach.     

空间三关节机器人模糊积分滑模控制

研究提高关节机器人轨迹跟踪控制的性能,由于关节机器人运动中产生振动,影响系统的稳定性能。为解决上述问题,提出了一种反馈线性化的自适应模糊积分滑模控制方法。在上述方法的基础上,对机器人非线性动力学模型反馈线性化。为了进一步提高滑模控制的精度,设计了一种积分滑模面的滑模控制器,可以减弱积分滑模控制的抖振。通过设计一个模糊控制器,根据积分滑模面的大小自适应地调节积分滑模控制的切换部分,达到削弱抖振的目的。利用李亚普诺夫定理证明了控制系统的稳定性。仿真结果表明,改进方法有效地提高了关节机器人跟踪控制性能。     

Continuous Sliding Mode Controller with Disturbance Observer for Hypersonic Vehicles

In this paper, a continuous sliding mode controller with disturbance observer is proposed for the tracking control of hypersonic vehicles to suppress the chattering. The finite time disturbance observer is involved to make that the continuous sliding mode controller has the property of disturbance rejection. Due to continuous terms replacing the discontinuous term of traditional sliding mode control, switching modes of velocity and altitude firstly arrive at small regions with respect to disturbance observation errors. Switching modes keep zero and velocity and altitude asymptotically converge to their reference commands after disturbance observation errors disappear. Simulation results have proved the proposed method can guarantee the tracking of velocity and altitude with continuous sliding mode control laws, and also has the fast convergence rate and robustness.      

Nonlinear cascade control of an electro-hydraulic actuator with large payload variation

Electro-hydraulic actuators have been widely used in industrial production, but the unknown variable payload seriously affects its position control accuracy. Therefore, a radial basis function neural network disturbance observer is designed to estimate the lumped disturbance force through strong online learning ability in the absence of force sensor. Besides, a nonlinear cascade controller with double loop structure is proposed in this paper. A global fast terminal sliding mode control method is firstly applied in the outer loop position system, which can eliminate chattering and improve convergence speed comparing to traditional sliding mode control. The inner loop force system adopts a backstepping control method to calculate the actual input of the whole system. Theoretical analysis indicates that the proposed controller is stable even if existing time-variant disturbance. Moreover, three comparative controllers are designed and tested in both simulations and experiments. Comparative results show that the developed method has absolute average errors of 1.14 and 0.49 mm in different position tracking, which means more satisfactory tracking performance compared to the contrast controllers.     

Fast terminal sliding‐mode finite‐time tracking control with differential evolution optimization algorithm using integral chain differentiator in uncertain nonlinear systems

This paper presents a fast terminal sliding‐mode tracking control for a class of uncertain nonlinear systems with unknown parameters and system states combined with time‐varying disturbances. Fast terminal sliding‐mode finite‐time tracking systems based on differential evolution algorithms incorporate an integral chain differentiator (ICD) to feedback systems for the estimation of the unknown system states. The differential evolution optimization algorithm using ICD is also applied to a tracking controller, which provides unknown parametric estimation in the limitation of unknown system states for trajectory tracking. The ICD in the tracking systems strengthens the tracking controller robustness for the disturbances by filtering noises. As a powerful finite‐time control effort, the fast terminal sliding‐mode tracking control guarantees that all tracking errors rapidly converge to the origin. The effectiveness of the proposed approach is verified via simulations, and the results exhibit high‐precision output tracking performance in uncertain nonlinear systems.     

基于非线性参数的电液伺服系统滑模控制

针对在电液伺服系统跟踪控制中存在非线性不确定参数和外界扰动的问题,提出了一种基于积分微分器的滑模Lyapunov函数的控制方法。首先,在只有位移信号测量输出的情况下,采用高阶积分链式微分器对其速度和加速度信息进行预估。系统存在非线性不确定参数,利用微分器对状态和不确定项的实时估计,设计出积分滑模控制器,实现自适应规律以及对电液伺服系统中不确定扰动的抑制。搭建电液伺服系统AMESim模型并与Matlab构成联合仿真平台,对控制器进行仿真。仿真表明,该控制器具有良好的对非线性不确定参数变化的补偿能力和跟踪性能。     

一种新的自适应模糊滑模控制器设计方法

对一类非线性系统提出一种新的自适应模糊滑模控制器设计方法。将自适应模糊控制与滑模控制有效地结合在一起,先用滑模控制使跟踪误差进入边界层内,然后启动自适应模糊控制器。该控制器可消除滑模控制器中出现的抖振,并可在存在模糊逻辑系统逼近误差情况下使系统跟踪误差小于预先给定的任意常数。仿真算例验证了所提出方法的有效性。     

永磁球形电机的少保守性滑模控制

永磁球形电机轨迹跟踪控制方法常常利用高增益的控制输出来保证系统的鲁棒性及跟踪控制的快速性.但这种保守控制会带来较大的控制作用,甚至导致执行器饱和.为了减少控制的保守性,本文设计了一种带有非线性干扰观测器的模糊滑模控制器来解决球形电机的轨迹跟踪问题.利用干扰观测器对不确定性、摩擦、外界干扰、负载扰动等进行估计,并在控制输入端进行补偿实现对干扰的抑制.并利用滑模控制器抵消干扰观测器的干扰观测误差及不可观测部分的干扰,为了减少滑模的抖振,本文利用模糊逻辑对该部分进行逼近,并利用模糊的输出增益代替滑模的切换增益.此外通过Lyapunov方程证明了本文控制器的稳定性.仿真结果表明在存在模型不确定性及各种干扰的情况下,本文的轨迹跟踪控制具有良好的动静态性能和少保守性.     

带有非线性不确定奇异系统的积分滑模控制

针对一类含有非线性不确定的奇异系统, 提出了一种面向性能的鲁棒控制器. 控制器由3部分组成: 积分滑模控制、附加的非线性控制及复合非线性反馈控制. 积分滑模控制可将匹配不确定完全抵消并使系统轨迹进入理想滑模; 附加的非线性控制用来抑制理想滑动模态上非匹配不确定对系统稳定性和性能的影响; 复合非线性反馈控制则保证闭环系统输出按性能要求渐近地跟踪参考输入信号. 最后通过算例说明所提算法的有效性.