永磁同步电机的模糊滑模控制

为了实现高性能永磁同步电动机伺服系统快速而精确的位置跟踪控制,在滑模控制策略中引入模糊控制算法,设计了基于模糊规则的滑模控制器;并通过理论分析和控制仿真,证实了模糊滑模控制很好地解决了抖振问题,对参数变化和负载扰动具有很好的鲁棒性,永磁同步电机可获得很好的位置跟踪效果。     

车辆主动悬架自适应模糊滑模控制研究

针对主动悬架系统具有的非线性和不确定性,结合滑模控制的鲁棒性和模糊控制的优势,建立自适应模糊滑模控制策略。确定滑模切换面参数,应用切换控制方法和函数逼近技术改善滑模运动的动态品质,并利用模糊语言达到控制悬架振动的效果。以车辆1/4主动悬架动力学模型为对象进行仿真,结果显示,与传统的模糊控制相比,自适应模糊滑模控制能有效地改善路面变化对悬架的影响。     

基于扰动观测器的永磁同步电机电流环自适应滑模控制

针对扰动对永磁同步电机转速伺服系统性能的影响,提出了基于扰动观测器的电流环自适应滑模控制方法。设计了自适应律在线估计系统的内部参数摄动以补偿模型不确定性扰动。同时,设计了滑模扰动观测器实时估计系统外部负载扰动,并将观测值前馈补偿到电流环自适应滑模控制器,在提高系统鲁棒性的同时降低滑模控制系统的抖振。实验结果显示,采用基于扰动观测器的电流环自适应滑模控制方法,系统可快速、准确、无超调地跟踪900r/min的速度指令,调节时间为0.08s,稳态误差为±5r/min。加入0.6N·m的负载扰动,该控制方法的最大转速波动为21r/min,比PI控制方法的转速波动减小了3.4%。仿真和实验结果表明,基于扰动观测器的电流环自适应控制方法提高了永磁同步电机转速伺服系统的鲁棒性和动态响应性能,同时可有效抑制滑模控制系统的抖振。     

转台伺服系统的自适应模糊滑模逼近控制

在传统的转台伺服系统中加进了自适应模糊滑逼近模控制器。解决了传统的转台伺服控制方法易随电机参数变化而变化,抗负载扰动性能差,鲁棒性弱的缺点。自适应模糊滑模控制器作为一种非连续性控制,最大优点便是其滑动模态对加给系统的干扰具有完全的自适应性。系统再利用积分滑模面设计切换函数且将其模糊化,然后采用自适应模糊逼近方法,实现了对线性系统和非线性系统的高精度控制。仿真结果表明,自适应模糊滑模逼近控制不但具有良好的鲁棒性、较快的响应速度,而且在相似的控制效果下,可以极大的削弱滑模控制固有的抖振现象。     

大型装备电液系统高精度鲁棒位置控制

阀控非对称缸电液系统具有参数不确定性和强外部扰动,导致系统鲁棒性和跟踪性能变差,控制难度增加.考虑外部扰动建立系统动态模型,为了提高系统鲁棒性和跟踪精度,提出自适应滑模控制策略,用滑模边界层厚度函数代替符号函数以减小系统颤振,构建扰动观测器来调整切换增益,进一步提高系统稳定性.引入可变边界层厚度函数,抑制变化负载对系统...     

直接型模糊自适应滑模控制在智能减振结构中的应用

在智能减振结构中,需要控制器有很好的鲁棒性,以保证在结构参数发生变化的情况下仍可以获得理想的控制结果。简单模糊逻辑控制在系统结构参数变化比较大的情况下,其鲁棒性能比较差。引入滑模控制的思想,把基本控制量分为等效控制量和开关控制量,并同时用两个模糊逻辑进行近似逼近,自适应率的设计保证了系统的稳定性,从而建立了直接型模糊自适应滑模控制。通过和简单模糊控制的控制结果比较,验证了直接型模糊自适应滑模控制在智能减振系统中的有效性。     

一类不确定非线性系统的自适应模糊控制

自适应模糊控制理论是模糊控制理论与自适应控制理论相互交叉、相互渗透而形成的一个研究领域.针对一类带有扰动的SISO不确定非线性系统,本文提出了一种综合型自适应模糊控制方案.该方案充分利用了被控对象信息和模糊控制规则,保证了闭环系统的稳定性和跟踪误差的收敛性,仿真结果表明本方法比单纯的直接型或间接型模糊控制方法具有更好的跟踪性能.     

液压挖掘机器人的力与位置混合控制系统的研究

利用模糊滑模控制理论和混合控制理论设计了力和位置混合控制器,它在对液压缸的驱动力进行控制的同时,又对液压活塞杆的位置进行跟踪控制。仿真试验表明,模糊滑模控制器既具有滑模控制鲁棒性好和响应速度快的特点,又利用模糊控制有效地削弱了普通滑模控制的抖振现象,能够很好地满足挖掘机器人运动系统的要求。     

直接驱动数控转台自适应二阶滑模控制

针对直接驱动数控转台用环形永磁力矩电动机易受负载扰动及自身参数变化影响的特点,设计了自适应二阶滑模控制器。控制律采用自适应螺旋算法,二阶滑模将不连续控制作用于变量的高阶微分上,削弱了抖振现象。引入自适应控制是对螺旋算法中的控制增益进行动态调节,从而克服了控制增益需要不确定性的界来确定的局限,进而提高了控制性能。仿真结果表明该策略具有较强的位置定位能力,对负载扰动和参数变化等不确定性具有很强的鲁棒性,同时有效地削弱了抖振现象。     

计入摩擦的进给伺服系统自适应滑模控制方法研究

针对具有非线性摩擦和有界外部扰动的进给伺服系统,设计了一种自适应滑模控制器。该控制器采用自适应算法建立了摩擦力的线性边界,将其作为滑模控制项增益,利用滑模控制项补偿摩擦和外部扰动,使系统跟踪误差渐进收敛于要求的允差内。基于Lyapunov稳定性理论证明了闭环控制系统的全局稳定性。仿真结果表明该控制器能有效补偿摩擦和外部扰动,相对于传统的PD和PID控制,显著提高了进给伺服系统的跟踪精度,并对系统参数和摩擦的不确定性具有一定的鲁棒性。     

Adaptive backstepping sliding mode control with fuzzy monitoring strategy for a kind of mechanical system

A novel adaptive backstepping sliding mode control (ABSMC) law with fuzzy monitoring strategy is proposed for the tracking-control of a kind of nonlinear mechanical system. The proposed ABSMC scheme combining the sliding mode control and backstepping technique ensure that the occurrence of the sliding motion in finite-time and the trajectory of tracking-error converge to equilibrium point. To obtain a better perturbation rejection property, an adaptive control law is employed to compensate the lumped perturbation. Furthermore, we introduce fuzzy monitoring strategy to improve adaptive capacity and soften the control signal. The convergence and stability of the proposed control scheme are proved by using Lyaponov′s method. Finally, numerical simulations demonstrate the effectiveness of the proposed control scheme.     

A novel adaptive sliding mode control with application to MEMS gyroscope

This paper presents a new adaptive sliding mode controller for MEMS gyroscope; an adaptive tracking controller with a proportional and integral sliding surface is proposed. The adaptive sliding mode control algorithm can estimate the angular velocity and the damping and stiffness coefficients in real time. A proportional and integral sliding surface, instead of a conventional sliding surface is adopted. An adaptive sliding mode controller that incorporates both matched and unmatched uncertainties and disturbances is derived and the stability of the closed-loop system is established. The numerical simulation is presented to verify the effectiveness of the proposed control scheme. It is shown that the proposed adaptive sliding mode control scheme offers several advantages such as the consistent estimation of gyroscope parameters including angular velocity and large robustness to parameter variations and external disturbances.     

防抱制动系统参数自适应滑模变结构控制器的研究

首先针对具有参数不确定性的二阶非线性系统提出了自适应滑模变结构的控制算法 ,该算法的基本思想是用自适应策略来估计不确定系统的参数 ,根据估计出的参数值 ,来设计滑模控制器 ,优点是无须事先已知不确定参数的边界 ,并且由于在自适应变结构控制采用了消颤措施 (增加了消颤项 ) ,能削弱常规滑模控制所引起的颤振现象 ,也能提高单纯的自适应控制的鲁棒性能。而后将这一控制策略应用于防抱死制动系统 (ABS)的研究中 ,设计了防抱死制动系统的自适应滑模变结构控制器 ,通过计算机仿真 ,验证了该控制方案在 ABS应用中的可行性和有效性     

挖掘机器人的模型与自适应模糊滑模控制

为实现挖掘机器人的自动挖掘,在挖掘机器人的轨迹规划器给出铲斗期望运动轨迹的情况下,需要挖掘机器人的控制系统能够控制其工作装置实现对给定轨迹的准确跟踪.利用拉格朗日方法建立了挖掘机器人工作装置的三自由度动力学方程,设计了自适应模糊滑模变结构控制器.利用模糊控制动态调节切换增益,将滑模控制的切换项转化为连续的模糊系统,增强了控制系统对挖掘机器人工作装置不确定性和外界干扰的鲁棒性,削弱了滑模控制的抖振现象,并且有较强的自适应跟踪能力.利用MATLAB7.4/Simulink工具箱对所设计的控制器进行了仿真,给出了自适应模糊滑模控制的跟踪性能及误差.     

Robust adaptive control for a MEMS vibratory gyroscope

This paper presents an adaptive sliding mode controller for a microelectromechanical systems (MEMS) vibratory z-axis gyroscope. The proposed adaptive sliding mode controller can real-time estimate the angular velocity and the damping and stiffness coefficients. The stability of the closed-loop system can be guaranteed with the proposed adaptive sliding mode control strategy. The numerical simulation for MEMS gyroscope is investigated to show the effectiveness of the proposed control scheme. It is shown that the proposed adaptive sliding mode control scheme offers several advantages such as real-time estimation of gyroscope parameters and large robustness to parameter variations and external disturbance.     

Adaptive super-twisting sliding mode observer based robust backstepping sensorless speed control for IPMSM

This paper proposes a higher-order sliding mode observer based robust backstepping control to realize high-performance sensorless speed regulation for the interior permanent magnet synchronous motor (IPMSM). A new robust adaptive super-twisting higher-order sliding mode based observer is proposed to estimate the rotor position. The proposed observer has advantages of sliding chattering reduction and robustness against uncertainties. And, a new robust integral adaptive backstepping control with sliding mode actions is designed to achieve precise speed regulation. The uncertainties with unknown bounds can be stabilized by the sliding mode actions. And both transient and steady performance can be achieved by using the sliding mode and integral actions simultaneously. Then, a sensorless scheme is put forward to by combining the presented observer and the proposed controller. The stability of the observer and controller are verified. Simulation and experiment results validate the proposed approach.     

基于自适应模糊的旋转弹反演滑模控制律设计

针对旋转弹药模型具有非线性、强耦合和参数不确定性等特点,建立了考虑不确定因素的非线性控制模型,提出一种基于自适应反演和滑模控制理论的旋转弹体姿态控制律。基于Lyapunov稳定性理论,利用反演控制和滑模变结构理论取虚拟控制量作为滑动模态,设计了姿态控制器;基于模糊控制方法较强的逼近能力,引入自适应模糊控制实现对不确定参数的估计,同时通过对切换增益的模糊逼近解决了滑模面的抖振问题。仿真结果表明,所设计的控制律具有较好的稳定性和鲁棒性,该控制模型和控制器的设计合理可行。     

Adaptive fuzzy sliding mode control for a robotic aircraft flexible tooling system

A robotic aircraft flexible tooling system is proposed in this paper, of which high-precision synchronous motion control of dual robots is a key part. In order to alleviate the effects of the mechanical coupling over synchronous and tracking errors of the two robots, a cross-coupling scheme based on an adaptive fuzzy sliding mode controller (AFSMC) is developed. First, the mechanical coupling model is established by dynamics analysis of the dual-robot driving system. Then, a novel cross-coupling error is proposed, which combines both the position and speed tracking and synchronous errors of dual robots. Moreover, the cross-coupling control scheme based on AFSMC is presented. For the proposed AFSMC, a fuzzy logic controller is adopted to generate the hitting control signal, and the output gain of the sliding mode control is tuned online by a supervisory fuzzy system. Finally, the preferable performance of the proposed AFSMC cross-coupling approach is verified by the simulation results compared with the conventional proportional-integral-derivative control and SMC cross-coupling controls.