挖掘机器人伺服系统神经网络滑模控制

挖掘机器人伺服系统存在高度非线性、参数不确定和未建模动态等诸多不利因素,提出了一种结合径向基函数(RBF)神经网络的非线性滑模控制器,以提高控制精度和鲁棒性.首先,建立了单联伺服系统的数学模型;其次,采用RBF神经网络对系统的不利因素进行逼近,提出积分滑模面进一步减小稳态误差,同时减少对伺服系统参数的依赖,在此基础上,...     

交流伺服系统自适应模糊滑模控制

介绍了交流伺服系统的自适应模糊滑模控制方案.通过自适应模糊控制解决了扰动补偿问题.正是因为结合了模糊控制的逼近特性和滑模控制的鲁棒性,才使得系统对外部扰动具有很好的稳定性和鲁棒性,同时消除了抖动现象.仿真实验表明这一控制方案具有很好的控制效果.     

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。     

多关节机器人反馈线性化双模糊滑模控制

为了提高多关节机器人轨迹跟踪控制性能,提出了一种反馈线性化双模糊滑模控制方法。该方法在对机器人非线性动力学模型反馈线性化的基础上,设计了一种双模糊滑模控制器。通过设计一个模糊控制器,根据跟踪误差和误差变化率自适应地调整滑模面的斜率,从而加快响应速度。通过设计另一个模糊控制器,根据滑模面自适应地调整滑模控制的切换控制部分,从而减弱抖振。利用李亚普诺夫定理证明了控制系统的稳定性。针对空间三关节机器人进行了仿真实验,结果表明了所提方法的有效性。     

模拟转台伺服系统的自适应模糊滑模控制研究

利用Stribeck摩擦模型,将自适应控制与模糊滑模控制相结合,提出了自适应模糊滑模控制模型,对模拟转台伺服系统进行了控制。仿真结果表明,自适应模糊滑模控制器能有效抑制摩擦力矩的影响,实现高精度的位置跟踪,鲁棒性好,值得在其他非线性系统中推广使用。     

基于模型参考的主动空气悬架模糊自适应滑模控制

针对主动空气悬架这种时变、非线性复杂系统,以空气悬架客车1/4模型为控制对象,提出了模糊自适应滑模控制策略(FASMC),其中模糊自适应系统用来处理空气悬架系统的非线性和参数不确定性,并以最优控制的理想空气悬架作为参考模型。仿真试验表明,所提出的控制器能够有效降低车身振动幅度、提高车辆的可操纵性。     

并联机器人的智能模糊滑模控制算法

针对以交流伺服电机驱动的二自由度并联机器人,设计了智能模糊滑模控制算法.该方法先设计动态滑模面,使系统的任意初始状态一开始就在滑模面上,消除了滑模控制的到达运动阶段,使系统在响应的全过程都具有鲁棒性;然后设计一种智能模糊控制器,用模糊控制器的输出取代滑模控制切换项的输出.仿真结果表明,该控制方法不仅增强了全局抗干扰能力,而且有效地消除了系统的抖振现象.     

漂浮基姿态受控空间机器人关节运动的自适应模糊滑模控制

重点研究了载体位置无控、姿态受控情况下,空间机器人姿态、关节协调运动的自适应模糊滑模控制问题。由拉格朗丑第二类方法及系统动量守恒关系,建立了漂浮基空间机器人的系统动力学方程。以此为基础,针对空间机器人所有惯性参数均未知的情况,设计了空间机器人载体姿态与机械臂各关节协调运动的自适应模糊滑模控制方案。数值仿真的结果,证实了该控制方案的有效性。     

滑模模糊控制算法在液压机器人控制中的应用

Pb-211液压机器人腰部是一个非线性液压伺服控制系统，常规PID控制算法很难在不出现超调情况下满足控制系统快速性的要求。针对这种情况以及液压系统参数时变等特点，在常规滑模控制算法的基础上，引入模糊控制技术，采用滑模模糊控制策略进行控制器设计。仿真结果表明，滑模模糊控制算法能够在不出现超调情况下显著提高系统的响应速度，满足系统响应速度和控制精度的要求，而且对正弦干扰具有较强的鲁棒性。     

挖掘机的4自由度自适应模糊滑模控制

为实现挖掘机回转和工作装置的轨迹跟踪控制,建立挖掘机回转和工作装置的4自由度运动学和拉格朗日动力学方程.挖掘机工作装置具有明显的非线性和不确定性特征,并存在外部干扰,所以将滑模变结构理论用于其控制系统.针对滑模控制的抖振可能激活高频动态和破坏控制器部件的缺点,设计自适应模糊滑模控制器.控制规则包括3部分:等效控制、调整控制和切换控制.利用自适应模糊系统输出动态调节切换增益以逼近系统不确定性的上界,将滑模控制的切换项转化为连续的模糊输出,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.针对一个完整的挖掘卸料过程,将所设计的控制器用于仿真试验,给出自适应模糊滑模控制的跟踪性能及控制输入的效果.     

Composite fuzzy sliding mode control of nonlinear singularly perturbed systems

This paper deals with the robust asymptotic stabilization for a class of nonlinear singularly perturbed systems using the fuzzy sliding mode control technique. In the proposed approach the original system is decomposed into two subsystems as slow and fast models by the singularly perturbed method. The composite fuzzy sliding mode controller is designed for stabilizing the full order system by combining separately designed slow and fast fuzzy sliding mode controllers. The two-time scale design approach minimizes the effect of boundary layer system on the full order system. A stability analysis allows us to provide sufficient conditions for the asymptotic stability of the full order closed-loop system. The simulation results show improved system performance of the proposed controller as compared to existing methods. The experimentation results validate the effectiveness of the proposed controller.     

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。     

Nonlinear adaptive control based on fuzzy sliding mode technique and fuzzy-based compensator

It is difficult to efficiently control nonlinear systems in the presence of uncertainty and disturbance (UAD). One of the main reasons derives from the negative impact of the unknown features of UAD as well as the response delay of the control system on the accuracy rate in the real time of the control signal. In order to deal with this, we propose a new controller named CO-FSMC for a class of nonlinear control systems subjected to UAD, which is constituted of a fuzzy sliding mode controller (FSMC) and a fuzzy-based compensator (CO). Firstly, the FSMC and CO are designed independently, and then an adaptive fuzzy structure is discovered to combine them. Solutions for avoiding the singular cases of the fuzzy-based function approximation and reducing the calculating cost are proposed. Based on the solutions, fuzzy sliding mode technique, lumped disturbance observer and Lyapunov stability analysis, a closed-loop adaptive control law is formulated. Simulations along with a real application based on a semi-active train-car suspension are performed to fully evaluate the method. The obtained results reflected that vibration of the chassis mass is insensitive to UAD. Compared with the other fuzzy sliding mode control strategies, the CO-FSMC can provide the best control ability to reduce unwanted vibrations.     

基于模糊滑模控制的再生制动系统稳定性分析

针对电动汽车再生制动系统稳定性问题,将模糊滑模控制技术应用于再生制动过程的稳定性研究。分析了再生制动过程中3种制动模式之间的相互关联以及动态演化,并综合考虑车辆制动稳定性及制动能量回收率,提出了电机再生制动力和前后轮液压制动力协调控制的最大化制动力分配策略;以滑移率为控制目标,将模糊控制与变结构控制相结合,建立了基于电机再生制动的稳定性模糊滑模控制策略;依据实车参数,对控制策略模型进行了仿真分析。研究结果表明,模糊滑模控制实现了电动汽车制动模式的合理切换,并验证了控制策略的有效性。     

一类不确定非线性系统的自适应滑模控制

滑模变结构控制系统能够通过控制其本身结构的变化,使得系统性能保持一直高于一般固定结构控制所能达到的性能,突破了经典线性控制系统的品质限制,适用于非线性的不确定系统。同时滑模控制能保证在模型的不确定和外部扰动的情况下系统的稳定性与鲁棒性,而且以损失能导致抖振的最优控制性能而得到稳定鲁棒性,同时它的不确定性上界必须是已知的,但有时候很难得到上界。这样提出一种自适应的方法以进一步避免这些问题,同时这种方法能保证闭环系统的稳定性。本论文给出仿真结果来验证该方法的有效性。     

基于模糊滑模控制和两级滤波滑模观测器的PMSM改进控制策略

针对传统带有滑模观测器的永磁同步电机控制系统中转矩脉动大、抖振明显、反电动势估计精度差等问题,提出基于模糊滑模控制和两级滤波滑模观测器的PMSM改进控制策略.首先,在速度环提出基于双曲正弦函数的新型趋近率,结合模糊控制思想对趋近率参数实现自整定,设计了一种基于新型趋近率的模糊积分滑模速度环控制器,并且对新型趋近率的抖振抑制效果给出严格分析.其次,提出基于变截止频率低通滤波器和修正反电动势观测器的两级滤波结构,抑制反电动势中的高频分量和测量噪声,并对转子位置进行合理补偿,继而设计了两级滤波滑模观测器;通过Lyapunov判据对本文提出控制策略的稳定性进行了推导证明.仿真和实验结果表明,与传统滑模观测器相比,改进的控制器使电机在启动和受到外部扰动时系统响应良好,有效改善了转矩脉动、抖振、反电动势的估计精度等问题.     

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.     

Adaptive fuzzy sliding mode control for an automatic arc welding system

This paper describes an automatic welding control system developed for alternating current shielded metal arc welding (SMAW). This method could replace manual operations which require a well-trained technician. We have derived a mathematical model of the welding control system and identified the system’s parameters. The sliding surface is used as the input variable to reduce the number of fuzzy reasoning rules, in comparison with the conventional two-dimensional fuzzy logic control (FLC) algorithm. An adaptive fuzzy sliding mode controller (AFSMC) consists of an equivalent control part and a hitting control part. An adaptive law derived from a Lyapunov function is used to obtain the FLC’s parameters, and is applied to approximate the equivalent control part of the sliding mode control (SMC), so that the system states can be forced to zero. By using three-rules FLC, the control part that satisfies the hitting conditions of the SMC can force the system’s states to reach and remain on the sliding surface. Therefore, the stability of the AFSMC can be guaranteed and can be used to modulate the rate of the electrode feeding mechanism that regulates the arc current of the SMAW. The simulation and the experimental results both show that this automatic welding control system, based on the AFSMC, can perform effectively.     

Adaptive fuzzy sliding mode control for an automatic arc welding system

This paper describes an automatic welding control system developed for alternating current shielded metal arc welding (SMAW). This method could replace manual operations which require a well-trained technician. We have derived a mathematical model of the welding control system and identified the system’s parameters. The sliding surface is used as the input variable to reduce the number of fuzzy reasoning rules, in comparison with the conventional two-dimensional fuzzy logic control (FLC) algorithm. An adaptive fuzzy sliding mode controller (AFSMC) consists of an equivalent control part and a hitting control part. An adaptive law derived from a Lyapunov function is used to obtain the FLC’s parameters, and is applied to approximate the equivalent control part of the sliding mode control (SMC), so that the system states can be forced to zero. By using three-rules FLC, the control part that satisfies the hitting conditions of the SMC can force the system’s states to reach and remain on the sliding surface. Therefore, the stability of the AFSMC can be guaranteed and can be used to modulate the rate of the electrode feeding mechanism that regulates the arc current of the SMAW. The simulation and the experimental results both show that this automatic welding control system, based on the AFSMC, can perform effectively.     

基于交流伺服电机驱动的并联机器人动态滑模控制

并联机器人具有刚度大、承载能力强、误差小等特点,针对以交流伺服电机驱动的并联机器人机构--GPM-200并联机构,建立了控制系统模型,并在其工作空间中进行了轨迹规划,而后设计了一种动态滑模控制算法,在Matlab/Simulink上进行了仿真实验,结果表明:该算法鲁棒性好,且系统抗干扰能力强,对系统参数变化不敏感,具有良好的跟踪性能,实现了对该并联机器人的高精度实时控制.