电液位置伺服系统的模糊滑模控制研究

针对电液位置伺服系统的位置跟踪控制问题,在滑模控制理论的基础上,加入模糊控制理论,提出了一种模糊自学习滑模控制方案.通过设计模糊控制器,用模糊输出代替滑模切换控制,将该控制方法应用于电液位置伺服系统的研究中,仿真实验结果表明该控制方案的有效性,跟踪性能良好,能有效削弱抖振.     

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。     

非完整移动机械臂的自适应模糊滑模控制研究

针对四轮二连杆非完整移动机械臂的轨迹跟踪问题,设计了一种结合自适应模糊控制和滑模控制的控制策略。首先建立了系统包含未知动力学模型不确定性和外部扰动的动力学控制模型,然后基于反演技术设计了控制器;采用了模糊控制来逼近系统未知时变总体不确定性,并采用了自适应机制动态优化模糊系统控制参数,进一步采用了指数趋近律滑模控制消除模糊逼近误差的影响。研究结果表明:该控制器对系统总体不确定性进行了有效补偿,保证了移动机械臂在复杂不确定环境下的良好轨迹跟踪性能。     

装载机工作装置轨迹的自适应模糊滑模控制

为实现装载机工作装置的轨迹跟踪控制,建立装载机工作装置的二自由度运动学和拉格朗日动力学方程。装载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,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,将模糊控制的切换项转化为连续的模糊系统,增强了控制系统对装载机工作装置的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。设计过程采用了方法,保证了控制系统的稳定与收敛,仿真结果给出了自适应模糊滑模控制的跟踪性能及误差。     

差速驱动AGV建模和轨迹跟踪控制研究

针对应用于工厂物料运输的差速驱动AGV,在实际工作中轨迹跟踪控制将会受外界干扰等因素的影响,提出了一种自适应模糊滑模轨迹跟踪控制律.首先建立了差速驱动AGV的数学模型;然后针对AGV运动学模型设计了Backstep-ping方法控制律,得到虚拟控制速度;针对其动力学模型设计了以力矩为控制输入的自适应模糊滑模控制律,使得其能够对虚拟速度进行跟踪,其中利用模糊系统的万能逼近特性,逼近滑模控制器的切换部分来避免滑模控制的抖振现象;采用Lyapunov稳定性理论分析证明了控制系统的稳定性.最后仿真试验表明了所设计的控制律能有效的跟踪参考轨迹.     

直驱泵控电液位置伺服系统模糊滑模控制仿真与实验研究

针对直驱泵控电液位置伺服系统采用普通滑模控制存在高频抖振现象以及跟踪控制性能欠佳的问题,在普通滑模控制的基础上引入模糊控制量来柔化控制信号,从而削弱滑模切换时产生的剧烈抖振,提高电液位置伺服系统控制精度和稳定性。设计了比例切换模糊滑模控制器,实现了利用模糊控制输出项柔化滑模切换控制。采用滑模控制和模糊滑模控制对单位阶跃响应和余弦跟踪特性进行了仿真与实验研究。结果表明:模糊滑模控制能显著提高直驱泵控系统的动态响应速度和稳态控制精度,增强系统的鲁棒性,削弱普通滑模控制存在的高频抖振现象。     

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。     

不确定机械系统的二阶逼近模糊滑模控制

针对不确定机械系统,利用模糊逻辑系统的万能逼近特性对未知非线性函数建模,以便设计控制方法。基于一阶逼近精度的模糊逻辑系统需要足够多的模糊规则才能保证一定的逼近精度,然而规则数的增多必然导致计算量的增大,不利于实时控制。本文中设计了具有二阶逼近精度的模糊逻辑系统对机械系统中的非线性未知部分进行实时逼近,并结合鲁棒性能好的滑模控制对不确定机械系统进行轨迹跟踪控制。从仿真实验证明,具有二阶逼近精度的模糊系统可以以很少的规则高精度的逼近任意非线性函数,并以此为基础构成的模糊滑模控制器不仅可以达到所希望的控制精度,比起规则数量多得多的模糊滑模控制,甚至位置误差和速度误差更小,跟踪速度更快。故采用特殊隶属函数所设计的自适应模糊逻辑系统,解决了逼近精度和模糊规则数量之间的矛盾,为机械系统的高精度的实时控制提供了保证。     

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。     

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.     

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.     

欠驱动桥式起重机自适应模糊滑模抗摆控制

针对不确定欠驱动桥式起重机负载抗摆控制问题,提出一种模糊滑模控制方法。首先将整个系统分成几个不同的子系统,分别设计子系统的滑模面;然后从一级滑模面构造二级滑模面。基于模糊逻辑和自适应率分别逼近未知非线性函数和估计干扰上边界,李亚普诺夫稳定理论和滑模控制确保欠驱动系统鲁棒稳定性,桥式起重机系统的仿真结果验证了该方法的有效性。     

基于快速终端滑模算法的机械手跟踪控制研究

提出了一种模糊自适应快速终端滑模控制方法。该控制方法采用多幂次趋近律构造趋近运动,用以提高趋近滑模面的速度,然后对常规的终端滑模面进行改进,提高沿滑模面收敛的速度。为消除控制系统中存在的不确定因素和建模误差,该控制算法还引进模糊自适应方法进行在线逼近。利用李雅普诺夫定理证明了所提出算法的稳定性。最后基于MATLAB与ADAMS联合仿真平台,采用所提出的算法对自行设计的3R型机械手进行轨迹跟踪研究,仿真结果显示,本控制方法具有更快的收敛性和更强的鲁棒性,有效地抑制了滑模控制中存在的振荡。     

Implementation of a ball inverted pendulum with omnidirectional moving ability using a robust fuzzy control strategy

A robust fuzzy controller (RFC) is proposed for a ball inverted pendulum (BIP) system control problem. A Mamdani-type fuzzy controller and a compensated control technique are combined in the proposed control system. This controller is used for real-world control of a BIP with unknown system uncertainties. Using this method, the approximation error caused by the trial-and-error fuzzy control design procedure is minimized. Moreover, the decoupled technique provides a simple method for achieving asymptotic stability control for angle and position of a BIP control system. The concept of this approach is to decouple the entire system into two subsystems. Next, the primary subsystem combines the information provided by the secondary subsystem. And then a control force is generated to drive both subsystems toward their targets, respectively. Thus, the platform can move to any position without constraints. The stability of RFC, which is based on the Lyapunov stability theorem, is guaranteed. Furthermore, to verify the effectiveness of the control algorithm, several numerical simulations and dynamic simulation in the automatic dynamic analysis of mechanical systems (ADAMS) environment with MATLAB are implemented. Finally, the efficiency of the RFC is verified with real-time implementation of the BIP.     

Model reference self-learning fuzzy control method for automated mechanical clutch

Automated mechanical clutch is a critical component in vehicle powertrain, whose operations have great influence on fuel economy, comfort, and drivability. However, the control of clutch is a challenging problem due to the nonlinearities and uncertainties, which has attracted extensive attention. This paper proposed a model reference self-learning fuzzy control method with considering clutch wear. Fuzzy control is a simple but effective method to deal with the nonlinear system, but the determined fuzzy rules cannot be suitable for system variations due to clutch wear. Therefore, a self-learning algorithm based on referent model is introduced into fuzzy controller. Then, simulations are carried out in MATLAB/SIMULINK, and the results show that the method solves the problem of clutch wear effectively compared with the fuzzy control without self-learning ability. Finally, a test bench is designed and experiments are carried out to verify the validity of the proposed method.     

Fault tolerant synchronization of chaotic heavy symmetric gyroscope systems versus external disturbances via Lyapunov rule-based fuzzy control

In this paper, fault tolerant synchronization of chaotic gyroscope systems versus external disturbances via Lyapunov rule-based fuzzy control is investigated. Taking the general nature of faults in the slave system into account, a new synchronization scheme, namely, fault tolerant synchronization, is proposed, by which the synchronization can be achieved no matter whether the faults and disturbances occur or not. By making use of a slave observer and a Lyapunov rule-based fuzzy control, fault tolerant synchronization can be achieved. Two techniques are considered as control methods: classic Lyapunov-based control and Lyapunov rule-based fuzzy control. On the basis of Lyapunov stability theory and fuzzy rules, the nonlinear controller and some generic sufficient conditions for global asymptotic synchronization are obtained. The fuzzy rules are directly constructed subject to a common Lyapunov function such that the error dynamics of two identical chaotic motions of symmetric gyros satisfy stability in the Lyapunov sense. Two proposed methods are compared. The Lyapunov rule-based fuzzy control can compensate for the actuator faults and disturbances occurring in the slave system. Numerical simulation results demonstrate the validity and feasibility of the proposed method for fault tolerant synchronization.     

Research on the effects of coordinate deformation on radial-axial ring rolling process by FE simulation based on in-process control

The boundary layer approach is the most popular method to reduce the chattering phenomenon in sliding mode control (SMC) for uncertain nonlinear systems. This paper applies the fuzzy sliding mode structure based on the boundary layer theory which is used as speed controller of an indirect field-oriented control (IFOC) of an induction motor (IM) drive. A fuzzy inference system is assigned for reaching the controller part of the fuzzy sliding mode controller (FSMC) to eliminate the chattering phenomenon in spite of the small and large uncertainties in the system. The applied fuzzy system acts like a saturation function technique in a thin boundary layer near the sliding surface so that the stability of the system is guaranteed. Also, the equivalent control part is estimated to avoid the computational burden by an averaging filter. On the other hand, the averaging filter assists to improve the tracking performance despite the possibility of large uncertainties in the system so that the stability of the system is guaranteed. The main advantages of the proposed chattering-free speed controller are robustness to parameter variations and external load disturbance. The simulation results are shown to verify the effectiveness of the proposed speed controller, and its advantages are shown in comparison with the FSMC system and the conventional SMC.     

输入受限的非完整移动机器人的自适应模糊控制

提出了一种非完整移动机器人饱和自适应模糊轨迹跟踪控制方法,该方法基于反演技术分别设计了系统的运动学控制器和动力学控制器。运动学控制器通过引入分流控制技术解决了初始速度跳变引起的控制量突变问题,动力学控制器利用饱和函数和受限控制参数实现了其有界力矩控制。自适应模糊控制器将模糊逻辑系统与自适应方法相结合,有效消除了常规方法难以解决的系统未知不确定性对系统的影响。通过Lyapunov直接法证明了该系统是收敛且渐进稳定的。仿真结果验证了所设计控制器的良好控制性能和强鲁棒性。     

模糊自适应预测控制在航空发动机中的应用研究

对于航空发动机这样复杂的系统,其数学模型具有较大的不确定性,而模糊控制对于解决模型不确定性问题具有较好的优势,运用模糊控制理论就具有较好的实践意义。而且,航空发动机在实际运行中存在诸多可测与不可测的扰动,将模糊建模技术与预测控制算法相结合,采用输出误差反馈启发校正的方法,有效地降低了系统设计与实现的复杂性,提高了系统的实时性,并使得该算法的模糊预测控制在鲁棒性、动态性能等方面皆优于常规PID控制。最后,通过数字仿真,对比了经典PID控制和运用模糊自适应预测控制。仿真结果表明,文中所采用的方法有较好的效果,其证明了该方法在航空发动机控制中应用的可能性。     

A novel sliding-mode control of induction motor using space vector modulation technique

This paper presents a novel sliding-mode control method for torque control of induction motors. The control principle is based on sliding-mode control combined with space vector modulation technique. The sliding-mode control contributes to the robustness of induction motor drives, and the space vector modulation improves the torque, flux, and current steady-state performance by reducing the ripple. The Lyapunov direct method is used to ensure the reaching and sustaining of sliding mode and stability of the control system. The performance of the proposed system is compared with those of conventional sliding-mode controller and classical PI controller. Finally, computer simulation results show that the proposed control scheme provides robust dynamic characteristics with low torque ripple.