4-SPS(PS)并联机构模糊自适应滑模控制系统设计

针对并联机构传统控制方式轨迹跟踪精度误差较大的缺陷,提出了一种基于4-SPS(PS)并联机构的动力学方程和模糊自适应(Fuzzy-Adaptive SMC)滑模控制器的控制系统。首先,基于螺旋理论及反螺旋理论,设计了一种4-SPS(PS)并联机构,并采用微运动法(Micro-Motion Method)对机构的运动学方程进行了探讨。其次,基于机构的动力学方程,结合模糊自适应算法,设计了一种新型滑模控制器(SMC),模糊自适应算法的作用是实时地修正系统的不确定和非线性项参数,有效抑制了SMC系统的抖振现象。最后,建立了机构的系统仿真框图和实验平台,分别对机构进行仿真分析和实验研究。结果表明:模糊自适应滑模变结构控制器的轨迹跟踪精度高,鲁棒性强,稳态误差小,从而验证了该新型SMC控制器的有效性。     

基于干扰误差补偿的自动化电机自适应滑模反演控制

针对自动化电机受电磁干扰误差较大,导致电机控制效果较差、难以反映真实运行状态的问题,提出基于干扰误差补偿的自动化电机自适应滑模反演控制方法。构建电机的转子动力学模型,设计干扰观测器,将干扰预测输出值传输至增益调整模块,构建非线性干扰预测动态方程,将预测的干扰因素转化为相应控制量。电机的连续控制问题即跟踪控制问题,按照滑模反演控制理论,定义电机的两个子误差,引入滑模切换函数,构建转子动力学惯性逆矩阵获取控制力矩,通过跟踪转子输出轴完成电机自适应滑模反演控制。实验结果表明,所提方法能够较好地跟踪实际干扰信号变化轨迹,对自动化电机的控制性能较好。     

基于T-S模糊系统的漂浮基空间机器人关节协调运动的分散自适应滑模控制

针对载体位置和姿态均不受控的漂浮基空间机器人系统动力学方程难以预知的情况,提出了一种基于模糊逻辑系统的分散自适应滑模控制方案。利用第二类拉格朗日方法建立了空间机器人系统动力学方程。针对空间机器人的每一个自由度,将其动力学描述为分散交联子系统的集合。使用T-S模糊逻辑系统逼近子系统未知的动力学模型,然后设计自适应滑模控制器消除交联项和模糊逼近误差对轨迹跟踪性能的影响,并用Lyapunov理论证明控制器的稳定性。这种控制方法不需要预知系统动力学方程。数值仿真结果证实了该分散控制器的可靠性和有效性。     

平面2自由度并联机器人的解耦控制和仿真分析

以平面2自由度并联机器人为研究对象,推导其运动学模型,在运动学模型的基础上结合欧拉-拉格朗日动力学方程推导其动力学模型,根据得到的动力学模型引入计算力矩解耦控制方法,并证明该方法在理想估计与非理想估计下,对应的李雅普诺夫函数是全局渐进稳定的,从而得到解耦控制率方程,根据控制率方程和机器人的实际结构参数搭建Simulink仿真模型,进行运动控制仿真,仿真方法有:基于传统PD控制器的计算力矩解耦控制仿真方法和基于自适应模糊控制器的计算力矩解耦控制仿真方法,仿真输出机器人跟踪给定运动轨迹的效果图和误差图。仿真结果表明,无论是在理想或非理想状态下,计算力矩解耦控制方法确实可以使控制系统趋于稳定,且跟踪误差小,通过比较可知,基于自适应模糊控制器的计算力矩解耦控制方法的效果更佳。     

柔性关节机械臂的非线性控制策略研究

针对外部干扰情况下的柔性关节机械臂非线性动力学模型,提出一种基于反演设计思想的递阶控制策略。把电机的输出角度向量作为关节子系统的控制变量,设计虚拟电机角度向量实现关节轨迹跟踪,同时在反演正定函数中综合积分项消除轨迹跟踪误差。计算实际的关节电机输出力矩,使电机输出角度跟踪虚拟控制量,通过设计自适应滑模变结构控制器消除系统不确定因素的影响。基于李雅普络夫稳定性理论证明系统的稳定性和轨迹跟踪误差的收敛性。     

柔性关节机械臂的非线性控制策略研究

针对外部干扰情况下的柔性关节机械臂非线性动力学模型,提出一种基于反演设计思想的递阶控制策略。把电机的输出角度向量作为关节子系统的控制变量,设计虚拟电机角度向量实现关节轨迹跟踪,同时在反演正定函数中综合积分项消除轨迹跟踪误差。计算实际的关节电机输出力矩,使电机输出角度跟踪虚拟控制量,通过设计自适应滑模变结构控制器消除系统不确定因素的影响。基于李雅普络夫稳定性理论证明系统的稳定性和轨迹跟踪误差的收敛性。     

迭代学习在工业机械手自适应控制中的应用

针对机器人运动控制模型中存在的未知项建模误差,提出了基于迭代学习与滑模控制的机器人组合自适应控制方法.将机器人动力学方程以状态回归量的形式表示,使时变参数与物理参数分离,通过设计的参数自适应律,实现了对未知参数的在线估计.将跟踪误差限制在滑模面上,实现了对目标轨迹的有效跟踪.仿真实例表明,提出的组合控制算法在机器人轨迹跟踪中具有一定的可行性.     

下肢康复机器人模糊增益自适应调整的滑模阻抗控制

为了实现下肢康复机器人在康复训练过程中主动模式下的控制,在分析了人机交互作用力与动力学模型的基础上,提出了一种模糊增益自适应调整的滑模阻抗控制。该控制方法,通过阻抗控制器修正期望的下肢运动轨迹,得到新的关节运动轨迹,将新的关节轨迹与实际的关节轨迹误差转化为滑模函数,通过模糊化,将自适应力矩作用于下肢康复机器人。该控制方法减轻了滑模控制中的抖振现象,使其达到期望的力矩控制效果,实现了主动模式下的的柔顺性。     

变论域模糊补偿的机械臂积分终端滑模控制

为了减小机械臂在环境扰动、参数漂移和建模误差等影响下的轨迹跟踪误差,设计了基于积分终端滑模和变论域模糊补偿的组合控制器。采用拉格朗日方程建立了机械臂系统的动力学模型,制定了不确定因素影响下机械臂跟踪控制方案;设计的积分终端滑模控制器可以将系统初始状态限制在滑模面上,消除了控制过程的抖振并提高了跟踪速度;提出了自适应论域策略,该策略可以提高补偿力矩的输出细粒度,并将变论域模糊算法用于不确定因素补偿。经实验验证,变论域模糊补偿控制对关节1角位置的最大跟踪误差为0.103 rad,误差绝对均值为0.025 rad,对关节2角位置的最大跟踪误差为0.073 rad,误差绝对均值为0.012 rad,跟踪控制精度高于模糊补偿控制、RBF-BP控制和自适应鲁棒控制,验证了变论域模糊补偿控制方法的有效性和先进性。     

3-SPS(RPR)并联机构神经网络自适应滑模控制系统研究

通过Sim Mechanics Link插件关联Solidworks与Matlab软件,将3-SPS(RPR)并联机构的Solidworks三维模型转换为Matlab/Sim Mechanics仿真分析模型。基于机构的Sim Mechanics模型和动力学方程,结合神经网络自适应算法,设计了一种新型滑模控制器,并通过Lyapunov函数证明了该控制器的稳定性。神经网络自适应算法的作用是实时地修正系统的不确定和非线性项参数,有效解决了滑模控制系统的抖振问题。建立机构的Matlab/Simulink系统框图并进行仿真分析,结果表明:新型滑模控制器的轨迹跟踪精度比传统滑模控制器的高,且响应速度快,鲁棒性强,从而验证了新型滑模控制器的有效性。     

Adaptive sliding mode disturbance rejection control with prescribed performance for robotic manipulators

This study proposes an adaptive sliding mode disturbance rejection control with prescribed performance for robotic manipulators. A transformation with respect to tracking error using certain performance functions is used to ensure the transient and steady-state performances of the trajectory tracking control for robotic manipulators. Using the transformed error, a nonsingular terminal sliding mode surface is proposed. A continuous terminal sliding mode control (SMC) is presented to stabilize the system. To compensate for the uncertainty and external disturbance, a novel sliding mode disturbance observer is proposed. Considering the unknown boundary of the derivative of a lumped disturbance, an adaptive law based on the idea of equivalent control is designed. Combining the adaptive law, continuous nonsingular terminal SMC, and sliding mode disturbance observer, the adaptive sliding mode disturbance rejection control with prescribed performance is developed. Simulations are carried out to demonstrate the effectiveness of the proposed approach.     

船用天然气发动机电子节气门自适应高阶滑模控制

针对船用天然气发动机电子节气门非线性控制问题以及高阶滑模控制存在的边界难以估计问题,提出了一种基于高阶 滑模理论的节气门自适应控制算法,设计了基于系统相平面轨迹收敛过程的自适应策略,为了增加控制算法的实用性,在自适 应策略的基础上设计了检测区域,通过判断系统状态与该区域的相对位置双向调节控制增益,以防止增益过大而导致控制精度 降低、控制能量浪费的问题;同时,采用鲁棒微分估计器,对不可观测量进行估计;最后,设计 3 种测试方案,将该算法与传统高 阶滑模算法进行实验对比。 实验结果表明:在阶跃信号下,该算法使系统响应速度提高 35% ,稳态误差均方根减小 37. 5% ;在正 弦信号下,系统最大稳态误差和稳态误差均方根分别减小 30% 和 22% 。     

Cross-coupling control method of the two-axis linear motor based on second-order terminal sliding mode

When the dual-axis linear motor is processing components, its accuracy will be affected by the uncertainty and nonlinearity of the system, and the complexity of the processing curve trajectory. The goal is to improve the machining accuracy and response speed of the XY dual-axis permanent magnet synchronous linear motor two-dimensional platform, improve the anti-interference ability, and reduce the contour error. This paper proposes a coupled control method based on dual closed-loop single-axis high-order terminal sliding mode position control (TSMC). First, an improved mathematical model of equivalent contour error is established. Combine the coordinated controller to get the coupling link. Then, to accelerate error convergence and suppress chattering, a high-order terminal sliding mode controller is designed. The single-axis current controller is designed using high-order sliding mode algorithms. Simulations and experiments show the effectiveness and feasibility of the proposed method.

     

Robust tracking control of triaxial angular velocity sensors using adaptive sliding mode approach

This paper presents a robust tracking control strategy using an adaptive sliding mode approach for MEMS triaxial angular sensor device that is able to detect rotation in three orthogonal axes, using a single vibrating mass. An adaptive sliding mode controller with proportional and integral sliding surface is developed and the stability of the closed-loop system can be guaranteed with the proposed adaptive sliding mode control strategy. The proposed adaptive sliding mode controller updates estimates of all stiffness errors, damping, and input rotation parameters in real time, removing the need for any offline calibration stages. To enable all unknown parameter estimates to converge to their true values, the necessary model trajectory is shown to be a three-dimensional Lissajous pattern. The numerical simulation for a MEMS triaxial angular velocity sensor is investigated to verify the effectiveness of the proposed adaptive sliding mode control scheme.     

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.     

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.     

RBF神经滑模控制在永磁直线同步电机的应用研究

给出了神经网络学习算法和神经滑模控制器的具体设计思路,将滑模控制器的切换函数作为神经网络输入,以滑模控制器为网络输出,从而实现神经网络学习能力和滑模控制自适应切换能力有效结合,将神经滑模控制器应用于永磁直线同步电机伺服系统,通过仿真说明了其良好的跟踪特性和低速平稳性。     

随机振动机械臂的自适应鲁棒滑模控制

为了解决存在外部不确定随机干扰情况下机械臂的高精度轨迹跟踪问题,提出了一种自适应鲁棒滑模控制方法,并用Lyapunov稳定性定理证明了其闭环系统的稳定性。采用饱和函数取代控制器中的符号函数,有效消除了控制器的抖振现象。仿真结果证明：与传统的PID控制器相比,提出的自适应鲁棒滑模控制器具有更高的鲁棒性、稳定性和精度。     

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.     

Adaptive robust motion trajectory tracking control of pneumatic cylinders with LuGre model-based friction compensation

Friction compensation is particularly important for motion trajectory tracking control of pneumatic cylinders at low speed movement. However, most of the existing model-based friction compensation schemes use simple classical models, which are not enough to address applications with high-accuracy position requirements. Furthermore, the friction force in the cylinder is time-varying, and there exist rather severe unmodelled dynamics and unknown disturbances in the pneumatic system. To deal with these problems effectively, an adaptive robust controller with LuGre model-based dynamic friction compensation is constructed. The proposed controller employs on-line recursive least squares estimation（RLSE） to reduce the extent of parametric uncertainties, and utilizes the sliding mode control method to attenuate the effects of parameter estimation errors, unmodelled dynamics and disturbances. In addition, in order to realize LuGre model-based friction compensation, the modified dual-observer structure for estimating immeasurable friction internal state is developed. Therefore, a prescribed motion tracking transient performance and final tracking accuracy can be guaranteed. Since the system model uncertainties are unmatched, the recursive backstepping design technology is applied. In order to solve the conflicts between the sliding mode control design and the adaptive control design, the projection mapping is used to condition the RLSE algorithm so that the parameter estimates are kept within a known bounded convex set. Finally, the proposed controller is tested for tracking sinusoidal trajectories and smooth square trajectory under different loads and sudden disturbance. The testing results demonstrate that the achievable performance of the proposed controller is excellent and is much better than most other studies in literature. Especially when a 0.5 Hz sinusoidal trajectory is tracked, the maximum tracking error is 0.96 mm and the average tracking error is 0.45 mm. This paper constructs an adaptive robust controller