漂浮基柔性关节空间机器人自适应滑模运动控制及振动主动抑制

讨论了关节柔性且系统参数不确定的漂浮基空间机器人系统的动力学建模过程、运动轨迹跟踪控制算法设计及系统柔性振动的主动抑制问题。利用系统动量、动量矩守恒关系和拉格朗日法对系统动力学进行分析,并建立系统动力学方程。基于奇异摄动法将系统分解为表示系统刚性运动部分的慢变子系统和表示系统柔性运动部分的快变子系统。针对慢变子系统提出了一种自适应滑模控制算法。该控制算法是由基于滑模面的等效控制项、自适应控制项和PID反馈控制项组成。因此,它集合了滑模控制、自适应算法和PID技术的优点,且弥补了三种算法各自的缺点。该控制算法能够有效地补偿系统的转动误差和不确定参数,提高控制系统的精度。针对快变子系统,提出基于速度差值的反馈控制算法来抑制柔性关节引起的系统柔性振动,保证系统的稳定性。最后,通过仿真实验证明了提出的混合控制算法的有效性。     

An adaptive fuzzy sliding mode controller for MEMS triaxial gyroscope with angular velocity estimation

In this paper, an adaptive fuzzy sliding mode control (AFSMC) for Micro-Electro-Mechanical Systems (MEMS) triaxial gyroscope is proposed. First, a novel adaptive identification approach with sliding mode controller which can identify angular velocity and other system parameters is developed. And in order to reduce the chattering, an AFSMC is designed to approximate the upper bound of the uncertainties and external disturbances. Based on Lyapunov methods, these adaptive laws can guarantee that the system is asymptotically stable. Numerical simulations are investigated to verify the effectiveness of the proposed AFSMC scheme.     

Adaptive sliding mode control of dynamic system using RBF neural network

This paper presents a robust adaptive sliding mode control strategy using radial basis function (RBF) neural network (NN) for a class of time varying system in the presence of model uncertainties and external disturbance. Adaptive RBF neural network controller that can learn the unknown upper bound of model uncertainties and external disturbances is incorporated into the adaptive sliding mode control system in the same Lyapunov framework. The proposed adaptive sliding mode controller can on line update the estimates of system dynamics. The asymptotical stability of the closed-loop system, the convergence of the neural network weight-updating process, and the boundedness of the neural network weight estimation errors can be strictly guaranteed. Numerical simulation for a MEMS triaxial angular velocity sensor is investigated to verify the effectiveness of the proposed adaptive RBF sliding mode control scheme.     

Adaptive control of MEMS gyroscope using global fast terminal sliding mode control and fuzzy-neural-network

An adaptive control of MEMS gyroscope using global fast terminal sliding mode control (GTSMC) and fuzzy-neural-network (FNN) is presented for micro-electro-mechanical systems (MEMS) vibratory gyroscopes in this paper. This approach gives a new global fast terminal sliding surface, which will guarantee that the designed control system can reach the sliding surface and converge to equilibrium point in a shorter finite time from any initial state. In addition, the proposed adaptive global fast terminal sliding mode controller can real-time estimate the angular velocity and the damping and stiffness coefficients. Moreover, the main feature of this scheme is that an adaptive fuzzy-neural-network is employed to learn the upper bound of model uncertainties and external disturbances, so the prior knowledge of the upper bound of the system uncertainties is not required. All adaptive laws in the control system are derived in the same Lyapunov framework, which can guarantee the globally asymptotical stability of the closed-loop system. Numerical simulations for a MEMS gyroscope are investigated to demonstrate the validity of the proposed control approaches.     

基于输出的建筑结构分散滑模控制

大尺度结构分解为多个低阶子结构,子结构间的相互作用视为作用于子结构的有界扰动。本文提出了一种基于部分位移、速度输出反馈的建筑结构分散控制方法。分析了输出坐标下子结构稳定滑模的存在条件,得到输出坐标下子结构稳定滑模面方程。建立了基于输出的稳定分散控制格式,其中控制力非线性部分保证结构全局状态收敛至设计的滑模面,线性部分使建筑结构闭环子结构系统渐进稳定。以一20层钢结构基准模型在地震激励下的控制为例,验证了该分散控制的有效性。研究表明,使用部分位移、速度输出信号可以设计基于全局稳定的建筑结构分散滑模控制。所提控制方法有效抑制了大尺度建筑结构振动响应,避免了滑模设计所需的复杂坐标变换,简化了基于输出的稳定滑模设计。     

Design of CNF-based nonlinear integral sliding surface for matched uncertain linear systems with multiple state-delays

This paper presents an approach of achieving high performance and robustness for matched uncertain multi-input multi-output linear systems with external disturbances and multiple state-delays, which are often encountered in practice and are frequently the sources of instability. This scheme is based on composite nonlinear feedback and integral sliding mode control methods. The selection of nonlinear function and the existence of sliding mode are two important issues, which have been addressed. The control law is designed to guarantee the existence of the sliding mode around the nonlinear surface, and the damping ratio of the closed-loop system is increased as the output approaches the set-point. Simulation results are presented to show the effectiveness of the proposed method as a promising way for controlling similar nonlinear systems.     

弹性关节空间机械臂级联智能滑模控制

谐波减速器和力矩传感器等柔性元件因其独特性能而广泛应用在空间机器人关节系统中,以获取高减速比．但同时这些柔性元件的存在为空间机械臂系统引入了关节柔性,使得对其稳定控制变得更为复杂．基于此,文中讨论了基于自适应回归小波神经网络(Self-Recurrent Wavelet Neural Networks, SRWNN)的弹性关节空间机械臂系统动力学建模及级联智能滑模控制．首先,利用级联系统理论及第二类拉格朗日方法推导出了由外环刚性臂子系统和内环关节电机转子子系统组成的系统级联动力学模型;其次,为两个子系统分别设计了内、外环自适应滑模回归小波神经网络控制．外环控制算法以期望轨迹为控制量,而其控制信号作为抑制弹性关节振动的内环控制算法的控制量,整个控制系统由内、外环控制系统叠加而成;而后,基于Lyapunov稳定性理论证明了整个控制系统的稳定性并设计了自适应回归小波神经网络的各权值参数在线学习算法．所提的控制算法有效地消除了模型不确定的影响,避免了复杂的求导计算和角加速度可测的要求,同时,控制系统设计过程中未涉及惯常奇异摄动双时标分解操作,在理论上适合任意大小的关节柔性刚度．最后,系统对比仿真试验证明了所提的级联智能控制算法优于惯常基于奇异摄动法和基于柔性铰补偿奇异摄动法的控制方案．     

振动陀螺仪单向时滞耦合系统的摄动分析

针对振动陀螺仪单向时滞耦合系统,研究了角速度、耦合强度、耦合时滞与系统输出信号之间的关系,着重关注耦合时滞对待检测角速度测量结果的影响．本文采用摄动法对振动陀螺仪单向时滞耦合系统进行理论分析,得到了系统输出信号、系统振动边界和待检测角速度的近似表达式,并将数值和近似计算结果进行了对比．理论分析结果与数值结果比较吻合,验证了运用摄动法分析振动陀螺仪单向时滞耦合系统的有效性,也表明了在运用摄动法分析系统时具有局限性．     

微机械陀螺仪结构误差的控制技术

研究了与加工精度相关的结构误差以及结构参数随环境改变产生的仪表误差。在分析机理的前提下,提出了采用数字控制技术来抑制陀螺结构误差的技术方案,即结构的反馈解耦控制,驱动模态的恒频恒幅控制以及检测模态的力反馈解耦控制。利用平均和摄动理论分别对上述控制回路进行建模,并给出了仿真结果。分析和仿真结果表明,上述控制方案能有效消除结构的耦合运动,降低陀螺输出对结构参数的依赖。     

Nonlinear dynamic analysis and sliding mode control for?a?gyroscope system

This paper employs differential transformation (DT) method to analyze and control the dynamic behavior of a gyroscope system. The analytical results reveal a complex dynamic behavior comprising periodic, subharmonic, quasiperiodic, and chaotic responses of the center of gravity. Furthermore, the results reveal the changes which take place in the dynamic behavior of the gyroscope system as the external force is increased. The current analytical results by DT method are found to be in good agreement with those of Runge?CKutta (RK) method. In order to suppress the chaotic behavior in gyroscope system, the sliding mode controller (SMC) is used and guaranteed the stability of the system from chaotic motion to periodic motion. Numerical simulations are shown to verify the results. The proposed DT method and controlling scheme provide an effective means of gaining insights into the nonlinear dynamics and controlling of gyroscope systems.     

Decentralized sliding mode control of fractional-order large-scale nonlinear systems

This paper presents some novel discussions on fully decentralized and semi-decentralized control of fractional-order large-scale nonlinear systems with two distinctive fractional derivative dynamics. First, two decentralized fractional-order sliding mode controllers with different sliding surfaces are designed. Stability of the closed-loop systems is attained under the assumption that the uncertainties and interconnections among the subsystems are bounded, and the upper bound is known. However, determining the interconnections and uncertainties bound in a large-scale system is troublesome. Therefore in the second step, two different fuzzy systems with adaptive tuning structures are utilized to approximate the interconnections and uncertainties. Since the fuzzy system uses the adjacent subsystem variables as its own input, this strategy is known as semi-decentralized fractional-order sliding mode control. For both fully decentralized and semi-decentralized control schemes, the stability of closed-loop systems has been analyzed depend on the sliding surface dynamics by integer-order or fractional-order stability theorems. Eventually, simulation results are presented to illustrate the effectiveness of the suggested robust controllers.     

振动轮式硅微陀螺仪检测轴的闭环特性

研究了振动轮式硅微陀螺仪敏感结构的谐振特性,重点进行了检测轴的闭环控制系统分析和测试。通过对不同气压条件下检测轴谐振特性的研究及驱动轴和检测轴谐振频率匹配的试验,分析了静电力反馈控制系统中的变刚度问题,进行了硅微陀螺仪检测轴的闭环控制系统设计,给出了检测轴闭环控制系统的原理框图和传递函数,同时分析了闭环条件下驱动轴回路和检测轴回路各部分的相位关系以及正交分量的消除方法。试验结果表明闲环控制提高了硅微陀螺仪的精度指标。     

漂浮基柔性空间机器人的鲁棒控制及振动抑制

讨论了漂浮基柔性空间机器人系统的动力学建模、运动控制算法设计以及关节、臂双重柔性振动的分级主动抑制问题. 利用系统动量、动量矩守恒关系和拉格朗日-假设模态法对系统进行动力学分析,建立系统动力学方程. 基于奇异摄动法,将系统分解为表示系统刚性运动部分的慢变子系统, 表示由柔性臂引起的系统柔性运动部分的快变子系统1和表示由柔性关节引起的系统柔性运动部分的快变子系统2. 针对慢变子系统提出一种鲁棒控制方法来补偿系统参数的不确定性和柔性关节引起的转动误差,实现系统期望运动轨迹的渐近跟踪;针对快变子系统1采用线性二次型最优控制器来抑制由柔性臂引起的系统柔性振动;针对快变子系统2设计了基于机械臂和电机转子的转角速度差值的反馈控制器来抑制由柔性关节引起的系统柔性振动. 因此,系统的总控制律为以上3个子系统控制律的综合. 最后通过仿真实验证明了所提出的混合控制方法的有效性.      

A particle swarm optimization approach for fuzzy sliding mode control for tracking the robot manipulator

In this paper, an optimal fuzzy sliding mode controller is used for tracking the position of robot manipulator, is presented. In the proposed control, initially by using inverse dynamic method, the known sections of a robot manipulator’s dynamic are eliminated. This elimination is done due to reduction over structured and unstructured uncertainties boundaries. In order to overcome against existing uncertainties for the tracking position of a robot manipulator, a classic sliding mode control is designed. The mathematical proof shows the closed-loop system in the presence of this controller has the global asymptotic stability. Then, by applying the rules that are obtained from the design of classic sliding mode control and TS fuzzy model, a fuzzy sliding mode control is designed that is free of undesirable phenomena of chattering. Eventually, by applying the PSO optimization algorithm, the existing membership functions are adjusted in the way that the error tracking robot manipulator position is converged toward zero. In order to illustrate the performance of the proposed controller, a two degree-of-freedom robot manipulator is used as the case study. The simulation results confirm desirable performance of optimal fuzzy sliding mode control.     

Forced sliding mode control for chaotic systems synchronization

Synchronization of chaotic systems is considered to be a common engineering problem. However, the proposed laws of synchronization control do not always provide robustness toward the parametric perturbations. The purpose of this article is to show the use of synergy-cybernetic approach for the construction of robust law for Arneodo chaotic systems synchronization. As the main method of design of robust control, the method of design of control with forced sliding mode of the synergetic control theory is considered. To illustrate the effectiveness of the proposed law, in this article it is compared with the classical sliding mode control and adaptive backstepping. The distinctive features of suggested robust control law are the more good compensation of parametric perturbations (better performance indexes—the root-mean-square error (RMSE), average absolute value (AVG) of error) without designing perturbation observers, the ability to exclude the chattering effect, less energy consuming and a simpler analysis of the stability of a closed-loop system. The study of the proposed control law and the change of its parameters and the place of parametric perturbation’s application is carried out. It is possible to significantly reduce the synchronization error and RMSE, as well as AVG of error by reducing some parameters, but that leads to an increase in control signal amplitude. The place of application of parametric disturbances (slave or master system) has no effect on the RMSE and AVG of error. Offered approach will allow a new consideration for the design of robust control laws for chaotic systems, taking into account the ideas of directed self-organization and robust control. It can be used for synchronization other chaotic systems.

     

基于反演高阶滑模的飞行器最优末制导律

针对传统最优末制导律鲁棒性能较弱,且对参数摄动及外扰敏感的不足,而滑模控制对扰动具有较强鲁棒性的优点,提出一种新的基于反演准连续高阶滑模的最优末制导律,其中反演控制能够有效保证系统全局稳定性,而准连续高阶滑模控制则用于消除扰动影响。为了去除抖振效果,引入自适应超螺旋算法在线更新控制参数以消除符号函数导致的高频抖振影响。仿真结果表明:飞行器在该末制导律导引下,弹目视线角速率快速收敛,从而保证飞行器有很高的命中精度;鲁棒性较强;能够较好的满足约束条件要求。     

Model predictive control of rigid spacecraft with two variable speed control moment gyroscopes

In this paper, an attitude maneuver control problem is investigated for a rigid spacecraft using an array of two variable speed control moment gyroscopes(VSCMGs)with gimbal axes skewed to each other. A mathematical model is constructed by taking the spacecraft and the gyroscopes together as an integrated system, with the coupling interaction between them considered. To overcome the singular issues of the VSCMGs due to the conventional torque-based method, the first-order derivative of gimbal rates and the second-order derivative of the rotor spinning velocity, instead of the gyroscope torques, are taken as input variables. Moreover, taking external disturbances into account,a feedback control law is designed for the system based on a method of nonlinear model predictive control(NMPC). The attitude maneuver can be realized fast and smoothly by using the proposed controller in this paper.     

TRAJECTORY TRACKING CONTROL FOR DUAL-ARM SPACE ROBOT WITH BOUNDED INPUT TORQUES

讨论基座姿态、位置均不控的自由漂浮双臂空间机器人在关节驱动力矩受限下其关节协调运动的控制问题. 运用拉格朗日第二类方程并耦合动量守恒关系建立动力学方程. 尔后,设计了基于饱和函数的控制方案,该方案引入具有饱和特性的双曲正切函数来控制关节力矩幅值. 最后,根据奇异扰动系统稳定性理论将系统分为降阶系统和边界层系统,分别利用李雅普诺夫函数证明其在原点呈指数稳定. 数值仿真进一步表明该方案的有效性和优越性.     

基于干扰观测器的柔性关节空间机器人退步自适应控制

研究了载体位置、姿态均不受控的情况下,系统参数不确定的柔性关节空间机器人轨迹跟踪的控制问题.结合系统动量、动量矩守恒关系,利用拉格朗日法推导出系统的动力学模型.为减小系统柔性关节对系统控制精度的影响,采用关节柔性补偿器来等效降低系统关节的柔性.再借助奇异摄动法,针对系统参数不确定的情况,设计了柔性关节空间机器人基于干扰观测器的退步自适应滑模控制方案.该方案不需要对系统惯性参数进行线性化处理,控制器结构简单,且实现了空间机器人期望轨迹的精确跟踪控制.通过平面两杆空间机器人的数值仿真证明了该方法的有效性.     

密频系统的反馈控制

研究了如何将结构重频系统设计中的反馈控制律用到含有密频子结构的系统上去，主要解决了如何估计将重频系统控制律用到相应的密频系统对闭环系统的（指数）衰减律的影响，原系统的结构参数有少量变化后的新系统以及原系统是不可控的密频系统的情形．理论和数值算例表明，只要对重频系统设计的反馈律作正确的坐标变换，应用到上述三种情形时，其闭环系统的衰减律的误差只有相应频率分散度的一阶小量