Modeling,identification and analysis of a novel two-axis differential micro-feed system

With the development of precision and ultra-precision machining technology, the demand of drive feed system increases. Non-linear friction in a conventional drive feed system (CDFS) feeding at low speed is one of the main factors that lead to the complexity of the feed drive. The CDFS will inevitably enter or approach a non-linear creeping area at extremely low speed. A novel two-axis differential micro-feed system (TDMS) is developed in this paper to overcome the accuracy limitation of CDFS. A dynamic model of TDMS is first established. Then, a distributed component friction parameter identification method using a genetic algorithm (GA) to identify the friction parameters of a TDMS is introduced. A proportional-derivate feed drive position controller with an observer-based friction compensator is implemented to achieve an accurate trajectory tracking performance. Finally, comparative experiments demonstrate the effectiveness of the TDMS in inhibiting the disadvantageous influence of non-linear friction and the validity of the proposed identification method for TDMS.     

Applications of integrated motion controllers for precise CNC machines

The error resources of precise motion control systems are basically categorized into linear and nonlinear effects. To realize the precise motion of industrial computer numerical control (CNC) machines, this paper presents an integrated motion control structure with modular algorithms, including both the linear control and the nonlinear compensation. In the linear control design, this study applies three algorithms: (1) feedforward control to address the tracking errors, (2) cross-coupled control to reduce the contouring errors, and (3) digital disturbance observer to lessen the effects of modeling errors and disturbances in real applications. The results indicate that the linear motion controller achieves greatly improved accuracy in both tracking and contouring by reducing the servo lags and mismatched dynamics of the different axes. However, the adverse effect due to friction still exists and cannot be eliminated by applying the linear motion controller only. This study further integrates the nonlinear compensator and develops friction estimation and compensation rules for CNC machines. The digital signal processors are suitable to implement all the developed linear and nonlinear algorithms, and the present controllers have been successfully applied to industrial CNC machines. Experimental results on a vertical machining center indicate that, under different feed rates, the CNC machine with the integrated motion controller significantly reduces the maximum contouring error by 135% on average.     

Improvement of motion accuracy and energy consumption of a mechanical feed drive system using a Fourier series-based nonlinear friction model

Friction occurring in all mechanical systems, such as computer numerical controlled (CNC) machine tools, is an important issue in achieving the high accurate performance. Friction adversely affects not only motion accuracy of drive axes but also excessively consumes energy. Feed drives of CNC machines normally operate all day and night around the world, and therefore consumed energy reduction is highly expected. The motivation behind this work is to construct a novel friction model that can comprise many unknown friction sources in both low and high velocity regions and enable a friction compensator to precisely describe actual frictional behavior. A sliding mode control (SMC) is designed to verify the effectives of the proposed friction model in a biaxial feed drive system. Experimental results confirm that a combination of SMC and the proposed friction can effectively improve tracking accuracy and further achieve significant reduction of consumed energy compared to combining with the conventional model. Results show that the proposed approach can largely decrease the mean tracking error to less than 5 µm for each axis. The new friction also achieved effective reduction of control variance by 7.62%. Consequently, consumed energy of feed drives was significantly improved by 12.83% compared to using the conventional model.     

Disturbance observer and adaptive controller design for a linear-motor-driven table system

This paper presents a disturbance observer and adaptive controller design for a direct drive motion control system. An indirect adaptive controller is implemented to achieve desired tracking performance as well as deal with system parameters variation. To reduce tracking errors, a newly designed adaptive feed-forward controller is proposed based on an on-line estimated inverse model of the linear motor drive system. A digital disturbance observer is implemented to be included in the proposed feedback-feed-forward control structure to compensate for the undesired nonlinearity and external load disturbance of the direct drive system. Experimental results show that this control scheme can achieve superior contouring accuracy, disturbance rejection and robustness under the influence of friction and cogging force.     

Feedforward suppression of force ripple based on a simplex-optimized dither signal

This paper presents the design and realization of a feedforward dither signal to reduce the force ripple in an iron-core permanent magnet linear motor (PMLM). A composite control structure is used, consisting of three components: a simple feedforward component, a PID feedback component, and a ripple compensator (RC). The first two components are designed based on a dominant linear model of the motor. The dither signal is generated based on a signal model which is identified using a multidimensional simplex downhill method. In this way, a simple approach is available to eliminate or suppress the inherent force ripple, thus facilitating smooth precise motion while uncompromising on the maximum force achievable. Real-time experimental results verify the effectiveness of the proposed scheme for high precision motion trajectory tracking.     

Precision motion control of permanent magnet linear motors

In the paper, a method of precision motion control for permanent magnet linear motors is proposed. Unlike rotational motors, permanent magnetic linear motors are more sensitive to various force disturbances because of the reduction of gears. So, as a feedback compensator, a disturbance observer is used to compensate the force disturbances based on the disturbance model. But the force disturbances of permanent magnetic linear motors cannot be fully compensated owing to the error of dynamic model, inaccurately detected velocity and acceleration, especially when a permanent magnetic linear motor runs in low speed. Further analysis shows that the force ripple is the main force disturbance when the velocity of a PMLM is close to zero, and the disturbance model denotes that the force ripple is position dependent. In order to further suppress the force disturbances of permanent magnetic linear motors a feedforward neural network using the BP algorithm is proposed to approximate and compensate the force ripple. The experimental results show that the force ripple is efficiently alleviated and the high positioning precision can be achieved by using the proposed precision motion control method.     

Position tracking control of saturated LSRM

This paper deals with the tracking control design of a linear synchronous reluctance motor (LSRM) drive. An extended nonlinear dynamic LSRM model with magnetic saturation included is used in the control design and practical realization, in order to improve tracking performances at very low speeds of motion. Iron core saturation is included in the extended model with the experimentally determined flux linkages given as functions of the direct and quadrature axes currents. Experimental results show that the proposed input-output linearizing tracking control with included saturation behaves considerably better than the one without saturation, introducing smaller position and speed errors and better motor stiffness, on account of the increased computational complexity.     

电液马达伺服系统积分鲁棒自适应高精度位置控制

电液马达伺服系统中存在各种类型的扰动,包括参数不确定性和不确定非线性,制约着其高精度位置控制。针对电液马达伺服系统高精度位置跟踪控制,考虑系统的黏性摩擦特性以及外干扰等建模不确定性,提出了一种基于鲁棒自适应的电液马达伺服系统高精度位置控制策略。所提出的全状态控制器通过自适应对模型不确定性进行估计及前馈补偿,提高了系统的低速伺服性能;通过自适应对未建模干扰等不确定性的上界进行估计并前馈补偿,提高了系统对外干扰的鲁棒性。所设计的闭环控制器还能保证系统获得渐近跟踪性能,对比仿真验证了其可行性。     

高加速度运动系统的非线性摩擦前馈补偿控制

高加速度运动系统中非线性摩擦的建模补偿对提高轨迹跟踪性能至关重要。本文针对传统参数化模型难以准确预估高加速度运动启停阶段摩擦过冲等非线性摩擦的问题,在传统模型结构的基础上,结合扩展Stribeck模型,提出一种扩展参数化模型,模型参数的训练和学习样本源于高精度迭代学习控制获取的有限轨迹下非线性摩擦前馈补偿数据,并采用Levenberg-Marquardt算法拟合模型参数。最后,在音圈电机驱动的高加速定位平台上针对不同运动轨迹进行了实验验证。结果表明,该方法能够克服传统参数化模型难以消除高加速度启停阶段摩擦过冲等非线性摩擦对轨迹跟踪精度的影响;且与迭代学习控制的轨迹跟踪精度接近,有效避免了迭代学习泛化性差等问题,可实现工作空间下任意轨迹的摩擦补偿。     

永磁同步电机位置伺服系统改进变结构自抗扰控制

为进一步提高传统变结构自抗扰控制器的控制精度,增强永磁伺服驱动系统的抗干扰能力,提出一种改进变结构自抗 扰控制策略。 该方法在基于变结构原理设计的扩张状态观测器中引入位置、速度的观测误差以实现状态变量的无差估计,采用 基于指数趋近律设计的非线性状态误差反馈控制律实现线性控制与非线性控制的平滑过渡,并在此基础上引入位置跟踪误差, 提高伺服系统的跟踪性能。 通过实验分析比较了改进变结构自抗扰控制与传统变结构自抗扰控制两种控制策略,结果显示改 进控制策略较传统控制策略的位置跟踪误差减少了约 30% 。 当负载突变时,传统控制策略的跟踪误差约为负载突变前最大跟 踪误差的 3. 4 倍,而改进变结构自抗扰控制策略仍能准确跟踪给定信号。     

Model predictive control for a class of systems with isolated nonlinearity

The paper is concerned with an overall convergent nonlinear model predictive control design for a kind of nonlinear mechatronic drive systems. The proposed nonlinear model predictive control results in the improvement of regulatory capacity for reference tracking and load disturbance rejection. The design of the nonlinear model predictive controller consists of two steps: the first step is to design a linear model predictive controller based on the linear part of the system at each sample instant, then an overall convergent nonlinear part is added to the linear model predictive controller to combine a nonlinear controller using error driven. The structure of the proposed controller is similar to that of classical PI optimal regulator but it also bears a set-point feed forward control loop, thus tracking ability and disturbance rejection are improved. The proposed method is compared with the results from recent literature, where control performance under both model match and mismatch cases are enlightened.     

Robust iterative learning contouring controller with disturbance observer for machine tool feed drives

In feed drive systems, particularly machine tools, a contour error is more significant than the individual axial tracking errors from the view point of enhancing precision in manufacturing and production systems. The contour error must be within the permissible tolerance of given products. In machining complex or sharp-corner products, large contour errors occur mainly owing to discontinuous trajectories and the existence of nonlinear uncertainties. Therefore, it is indispensable to design robust controllers that can enhance the tracking ability of feed drive systems. In this study, an iterative learning contouring controller consisting of a classical Proportional-Derivative (PD) controller and disturbance observer is proposed. The proposed controller was evaluated experimentally by using a typical sharp-corner trajectory, and its performance was compared with that of conventional controllers. The results revealed that the maximum contour error can be reduced by about 37% on average.     

大型天文望远镜摩擦传动系统低速特性的研究

研究了大型天文望远镜摩擦传动系统的运行原理和特性,并进行了实验。结果表明,影响摩擦传动低速稳定运行的因素很多,主要有:编码器的测量误差,环境变化引起的误差,摩擦力矩和电机波动力矩等引起的误差,以及加工制造和安装引起的误差。另外在整个传动链中其它部分的摩擦力矩也不可能是一个定值,也存在力矩波动。结果还表明,利用非线性PID控制算法增益参数非线性变化的特性,可以使得控制系统既能达到响应速度快,无超调的目的,又能增强抵抗影响摩擦传动低速稳定运行因素的能力。实验中,低速可以达到0.2″/s,位置精度为0.032″(RMS),证明了这种方法是行之有效的。     

Modeling and control compensation of nonlinear friction using adaptive fuzzy systems

System performance in terms of control accuracy and stability is usually negatively affected by friction occurrences in mechanical systems. Thus, it is important to model the friction properly so that it can be used in controller design. This paper employs adaptive fuzzy systems to approximate unknown nonlinear friction functions, and applies the estimation of friction in proportional-derivative (PD) control law to enhance the control performance. On the basis of Lyapunov stability theory, a bound of tracking errors of the closed-loop control system is derived. Techniques proposed in this paper have been applied to a typical motion control system for simulation studies. The results obtained demonstrate that our proposed method in this paper has good potential in controlling many mechanical systems with unknown nonlinear friction.     

Feedforward element design using learning controller for precision control of linear synchronous motor with nonlinear characteristics

This study presents a time-invariant feedforward (FF) element design for the high-speed and high-precision tracking control of an ultrahigh-acceleration, high-velocity linear synchronous motor (LSM). The linear motor can generate an acceleration greater than 70 G (= 686 m/s²) and move at a velocity above 10 m/s. To take advantage of this performance and realize high response, the design and usage of suitable FF elements is crucial. However, as the LSM includes highly nonlinear characteristics, it is difficult to provide an exact dynamic model for FF design. To overcome this problem, a control system with a learning controller (LC) as the FF element has been designed previously, demonstrating high-precision and high response motion. However, the motion performance can be achieved only with sufficient pre-learned motions. The integrator and the disturbance observer that were effective in suppressing disturbances were removed from the control system. In addition, the control system has some FF time-invariant elements along with the LC. This study proposes a design method for easy design of all FF elements using an LC. The designed FF elements are time invariant and are used with an integrator and a disturbance observer, without pre-learning. Using the proposed method, two sets of time-invariant FF elements are designed. The performances of two control systems, which include a set of time-invariant FF elements for each, and a simple disturbance observer are experimentally examined and compared with two previously designed control systems. Experimental results demonstrate that the performance of one of the control systems with a set of time-invariant FF elements designed in this study and a disturbance observer is good and almost comparable with that of the previously designed control system with high-precision and high response motion.     

Variable structure fuzzy control using three input variables for reducing motion tracking errors

Conventional fuzzy controllers for motion tracking utilize generally two input variables (position error and velocity error) to deal with highly nonlinear and time-varying dynamics associated with complex mechanical motion with multi- DOF. This results in some tracking errors at steady state, in general, mainly due to friction existing in mechanical systems. To eliminate the steady-state tracking errors, a variable structure fuzzy control algorithm is proposed using three input variables (position error, velocity error, and integral of position errors) and a switching logic between two inputs and three inputs. Simulation and experimental studies have been conducted to show the validity of the proposed control logic using a direct-drive SCARA manipulator with two degree-of-freedom. It has been shown that the proposed fuzzy control logic has significantly improved motion-tracking performance of the mechanical system when it is applied to complex polygon-tracking in Cartesian space with inverse kinematics and path planning. This paper was recommended for publication in revised form by Associate Editor Kyongsu Yi Chul-Goo Kang received his B.S. and M.S. degree in Mechanical Design and Production Engineering from Seoul National University, Korea, in 1981 and 1985, respectively. He then received his Ph.D. degree from Univ. of California, Berkeley in 1989. Dr. Kang is currently a Professor at the Department of Mechanical Engineering, Konkuk University in Seoul, Korea. He serves as a board member of the Institute of Control, Robotics and Systems, and also Korea Robotics Society. His research interests include motion and force control, train brakes, and intelligent robots.     

Nonlinear robust dual-loop control for electro-hydraulic load simulator

This paper investigates on the high performance torque control of electro-hydraulic load simulator (EHLS). In order to suppress actuator׳s motion disturbance, a nonlinear robust dual-loop control scheme is developed, which consists of a open-loop nonlinear velocity feed-forward compensator and a closed-loop nonlinear deterministic robust torque controller. The main function of the open-loop compensator is to decouple actuator׳s active motion disturbance, whereas the torque loop controller aims at guaranteeing the dynamics performance of tracking torque reference. Besides actuator׳s motion disturbance, both the nonlinearity characteristics and friction problem of the EHLS system are taken into consideration in this paper. The effectiveness of the developed method are verified through comparative co-simulations and experiments.     

精密定位系统的摩擦力建模与补偿

为了提高由直线电机驱动的精密定位系统的定位精度,建立了优化Stribeck摩擦模型,对摩擦力这一影响定位精度的主要因素进行补偿。首先,对于传统的Stribeck摩擦模型进行优化,采用改进的最小二乘算法对模型参数进行辨识。然后,对所建立的摩擦模型补偿算法进行仿真并与扰动观测器的补偿算法进行比较,发现前者速度比后者速度在补偿后提高了4.33%,对摩擦力具有更好的补偿效果。最后,在大行程二维精密定位平台上进行验证,根据平台能够达到的最大速度定义0.005 m/s为低速运动,0.05 m/s为高速运动,在这两种速度下进行实验,并与基于库仑摩擦前馈补偿模型比较。实验结果表明：精密定位平台在速度为0.005 m/s的低速运动时,优化模型的跟随误差减小了67.67%;在速度为0.05 m/s的高速运动时,优化模型的跟随误差减小了51.63%,验证了优化Stribeck摩擦模型补偿算法的有效性。本文提出的优化Stribeck摩擦模型可用于提高由直线电机驱动的精密定位系统的定位精度。     

考虑控制电信号中间量的机床运动控制误差数据驱动建模方法

现有数据驱动的机床运动控制误差建模方法通常使用端到端的模型,即通过机器学习算法直接构建参考轨迹信息(速度、加速度等)与伺服误差之间的模型,以降低建模复杂度。然而,该方法忽视了控制电信号对运动控制系统非线性扰动的反映,而导致建立的模型精度受限。为解决此问题,提出了一种使用控制电信号作为中间量的数据驱动运动控制误差建模方法。该方法采集参考轨迹信息(速度、加速度、急动度等)、控制电信号、跟踪误差以及构造的换向特征,构建并训练基于参考轨迹信息的控制电信号预测网络,以及基于电信号和参考轨迹信息的运动控制误差预测网络,利用控制电信号这一中间量有效反应系统所受非线性扰动的特点,实现了高精度的运动控制误差数据驱动建模。在实际验证测试时,将参考轨迹信息输入电信号预测网络,而后将得到的预测控制电信号和参考轨迹信息输入跟踪误差预测网络,即可实现运动控制误差的预测。通过实验对所提出的建模方法进行了验证,所提出方法相对于传统的端到端建模方法,运动控制误差的预测精度在X轴和Y轴分别提升16.33%和20.42%,误差补偿后运动控制轮廓精度相较于未补偿提升85.59%,验证了所提出方法的可行性。     

Trajectory planning and tracking control of a ground mobile robot:A reconstruction approach towards space vehicle

With the development of the similarity calculation method, the orbital motion of space vehicle can be translated into a sequence of waypoints that reflect position and velocity on the ground. In this paper, a motion control system is proposed to make the mobile robot pass through the desired waypoints for reconstructing the orbital motion. First, the parameterized trajectory optimization method is applied to generate a curvature-continuous trajectory from the waypoints, the position and velocity demands are presented as the equality constraints. Virtual positions are introduced to reduce the oscillation, and the total execution time of the whole trajectory is selected as the optimization parameter to reduce the computational burden. Then, an equivalence transformation is provided to translate the error system into an affine form, which is beneficial for the feedback controller design. Based on this, a nonlinear trajectory tracking controller is proposed, which includes a feedforward controller and an error feedback controller, and its exponential stability is proved using Persistency of Excitation Lemma. In addition, a shunting neural dynamics model is employed to avoid sharp velocity jumps. Finally, the performed experiments verify the effectiveness of the proposed method.