Design of a fuzzy-sliding mode controller for a SCARA robot to reduce chattering

To overcome problems in tracking error related to the unmodeled dynamics in the high speed operation of industrial robots, many researchers have used sliding mode control, which is robust against parameter variations and payload changes. However, these algorithms cannot reduce the inherent chattering which is caused by excessive switching inputs around the sliding surface. This study proposes a fuzzy-sliding mode control algorithm to reduce the chattering of the sliding mode control by fuzzy rules within a pre-determined dead zone. Trajectory tracking simulations and experiments show that chattering can be reduced prominently by the fuzzysliding mode control algorithm compared to a sliding mode control with two dead zones, and the proposed control algorithm is robust to changes in payload. The proposed control algorithm is implemented to the SCARA (selected compliance articulated robot assembly) robot using a DSP (digital signal processor) for high speed calculations.     

Sliding mode controller with sliding perturbation observer based on gain optimization using genetic algorithm

The Stewart platform manipulator is a closed-kinematics chain robot manipulator that is capable of providing high structural rigidity and positional accuracy. However, this is a complex and nonlinear system, so the control performance of the system is not so good. In this paper, a new robust motion control algorithm is proposed. The algorithm uses partial state feedback for a class of nonlinear systems with modeling uncertainties and external disturbances. The major contribution is the design of a robust observer for the state and the perturbation of the Stewart platform, which is combined with a variable structure controller (VSC). The combination of controller and observer provides the robust routine called sliding mode control with sliding perturbation observer (SMCSPO). The optimal gains of SMCSPO, which is determined by nominal eigenvalues, are easily obtained by genetic algorithm. The proposed fitness function that evaluates the gain optimization is to put sliding function. The control performance of the proposed algorithm is evaluated by the simulation and experiment to apply to the Stewart platform. The results showed high accuracy and good performance.     

Implementation of a robust dynamic control for SCARA robot

A control system for SCARA robot is designed for implementing a robust dynamic control algorithm. This study focuses on the use of DSPs in the design of joint controllers and interfaces in between the host controller and four joint controllers and in between the joint controllers and four servo drives. The mechanical body of SCARA robot and the servo drives, are selected from the commercially available products. The four joint controllers, assigned to each joint separately, are combined into a common system through the mother board hardwarewise and through the global memory softwarewise. The mother board is designed to connect joint controllers onto the board through the slots adopting PC/104 bus structures. The global memory stores the common data which can be shared by joint controllers and used by the host computer directly, and it virtually combines the whole system into one. To demonstrate the performance and efficiency of the system, a robust inverse dynamic algorithm is proposed and implemented for a faster and more precise control. The robust inverse dynamic algorithm is basically derived from an inverse dynamic algorithm and a PID compensator. Based upon the derived dynamic equations of SCARA robot, the inverse dynamic algorithm is initially implemented with l msec of control cycle—0.3 msec is actually used for the control algorithm—in this system. The algorithm is found to be inadequate for the high speed and precision tasks due to inherent modelling errors and time-varying factors. Therefore a variable PID algorithm is combined with the inverse dynamic algorithm to reinforce robustness of control. Experimental data using the proposed algorithm are presented and compared with the results obtained from the PID and the inverse dynamic algorithms.     

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。     

Fuzzy logic sliding mode control for command guidance law design

Recently, the combination of sliding mode and fuzzy logic techniques has emerged as a promising methodology for dealing with nonlinear, uncertain, dynamical systems. In this paper, a sliding mode control algorithm combined with a fuzzy control scheme is developed for the trajectory control of a command guidance system. The acceleration command input is mathematically derived. The proposed controller is used to compensate for the influence of unmodeled dynamics and to alleviate chattering. Simulation results show that the proposed controller gives good system performance in the face of system parameters variation and external disturbances. In addition, they show the effectiveness of the proposed missile guidance law against different engagement scenarios where the results demonstrate better performance over the conventional sliding mode control.     

机械臂任务空间鲁棒Terminal滑模控制

不确定性和外部干扰是制约机器人控制精度的主要因素,传统Terminal滑模控制方法未能考虑机械臂运动学不确定性。提出一种新的机械臂任务空间鲁棒连续非奇异Terminal滑模跟踪控制方法。该方法具有较强的鲁棒性,能够有效克服运动学不确定性、动力学不确定性和外部干扰,保证机械臂任务空间跟踪误差有限时间稳定,将现有机械臂Terminal滑模控制方法从关节空间扩展到任务空间。通过模型转换,同时考虑机械臂运动学不确定性和动力学模型不确定性。使用矢量和矩阵范数定义,给出系统不确定性的界定方法。运用Lyapunov再设计方法和有界稳定理论,分析系统稳定性,明确给出系统调节时间和跟踪误差剩余集的估计方法。仿真中,通过与现有机械臂关节空间Terminal滑模跟踪控制方法比较,验证了所提方法的有效性。     

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.     

Sliding mode control with PID sliding surface and experimental application to an electromechanical plant

In this study, a sliding mode control system with a proportional+integral+derivative (PID) sliding surface is adopted to control the speed of an electromechanical plant. A robust sliding mode controller is derived so that the actual trajectory tracks the desired trajectory despite uncertainty, nonlinear dynamics, and external disturbances. The proposed sliding mode controller is chosen to ensure the stability of overall dynamics during the reaching phase and sliding phase. The stability of the system is guaranteed in the sense of the Lyapunov stability theorem. The chattering problem is overcome using a hyperbolic function for the sliding surface. Experimental results that are compared with the results of conventional PID verify that the proposed sliding mode controller can achieve favorable tracking performance, and it is robust with regard to uncertainties and disturbances.     

SCARA机器人的自适应迭代学习轨迹跟踪控制

为了减小执行重复运动任务机器人的末端位置误差,提出了自适应迭代学习轨迹跟踪控制算法。根据拉格朗日方程得到SCARA机器人的动力学模型,设计了控制力矩的迭代算法,利用Lyapunov函数对该算法的稳定性进行了理论证明,搭建了具有典型机械结构的SCARA机器人实验平台。通过实验验证了自适应迭代学习控制算法能有效减小SCARA机器人的末端位置误差,具有较强的可执行性。     

A robust control with a neural network structure for uncertain robot manipulator

A robust position control with the bound function of neural network structure is proposed for uncertain robot manipulators. The uncertain factors come from imperfect knowledge of system parameters, payload change, friction, external disturbance, and etc. Therefore, uncertainties are often nonlinear and time-varying. The neural network structure presents the bound function and does not need the concave property of the bound function. The robust approach is to solve this problem as uncertainties are included in a model and the controller can achieve the desired properties in spite of the imperfect modeling. Simulation is performed to validate this law for four-axis SCARA type robot manipulator.     

A new continuous sliding mode control approach with actuator saturation for control of 2-DOF helicopter system

The 2-degree of freedom (DOF) helicopter system is a typical higher-order, multi-variable, nonlinear and strong coupled control system. The helicopter dynamics also includes parametric uncertainties and is subject to unknown external disturbances. Such complicated system requires designing a sophisticated control algorithm that can handle these difficulties. This paper presents a new robust control algorithm which is a combination of two continuous control techniques, composite nonlinear feedback (CNF) and super-twisting control (STC) methods. In the existing integral sliding mode (ISM) based CNF control law, the discontinuous term exhibits chattering which is not desirable for many practical applications. As the continuity of well known STC reduces chattering in the system, the proposed strategy is beneficial over the current ISM based CNF control law which has a discontinuous term. Two controllers with integral sliding surface are designed to control the position of the pitch and the yaw angles of the 2- DOF helicopter. The adequacy of this specific combination has been exhibited through general analysis, simulation and experimental results of 2-DOF helicopter setup. The acquired results demonstrate the good execution of the proposed controller regarding stabilization, following reference input without overshoot against actuator saturation and robustness concerning to the limited matched disturbances.     

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。     

H∞ observer-based event-triggered sliding mode control for a class of discrete-time nonlinear networked systems with quantizations

This paper investigates the problem of H_∞ observer-based event-triggered sliding mode control (SMC) for a class of uncertain discrete-time Lipschitz nonlinear networked systems with quantizations occurring in both input and output channels. The event-triggered strategy is used to save the limited network bandwidth. Then, based on the zero-order-hold (ZOH) measurement, a state observer is designed to reconstruct the system state, which facilitates the design of the discrete-time sliding surface. Considering the effects of quantizations, networked-induced constraints and event-triggered scheme, the nonlinear state error dynamics and sliding mode dynamics are converted into a unified linear parameter varying (LPV) time-delay system with the aid of a reformulated Lipschitz property. By using the Lyapunov-Krasovskii functional and free weighting matrix, a new sufficient condition is derived to guarantee the robust asymptotic stability of the resulting closed-loop system with prescribed H_∞ performance. And then the observer gain, event-triggering parameter and sliding mode parameter are co-designed. Furthermore, a novel SMC law is synthesized to force the trajectories of the observer system onto a pre-specified sliding mode region in a finite time. Finally, a single-link flexible joint robot example is utilized to demonstrate the effectiveness of the proposed method.     

快速终端滑模控制在并联机器人中的应用

针对二自由度冗余驱动并联机器人,提出了并联机器人的快速终端滑模控制(FTSMC)以实现其鲁棒控制,并利用Lyapunov函数证明了该控制系统的稳定性。仿真结果表明,该控制系统跟踪效果好,系统误差小,可以满足并联机器人控制的要求。与采用普通滑模控制相比,该控制系统具有状态响应速度快,系统状态在有限时间内收敛到零的特点。仿真实验证实了该控制策略的正确性和有效性。     

Sliding mode control of two-wheeled welding mobile robot for tracking smooth curved welding path

In this paper, a nonlinear controller based on sliding mode control is applied to a two-wheeled Welding Mobile Robot (WMR) to track a smooth curved welding path at a constant velocity of the welding point. The mobile robot is considered in terms of dynamics model in Cartesian coordinates under the presence of external disturbance, and its parameters are exactly known. It is assumed that the disturbance satisfies the matching condition with a known boundary. To obtain the controller, the tracking errors are defined, and the two sliding surfaces are chosen to guarantee that the errors converge to zero asymptotically. Two cases are to be considered : fixed torch and controllable torch. In addition, a simple way of measuring the errors is introduced using two potentiometers. The simulation and experiment on a two-wheeled welding mobile robot are provided to show the effectiveness of the proposed controller.     

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% 。     

树障清理空中机器人的姿态控制器设计

以一种用于对高压线路附近的树障进行清理的树障清理空中机器人为研究对象,分析其姿态控制问题。首先,建立了具有新型结构的树障清理空中机器人的姿态动力学模型和控制分配矩阵。然后,为了克服惯性矩阵的不确定性,采用滑模方法设计姿态控制器;同时,引入非线性函数来改进传统的边界层法以提高控制器性能;接着提出了一种切换控制分配矩阵的方法来解决空中机器人在切割作业过程中的动力学模型变化的问题。最后,在仿真平台上实现了上述控制器。实验结果表明,本滑模控制器具有良好的姿态控制性能,能有效克服机体惯量的不确定性;通过切换控制分配矩阵实现了空中机器人在切割作业过程中的姿态稳定。     

机器人关节滑模变结构的位置控制

为了使机器人关节有良好的静态特性,并具有一定的抗干扰能力,提出了一种由力矩电机和谐波减速机组成的机器人关节,采用指数趋近律的滑模变结构和模糊自适应滑模控制对机器人关节进行了位置控制,通过对机器人单关节Simulink建模仿真比较,结果表明,模糊自适应滑模控制大大减轻了指数趋近律滑模控制的抖振问题,其稳态精度达到了9×10-5rad;且与PID控制相比较,其响应速度快;在受高斯扰动时,采用模糊自适应滑模控制的关节发生的角度偏差整整比PID控制小10倍。仿真结果表明,滑模控制在机器人关节控制中精度高,响应速度快,具有一定的鲁棒性能。     

A new fractional-order sliding mode controller via a nonlinear disturbance observer for a class of dynamical systems with mismatched disturbances

This paper investigates the stabilization and disturbance rejection for a class of fractional-order nonlinear dynamical systems with mismatched disturbances. To fulfill this purpose a new fractional-order sliding mode control (FOSMC) based on a nonlinear disturbance observer is proposed. In order to design the suitable fractional-order sliding mode controller, a proper switching surface is introduced. Afterward, by using the sliding mode theory and Lyapunov stability theory, a robust fractional-order control law via a nonlinear disturbance observer is proposed to assure the existence of the sliding motion in finite time. The proposed fractional-order sliding mode controller exposes better control performance, ensures fast and robust stability of the closed-loop system, eliminates the disturbances and diminishes the chattering problem. Finally, the effectiveness of the proposed fractional-order controller is depicted via numerical simulation results of practical example and is compared with some other controllers.     

Fuzzy sliding mode control algorithm for a four-wheel skid steer vehicle

This research design and implement a robust dynamic feedback controller for a four-wheel skid steering vehicle (SSV) under highspeed cornering motion. First, SSV dynamics are modeled and analyzed to construct the simulation environment and to validate the performance of the proposed algorithm. A robust fuzzy-sliding mode controller is then designed to offset the effect of forces induced by wheel—soil interaction during skidding and ground-level fluctuations. It also eliminates the chattering phenomena encountered with conventional sliding mode control. Given P-3AT mobile robot parameters for trajectory tracking and velocity setting, extensive simulation results demonstrate the effectiveness of the proposed controller.