机械手时间最优轨迹规划方法研究

提出一种基于模糊遗传算法的机械手时间最优轨迹规划方案。该方案对简单遗传算法进行了改进，将模糊原理应用于遗传算法，形成了模糊遗传算法，对遗传算法中的交叉概率及变异概率进行模糊控制，提高了算法的收敛速度，有效地避免了初期收敛的发生，在进行时间最优轨迹规划时，综合考虑了机械手的运动学与动力学特性，采用罚函数方法来处理力矩约束。经仿真研究表明，该方法简单实用，适用于大范围空间的轨迹规划，克服了传统的非线性规划方法容易陷入局部极小的不足。     

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.     

Trajectory planning of redundant manipulator using fuzzy clustering method

The solution of inverse kinematics and trajectory planning with performance criteria for a redundant manipulator is proposed with modification in fuzzy c-means. A new fuzzy clustering model based on a new generalized validity index based on weighted within-scatter metrics and between-cluster scatter metrics for the manipulator is proposed. In order to understand the proposed algorithm and to show its performance, two simulation studies of trajectory planning with manipulability criteria for a redundant manipulator are modeled to solve the problems of finding association rules in the data and of setting up an appropriate classification procedures. The problem of redundant manipulator (which is a multi-input, multi-output nonlinear system) is new in terms of solution by clustering method. The proposed algorithm for the trajectory planning of the manipulator is simulated using Matlab®. All practical steps, from data acquisition to model validation, are illustrated using a 4 degree of freedom robot manipulator. The simulated results are compared with the numerical methods of the trajectory planning. The results are presented graphically. The proposed method has the advantage of simplicity, flexibility, and good tracking performance.     

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.     

欠驱动机器人最优运动轨迹生成与跟踪控制

以被动关节自由的欠驱动机器人为研究对象,对其最优运动规划与轨迹跟踪控制问题进行研究,控制目标为实现欠驱动机器人关节的任意位置控制.对欠驱动机器人系统的可控性条件进行分析,提出部分稳定规划器的思想,利用遗传算法对建立的适应度函数进行全局优化,得到部分稳定规划器的最优切换顺序.利用变结构控制方法进行反馈控制,实现了期望轨迹的精确跟踪.提出的方法一方面利用遗传算法的全局搜索能力,不必考虑机器人的严格线性化,能够快速、准确地实现路径寻优,且具有很好的稳定性:另一方面采用的变结构控制方法能够对系统干扰及参数变化具有良好的自适应性,因此本方法可以很容易推广到多自由度欠驱动机器人系统控制当中.通过末关节为被动关节的平面3自由度机器人进行仿真,仿真结果证明了方法的有效性.     

Trajectory optimization of an electro-hydraulic robot

The electro-hydraulic robot has great driving torque and plays an irreplaceable role in manufacturing. In this paper, a trajectory planning method for a 6-DOF electro-hydraulic robot based on time-energy-jerk is proposed and realized. A multi-objective function of the electro-hydraulic robot about working efficiency, impact, stability and energy consumption factors was built, at the same time, the kinematic and dynamic constraint functions were also built. The multi-objective trajectory function of the robot was optimized by using the non-dominated neighborhood immune genetic algorithm, and the optimal position, velocity, acceleration and jerk planning curves of each joint were obtained. In the experiment, the flow output curves of the hydraulic system of joint 6 based on fuzzy-PID control strategy under no-load, 1.5 kg load, 4 kg load were obtained, and show that the velocity and position trajectory of the joint can be well controlled using the presented fuzzy PID control strategy.

     

基于改进遗传算法的时间最优轨迹规划

提出一种工业机器人时间最优轨迹规划方法.将机器人关节空间的轨迹视为拟合关键点的三次样条曲线,以最优时间为目标建立最优时间轨迹规划的数学模型,同时考虑关节轨迹速度、加速度和加加速度的约束,结合目标函数值和约束条件提出一种用于进化算法的排序方法,以改进遗传算法为例优化关节空间的三次样条轨迹.应用谢菲尔德(Sheffield...     

基于遗传算法的平面欠驱动机器人模糊控制

以平面欠驱动机器人为研究对象,对其运动控制问题进行了研究,提出了一种基于遗传算法的模糊控制新方法.控制目标为实现欠驱动机器人的任意位置控制.控制器直接以关节角度误差变量作为模糊控制器的输入,引入遗传算法对模糊控制规则和隶属度函数同时进行优化,进而得到最优模糊控制系统,最后进行数值仿真,仿真结果表明所设计的控制器能快速精确的实现2自由度及3自由度欠驱动机器人的任意位置控制,且具有很好的稳定性.     

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。     

A type-2 fuzzy expert system based on a hybrid inference method for steel industry

In this paper, a novel type-2 fuzzy expert system for prediction the amount of reagents in desulfurization process of a steel industry in Canada is developed. In this model, the new interval type-2 fuzzy c-regression clustering algorithm for structure identification phase of Takagi–Sugeno (T–S) systems is presented. Gaussian Mixture Model is used to generate partition matrix in clustering algorithm. Then, an interval type-2 hybrid fuzzy system, which is the combination of Mamdani and Sugeno method, is proposed. The new hybrid inference system uses fuzzy disjunctive normal forms and fuzzy conjunctive normal forms for aggregation of antecedents. A statistical test, which uses least square method, is implemented in order to select variables. In order to validate our method, we develop three system modeling techniques and compare the results with our proposed interval type-2 fuzzy hybrid expert system. These techniques are multiple regression, type-1 fuzzy expert system, and interval type-2 fuzzy TSK expert system. For tuning parameters of the system, adaptive-network-based fuzzy inference system is used. Finally, neural network is utilized in order to reduce error of the system. The results show that our proposed method has less error and high accuracy.     

基于规则的自组织模糊控制算法研究

针对一类具有慢时变、大滞后、非线性的复杂过程控制，提出了一种基于规则自调整的模糊控制算法，它通过对对象特性的辨识与控制量的校正，直接修改控制规则，避免了常规模糊控制对操作经验过分依赖及采用模糊推理修改规则求解模糊关系矩阵的复杂运算过程，增强了控制的实时性。     

点焊机器人轨迹能耗模型及其优化算法研究

提出一种点焊机器人最优能耗轨迹优化方法,将机器人关节空间中的关键点用五次多项式曲线连接,并基于机器人动力学建立了永磁交流伺服电机驱动的点焊机器人轨迹能耗模型。在考虑运动学、动力学及生产周期约束的情况下,采用蜜蜂进化型遗传算法求解了点焊机器人最优能耗轨迹。为保证算法全局寻优和收敛速度,构建了一种非线性适应度函数。仿真结果表明,与之前算法相比,求解效率更高,且最优能耗轨迹较最短时间轨迹能耗明显减少。     

打滑状态下的多机器人编队控制

讨论打滑状态下的多机器人编队控制器设计问题。打滑现象会使机器人偏离正常的运动轨迹,导致基于理想环境设计的控制器控制效果变差,甚至发生机器人失控的现象。考虑打滑因素的控制算法能使机器人适应更一般的环境,增强机器人的实际可用性。采用领导者-跟随者策略来协调各机器人的运动。领导者机器人的运动规律根据任务需要事先设定,随后控制跟随者机器人以一定距离和角度跟随领导者机器人运动。根据机器人的运动特性导出单机器人在打滑情况下的运动规律,并据此导出两机器人以距离-角度模型形成编队的方程。采用二阶滑模控制法来为跟随者机器人设计控制器,使得两机器人在运动过程中能够形成期望的队形。以Matlab仿真来验证算法的有效性。理论推导及仿真结果说明,导出的编队模型能够准确描述机器人在有打滑情况时的运动规律,二阶滑模编队算法具有较好的抗干扰能力,适用性强。     

数控机床切削用量的模糊控制

阐述了在数控机床上使用模糊控制理论,对切削用量做出合理选择并使其达到最优值的一种方法。首先,利用模糊控制原理,结合数控机床实际,将切削力、毛坯材料、主轴转速、切削温度作为输入,进给速度、背吃刀量作为输出,设计出相应的模糊控制推理框图,展示推理过程;其次,依据推理框图和数控机床输入、输出条件,制订模糊推理规则,提出输入量检测的方法,推导出输入条件和输出条件的隶属度函数并以图形展示,定义输入、输出条件的模糊量子集;最后,根据输入、输出条件和模糊推理规则,构造出模糊控制规则表,实现了采用人类语言、模拟人类思维的控制方式。     

基于非线性优化算法的工业机器人轨迹跟踪自动控制

为完成机器人高效率工业生产任务，提出一种基于非线性优化算法的工业机器人轨迹跟踪自动控制方法。考虑杆件运动重力因素，从角速度、加速度等方面明确工业机器人动力学规律；使用具备非线性优化性质的蚁群算法规划运动轨迹，引入人工势场法计算待选节点和目标节点的间距，评估当前路径是否为最佳路径并更新信息素，输出最优工业机器人运行路线；计算机器人相对功率因数校正控制量，运用粒子群算法求解轨迹跟踪预测控制序列，通过支持向量机构建轨迹跟踪自动控制模型。实验结果表明，所提方法的轨迹跟踪稳定性强、精度高，能满足工业生产的实时动态需求，实用性强。     

模糊自适应PID控制器的设计

本文利用滞环继电反馈控制获取时滞对象的临界参数，按给定相角裕度法整定PID的初值，再结合模糊推理在线整定PID的参数。此整定方法有效地把专家经验应用于PID参数调节中，控制器集模糊控制器和PID控制器的优点于一身。仿真表明：该整定策略系统控制性能得到了很大的改善，是实现自动工业控制器的一种简单．实用的方法。     

基于规则进化模糊系统的步行方向意图识别

为了准确识别下肢功能障碍患者自主步行康复训练过程中的方向意图,提出了一种能够兼顾使用者个体差异及安全状态的新型步行方向意图识别方法。首先论述了康复训练机器人结构及患者前臂对机器人支撑板的压力和步行方向意图的关系。为保证患者安全地向任意方向行走,提出根据膝盖旋转角度推理安全步态的先决条件下,基于距离型模糊推理算法设计具有稀疏前件规则库的步行方向意图识别方法;然后为减小因个体差异、非稳定模糊规则引起的识别误差,提出规则进化算法实时优化模糊推理规则库。最后将该算法进行了多方向模糊推理实验与步行康复训练机器人压力控制实验,实验表明该算法可以准确识别下肢功能患者的任意步行方向意图并提高了步行的安全性,提出的步行方向意图识别方法可以应用在下肢功能障碍人士的日常起居与康复训练中。     

FUZZY MODEL-FOLLOWING ADAPTIVE CONTROL DESIGN FOR ROBOT MANIPULATORS

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Research on intelligent launching control of dual clutch transmissions based on adaptive neural fuzzy inference system

Vehicle launching has an important influence on driving performance of the vehicle. For vehicles with dual clutch transmissions (DCT), the clutch torque control is the key to the launching control. Therefore, a data-driven control method for DCT launching process based on adaptive neural fuzzy inference system (ANFIS) is proposed. Firstly, the vehicle test data during launching process is collected and the optimal clutch torque is obtained based on multi-objective particle swarm optimization (MOPSO). Afterward, to learn the launching control rules from optimization results, the combination of neural network and fuzzy logic algorithm, referred to as an ANFIS, is established. The dataset of the optimized launching clutch torque is utilized to train the ANFIS controller. Finally, the simulation and test results show that the data-driven control can accurately learn the launching control rules from the optimality, thereby achieving the optimal control for different launching intentions.

     

PSO–GSA based fuzzy sliding mode controller for DFIG-based wind turbine

In this paper an optimal fuzzy sliding mode control (FSMC) strategy is introduced for doubly fed induction generator-based wind turbine (DFIG-based WT). The control objective is to ensure power extraction maximization and null stator reactive power regulation according to the grid requirements. To this end, the sliding mode control (SMC) technique is combined with a simple fuzzy inference system to avoid the undesirable chattering phenomenon inherent to the conventional SMC. The proposed FSMC strategy is derived using the Lyapunov approach to guarantee the closed loop system’s stability. To obtain optimal control performances, the membership function parameters of the incorporated fuzzy system are tuned using an improved population-based optimization algorithm, which consists on the combination of particle swarm optimization (PSO) and gravitational search algorithm (GSA). Finally, the performances of the proposed control scheme, called PSO–GSA based FSMC are evaluated in comparison with PSO based FSMC and GSA based FSMC systems.