串联机器人多目标轨迹优化与运动控制研究
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摘要
随着我国工业自动化水平的不断提高,工业机器人的安装量迅猛增长,应用领域日益广泛,工业机器人已经成为一种标准的设备在工业现场得到了广泛的应用。据专家预测,国内工业机器人的安装量将以每年25%的速度递增。然而国内的机器人市场的基本都被国外公司,如ABB、FANUC、YASKAWA、MOTOMAN、KUKA、AdeptTechnology、COMAU等所垄断,国产机器人市场份额不到1%,且在运动速度、精度和可靠性等方面与国外同类产品相比存在较大差距。同时机器人技术是机械、电子、计算机、控制、信息、人工智能、仿生等多学科知识交叉融合的高新技术,理论研究也非常活跃。因此立足国内基础,研究机器人的通用共性技术和重点关键技术,尤其是研究高速高精度运动的相关理论及技术,一方面可以在理论上提高我国机器人研究的水平,另一方面在技术上促进我国工业机器人的整体性能的提高。
本文以自行研制SCARA (Selective Compliance Assembly Robot Arm选择顺应性装配机械臂)机器人为研究对象,以信号分析技术、现代控制理论、系统辨识技术及非线性动力学等多学科交叉为基础,采用理论分析、数值仿真和实验验证相结合的方法,开展工业机器人多目标轨迹优化及高性能运动控制相关研究工作。在系统实现方面,立足国内现有的技术基础,尝试了全部使用国产的器件,通过系统优化及软件算法弥补器件本身的缺陷,保证机器人整体性能。在控制系统设计方面,主控制器采用了ARM9平台,移植Linux操作系统,完成人机交互与运动规划,运动控制器采用了DSP+CPLD架构,完成插补与运动控制,一方面降低了成本,另一方面提高系统的稳定性。在结构设计方面上,选用国产谐波减速器组件,设计传动、抗弯、对心机构,通过高级运动控制算法补偿谐波减速器本身非线性摩擦等因素。在理论研究方面针对机器人高速、高精度运动性能,分别从运动规划、运动控制、柔性关节控制等方面展开相关研究,最终当机器人各关节最大运动速度在额定转速90%以上时,跟踪精度达到传感器分辨率的10倍以内,最终在SCARA机器人上得到的各关节平均跟踪误差小于0.005°,单关节的平均跟踪误差甚至达到了0.003°,为高性能国产化工业机器人的实现在关键理论技术和整机开发实践上做出了相应的探索。
本论文共分七章,主要的研究内容如下：
第一章,介绍了课题的研究背景,调研了国外先进机器人的相关产品及技术包括工业机器人技术上的最新进展,分析了国内工业机器人技术及产业发展的现状。在查阅相关文献的基础上,从机构优化、控制系统、轨迹规划、运动控制、柔性关节等方面对机器人理论研究现状进行了综述。最后阐明了本课题来源及研究内容。
第二章,介绍自行研制SCARA机器人的系统实现及关键技术,包括了结构设计、控制系统、驱动系统等。在结构上,采用谐波减速器组件,设计相应的传动、抗弯及对中机构。在控制系统架构上,基于ARM9平台设计示教规划器,并在Linux系统下开发相应的人机交互界面及运动规划算法,完成机器人示教规划功能,基于DSP设计运动控制器,完成运动插补及高速、高精度运动控制算法,实现了完全国产化的低成本的样机设计。
第三章,研究机器人多目标轨迹优化算法。首先采用高次B样条曲线,构造关节空间高阶连续轨迹,保证机器人关节的运动的连续性和启停运动参数的可配置性,并根据B样条曲线的凸包性质,将关节运动学约束转换为B样条曲线的控制顶点约束。以运动时间最短、轨迹最平滑、能耗最小,驱动力矩变化最小等指标为优化目标,采用改进NSGA-Ⅱ求解多目标优化的轨迹,得到了Pareto最优解集,为用户提供一组优化的解集,并在通用的六自由度机器人上进行研究分析。结果表明,与单目标优化算法相比,在另外的一个或几个目标的优化值近似的情况下,就比较的目标而言,多目标优化算法得到的优化结果更好。
第四章,研究了机器人的无模型控制算法。首先在PID控制的基础上提出了监督自适应PID控制算法,其中自适应PID部分使可达性条件最小,保证滑模态的发生,同时设计监督控制部分保证系统的稳定性。在此基础上设计监督自适应RBF网络控制算法,采用RBF网络逼近系统的理想控制器,采用同样的方法设计自适应律及监督控制器。提出了鲁棒PID输出反馈控制算法,在PD控制的基础上,设计非线性积分控制部分,提高系统的动态响应性能和鲁棒性,同时设计观测器,避免位置微分带来的高频噪声干扰,仿真及实验结果在不需要机器人模型参数信息的情况下,取得了较好的控制性能。
第五章,研究机器人模型参数辨识及基于模型信息的鲁棒自适应控制算法。首先建立机器人动力学模型并线性化,进一步考虑机器人动态约束,设计优化的激励轨迹,以充分激励机器人的动力学特性,减少系统辨识数值解带来的误差,采用极大似然参数估计算法,得到精确的参数辨识结果,仿真及实验结果表明辨识算法的有效性。进一步基于模型设计控制算法,考虑了谐波驱动的位置相关摩擦,采用未知参数的正余弦函数结合的形式表征位置相关摩擦,在期望补偿自适应鲁棒控制算法基础上,针对自适应律学习“慢”的局限性,提出改进自适应鲁棒控制算法,将积分型参数估计改为比例积分型参数估计,有效的抑制了系统的高频干扰。单关节及多关节机器人轨迹跟踪实验,得到了良好的跟踪性能。
第六章,针对谐波驱动机器人的柔性关节控制问题,提出了动态面backstepping控制算法及饱和模糊动态面backstepping控制算法。首先采用传统backstepping设计柔性关节控制器,进一步设计动态面backstepping控制器,采用动态面技术,引入一阶低通滤波器估计backstepping方法所设计的虚拟控制律,避免了对虚拟控制量的多次求导,解决了backstepping方法所引起的“计算膨胀”问题。在此基础上,考虑到力矩输出的受限问题,设计饱和模糊动态面backstepping控制算法,采用模糊系统逼近饱和非线性,提高系统在力矩受限情况下的跟踪精度。
第七章,总结了论文的主要研究工作、结论及创新点,并对以后的研究工作做了展望。
With the remarkable improvement of domestic industrial automation, robot manipulator installations are increasing greatly in our country, the robot manipulators have become standard equipments and have been widely used in the industrial fields. Experts predict that the amount of domestic robot manipulators will be increased by 25% every year. However, some foreign companies, such as ABB, FANUC, YASKAWA, MOTOMAN, KUKA, AdeptTechnology, COMAU, etc. have an overwhelmingly large share of our market while domestic companies have less than 1%. Moreover, there is a big gap of these likewise products between China and other countries on the performance such as speed, accuracy, reliability etc. The technology of robot manipulator is a cross-disciplinary integration, including mechanical, electronic, computer, control, information, artificial intelligence, bionics and other of high-tech field. The theoretical research of robot manipulators is very active. Hence, based on the domestic technological foundation, deep research on the general technology and the key technology of robot manipulators especially the research on the high-speed and high-precision technology can not only improve the theory research level of robot, but also will promote the overall technology of robot manipulators in China.
This dissertation addresses the study of our self-made SCARA (Selective Compliance Assembly Robot Arm) robot. Based on the knowledge of many disciplinary, such as signal analysis, modern control, system identification, nonlinear system and so on, with the help of combination of theoretical analysis, numerical simulation and experimental validation, high-speed and high-precision motion of robot manipulators and its related area are studied. For the system realization, based on the domestic existing technology, the robot manipulator design use all the domestic devices, and in order to guarantee the overall performance of the robot manipulator, The system design is optimized and advanced control algorithms are adopted to compensate for the lower performance of the devices themselves. In the electric system, ARM9 platform with Linux embedded are adopted in the design of main controller to realize human-computer interaction and motion planning. DSP+CPLD platform is used for the motion controller. These will help to reduce the cost and improve the stability of the system. In the design of mechanical structure, domestic harmonic reducer has been chosen, and corresponding transmission, bending and centering device are designed. With the help of advanced motion control algorithms, the flexibility and nonlinear friction factors of harmonic reducer are compensated. To obtain high-speed and high-precision motion performance of robot manipulator, some theory such as motion planning, motion control and flexible joints control, etc. are discussed. The maximum speed of each joint has reached more than 90% of the rated speed of robot manipulator, the tracking accuracy still reach less than 10 times of the sensor precision. Eventually the tracking error on each joint is less than 0.005°for multi-axis motion control and even less than 0.003°for uniaxial motion control. Such work is a exploration in realizing high-performance localized robot manipulator on the key technologies and the practice of overall unit.
This dissertation is divided into seven chapters, the main contents are as follows:
The first chapter introduces the research background, research topics related to the foreign advanced robot products and industrial robot technology, analyzes the latest progress of domestic robot manipulators and the present situation of the technology and industry. Literatures of the robot theories, including structural optimization, control system, trajectory planning, motion control and flexible joints, are reviewed. At last the support and the background of this research are clarified.
In chapterⅡ, the system realization and key technologies of the self-made SCARA robot are introduced, including the structure design, control system and drive system, etc. In the structure design, harmonic reducer components are adopted, corresponding transmission, bending and centering device are designed. In the control system, Teaching and planning system based on ARM9 platform is designed, and corresponding human-machine interface and motion planning algorithm are developed under Linux system, the function of robot demonstration and teaching planning are completed. Motion interpolation, high-speed and high-accuracy motion control algorithm are implemented on motion controller based on DSP. At last low cost prototype design are completed.
In chapterⅢ, the multi-objective trajectory optimization for manipulators is studied. The high degree B-splines are adopted to construct a continuous trajectory in joint space which guarantees the continuity of motion, as well as free configuration of motion parameters of starts and stops. According to the convex-hull property, kinematic constraints are transformed to the constraints on control points of B-splines. With minimum time, smooth trajectory, lowest energy consumption and the least torque variation as our optimizing objectives, firstly, the improved non-dominated sorting genetic algorithm-Ⅱ(NSGA-Ⅱ)is applied, then the Pareto optimization solution set is obtained, which provided many choices for users. The results on the general six degrees of freedom manipulator show that compared with the single-objective optimizations, the multi-objective optimization algorithm is better.
In chapter IV, some model free controllers are studied for trajectory tracking of robot manipulators. Firstly, a supervisory adaptive PID controller is proposed based on the traditional PID controller. Then the adaptive PID algorithm is designed to minimize the accessibility conditions to precipitate the sliding mode occur. At the same time, a supervisory adaptive RBF neural network controller is presented, the RBF neural network approximates the ideal controller and the supervisory controller guarantees the system stability. Then a robust nonlinear PID output feedback controller is designed. The PD part stabilizes the system, the nonlinear integration part is designed to improve the dynamic response and the robustness. A linear observer is proposed to estimate the actual joint velocity to avoid the high frequency disturbance generated by differential computing the position value. The experimental and simulation results show that the controller can achieve the favorable tracking performance without the model parameter information.
In chapter V, the research is focused on the parameter identification and adaptive robust control based on the model information. Firstly, the dynamic model of the robot manipulator is constructed and linearized. Then in consideration of the dynamic constraints, the optimized exciting trajectory is designed to excite the dynamic characteristics of the manipulator, so as to reduce the identification error, and the maximum likelihood method is used to get the precise parameters. It's shown that the proposed technique is effective according to the simulation and experimental results. A controller based on the model is proposed, position-dependent friction is expressed as the combining sine and cosine function with unknown coefficient, based on the desired compensation adaptive robust control, an improved adaptive robust control (IARC) is proposed. The controller replaces the integral parametric estimations law with the proportional-integral parametric estimations law considering the "slow" learning rate to suppress the high-frequency noise. The experimental results on the single-joint and multi-joint manipulator show that the controller can achieve good tracking performance.
In Chapter VI, dynamic surface backstepping control and saturated fuzzy dynamic surface backstepping control are proposed to deal with the flexible joint robot derived by harmonic gear reducer. Firstly, the traditional backstepping controller is designed for the flexible joint, and then the dynamic surface technique is introduced to design the dynamic surface backstepping controller. A first-order low-pass filter is proposed to approximate the virtual controller generated by backstepping so as to avoid the derivation of the controller. Thus the problem of 'explosion of complexity'in backstepping design procedure is solved. Based on the controller a saturated fuzzy dynamic surface backstepping controller is proposed to deal with the problem of limited torque, fuzzy system is used to approach the saturation nonlinearity to improve tracking precision under the limited torque.
In chapter VII, the main work, results and innovations of the thesis are summarized. And the future research is also prospected.
本文以自行研制SCARA (Selective Compliance Assembly Robot Arm选择顺应性装配机械臂)机器人为研究对象,以信号分析技术、现代控制理论、系统辨识技术及非线性动力学等多学科交叉为基础,采用理论分析、数值仿真和实验验证相结合的方法,开展工业机器人多目标轨迹优化及高性能运动控制相关研究工作。在系统实现方面,立足国内现有的技术基础,尝试了全部使用国产的器件,通过系统优化及软件算法弥补器件本身的缺陷,保证机器人整体性能。在控制系统设计方面,主控制器采用了ARM9平台,移植Linux操作系统,完成人机交互与运动规划,运动控制器采用了DSP+CPLD架构,完成插补与运动控制,一方面降低了成本,另一方面提高系统的稳定性。在结构设计方面上,选用国产谐波减速器组件,设计传动、抗弯、对心机构,通过高级运动控制算法补偿谐波减速器本身非线性摩擦等因素。在理论研究方面针对机器人高速、高精度运动性能,分别从运动规划、运动控制、柔性关节控制等方面展开相关研究,最终当机器人各关节最大运动速度在额定转速90%以上时,跟踪精度达到传感器分辨率的10倍以内,最终在SCARA机器人上得到的各关节平均跟踪误差小于0.005°,单关节的平均跟踪误差甚至达到了0.003°,为高性能国产化工业机器人的实现在关键理论技术和整机开发实践上做出了相应的探索。
本论文共分七章,主要的研究内容如下：
第一章,介绍了课题的研究背景,调研了国外先进机器人的相关产品及技术包括工业机器人技术上的最新进展,分析了国内工业机器人技术及产业发展的现状。在查阅相关文献的基础上,从机构优化、控制系统、轨迹规划、运动控制、柔性关节等方面对机器人理论研究现状进行了综述。最后阐明了本课题来源及研究内容。
第二章,介绍自行研制SCARA机器人的系统实现及关键技术,包括了结构设计、控制系统、驱动系统等。在结构上,采用谐波减速器组件,设计相应的传动、抗弯及对中机构。在控制系统架构上,基于ARM9平台设计示教规划器,并在Linux系统下开发相应的人机交互界面及运动规划算法,完成机器人示教规划功能,基于DSP设计运动控制器,完成运动插补及高速、高精度运动控制算法,实现了完全国产化的低成本的样机设计。
第三章,研究机器人多目标轨迹优化算法。首先采用高次B样条曲线,构造关节空间高阶连续轨迹,保证机器人关节的运动的连续性和启停运动参数的可配置性,并根据B样条曲线的凸包性质,将关节运动学约束转换为B样条曲线的控制顶点约束。以运动时间最短、轨迹最平滑、能耗最小,驱动力矩变化最小等指标为优化目标,采用改进NSGA-Ⅱ求解多目标优化的轨迹,得到了Pareto最优解集,为用户提供一组优化的解集,并在通用的六自由度机器人上进行研究分析。结果表明,与单目标优化算法相比,在另外的一个或几个目标的优化值近似的情况下,就比较的目标而言,多目标优化算法得到的优化结果更好。
第四章,研究了机器人的无模型控制算法。首先在PID控制的基础上提出了监督自适应PID控制算法,其中自适应PID部分使可达性条件最小,保证滑模态的发生,同时设计监督控制部分保证系统的稳定性。在此基础上设计监督自适应RBF网络控制算法,采用RBF网络逼近系统的理想控制器,采用同样的方法设计自适应律及监督控制器。提出了鲁棒PID输出反馈控制算法,在PD控制的基础上,设计非线性积分控制部分,提高系统的动态响应性能和鲁棒性,同时设计观测器,避免位置微分带来的高频噪声干扰,仿真及实验结果在不需要机器人模型参数信息的情况下,取得了较好的控制性能。
第五章,研究机器人模型参数辨识及基于模型信息的鲁棒自适应控制算法。首先建立机器人动力学模型并线性化,进一步考虑机器人动态约束,设计优化的激励轨迹,以充分激励机器人的动力学特性,减少系统辨识数值解带来的误差,采用极大似然参数估计算法,得到精确的参数辨识结果,仿真及实验结果表明辨识算法的有效性。进一步基于模型设计控制算法,考虑了谐波驱动的位置相关摩擦,采用未知参数的正余弦函数结合的形式表征位置相关摩擦,在期望补偿自适应鲁棒控制算法基础上,针对自适应律学习“慢”的局限性,提出改进自适应鲁棒控制算法,将积分型参数估计改为比例积分型参数估计,有效的抑制了系统的高频干扰。单关节及多关节机器人轨迹跟踪实验,得到了良好的跟踪性能。
第六章,针对谐波驱动机器人的柔性关节控制问题,提出了动态面backstepping控制算法及饱和模糊动态面backstepping控制算法。首先采用传统backstepping设计柔性关节控制器,进一步设计动态面backstepping控制器,采用动态面技术,引入一阶低通滤波器估计backstepping方法所设计的虚拟控制律,避免了对虚拟控制量的多次求导,解决了backstepping方法所引起的“计算膨胀”问题。在此基础上,考虑到力矩输出的受限问题,设计饱和模糊动态面backstepping控制算法,采用模糊系统逼近饱和非线性,提高系统在力矩受限情况下的跟踪精度。
第七章,总结了论文的主要研究工作、结论及创新点,并对以后的研究工作做了展望。
With the remarkable improvement of domestic industrial automation, robot manipulator installations are increasing greatly in our country, the robot manipulators have become standard equipments and have been widely used in the industrial fields. Experts predict that the amount of domestic robot manipulators will be increased by 25% every year. However, some foreign companies, such as ABB, FANUC, YASKAWA, MOTOMAN, KUKA, AdeptTechnology, COMAU, etc. have an overwhelmingly large share of our market while domestic companies have less than 1%. Moreover, there is a big gap of these likewise products between China and other countries on the performance such as speed, accuracy, reliability etc. The technology of robot manipulator is a cross-disciplinary integration, including mechanical, electronic, computer, control, information, artificial intelligence, bionics and other of high-tech field. The theoretical research of robot manipulators is very active. Hence, based on the domestic technological foundation, deep research on the general technology and the key technology of robot manipulators especially the research on the high-speed and high-precision technology can not only improve the theory research level of robot, but also will promote the overall technology of robot manipulators in China.
This dissertation addresses the study of our self-made SCARA (Selective Compliance Assembly Robot Arm) robot. Based on the knowledge of many disciplinary, such as signal analysis, modern control, system identification, nonlinear system and so on, with the help of combination of theoretical analysis, numerical simulation and experimental validation, high-speed and high-precision motion of robot manipulators and its related area are studied. For the system realization, based on the domestic existing technology, the robot manipulator design use all the domestic devices, and in order to guarantee the overall performance of the robot manipulator, The system design is optimized and advanced control algorithms are adopted to compensate for the lower performance of the devices themselves. In the electric system, ARM9 platform with Linux embedded are adopted in the design of main controller to realize human-computer interaction and motion planning. DSP+CPLD platform is used for the motion controller. These will help to reduce the cost and improve the stability of the system. In the design of mechanical structure, domestic harmonic reducer has been chosen, and corresponding transmission, bending and centering device are designed. With the help of advanced motion control algorithms, the flexibility and nonlinear friction factors of harmonic reducer are compensated. To obtain high-speed and high-precision motion performance of robot manipulator, some theory such as motion planning, motion control and flexible joints control, etc. are discussed. The maximum speed of each joint has reached more than 90% of the rated speed of robot manipulator, the tracking accuracy still reach less than 10 times of the sensor precision. Eventually the tracking error on each joint is less than 0.005°for multi-axis motion control and even less than 0.003°for uniaxial motion control. Such work is a exploration in realizing high-performance localized robot manipulator on the key technologies and the practice of overall unit.
This dissertation is divided into seven chapters, the main contents are as follows:
The first chapter introduces the research background, research topics related to the foreign advanced robot products and industrial robot technology, analyzes the latest progress of domestic robot manipulators and the present situation of the technology and industry. Literatures of the robot theories, including structural optimization, control system, trajectory planning, motion control and flexible joints, are reviewed. At last the support and the background of this research are clarified.
In chapterⅡ, the system realization and key technologies of the self-made SCARA robot are introduced, including the structure design, control system and drive system, etc. In the structure design, harmonic reducer components are adopted, corresponding transmission, bending and centering device are designed. In the control system, Teaching and planning system based on ARM9 platform is designed, and corresponding human-machine interface and motion planning algorithm are developed under Linux system, the function of robot demonstration and teaching planning are completed. Motion interpolation, high-speed and high-accuracy motion control algorithm are implemented on motion controller based on DSP. At last low cost prototype design are completed.
In chapterⅢ, the multi-objective trajectory optimization for manipulators is studied. The high degree B-splines are adopted to construct a continuous trajectory in joint space which guarantees the continuity of motion, as well as free configuration of motion parameters of starts and stops. According to the convex-hull property, kinematic constraints are transformed to the constraints on control points of B-splines. With minimum time, smooth trajectory, lowest energy consumption and the least torque variation as our optimizing objectives, firstly, the improved non-dominated sorting genetic algorithm-Ⅱ(NSGA-Ⅱ)is applied, then the Pareto optimization solution set is obtained, which provided many choices for users. The results on the general six degrees of freedom manipulator show that compared with the single-objective optimizations, the multi-objective optimization algorithm is better.
In chapter IV, some model free controllers are studied for trajectory tracking of robot manipulators. Firstly, a supervisory adaptive PID controller is proposed based on the traditional PID controller. Then the adaptive PID algorithm is designed to minimize the accessibility conditions to precipitate the sliding mode occur. At the same time, a supervisory adaptive RBF neural network controller is presented, the RBF neural network approximates the ideal controller and the supervisory controller guarantees the system stability. Then a robust nonlinear PID output feedback controller is designed. The PD part stabilizes the system, the nonlinear integration part is designed to improve the dynamic response and the robustness. A linear observer is proposed to estimate the actual joint velocity to avoid the high frequency disturbance generated by differential computing the position value. The experimental and simulation results show that the controller can achieve the favorable tracking performance without the model parameter information.
In chapter V, the research is focused on the parameter identification and adaptive robust control based on the model information. Firstly, the dynamic model of the robot manipulator is constructed and linearized. Then in consideration of the dynamic constraints, the optimized exciting trajectory is designed to excite the dynamic characteristics of the manipulator, so as to reduce the identification error, and the maximum likelihood method is used to get the precise parameters. It's shown that the proposed technique is effective according to the simulation and experimental results. A controller based on the model is proposed, position-dependent friction is expressed as the combining sine and cosine function with unknown coefficient, based on the desired compensation adaptive robust control, an improved adaptive robust control (IARC) is proposed. The controller replaces the integral parametric estimations law with the proportional-integral parametric estimations law considering the "slow" learning rate to suppress the high-frequency noise. The experimental results on the single-joint and multi-joint manipulator show that the controller can achieve good tracking performance.
In Chapter VI, dynamic surface backstepping control and saturated fuzzy dynamic surface backstepping control are proposed to deal with the flexible joint robot derived by harmonic gear reducer. Firstly, the traditional backstepping controller is designed for the flexible joint, and then the dynamic surface technique is introduced to design the dynamic surface backstepping controller. A first-order low-pass filter is proposed to approximate the virtual controller generated by backstepping so as to avoid the derivation of the controller. Thus the problem of 'explosion of complexity'in backstepping design procedure is solved. Based on the controller a saturated fuzzy dynamic surface backstepping controller is proposed to deal with the problem of limited torque, fuzzy system is used to approach the saturation nonlinearity to improve tracking precision under the limited torque.
In chapter VII, the main work, results and innovations of the thesis are summarized. And the future research is also prospected.
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