可重构模块机器人构形优化与自抗扰控制方法研究
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摘要
随着机器人技术的不断发展与成熟，现代化高性能机器人的应用领域正在不断扩大。从传统的工业生产、产品制造，到深空、深海探测、危险或恶劣条件作业等方面均有着大量应用与显著成效。与此同时，在一些特定的环境中，固定构形的机器人需要针对具体工作任务，改变相应参数来进行整体设计，以便完成不同的任务。然而，在实际任务中，外界环境经常是未知多变的，如核电站、月球空间站、深海极地研究站等，想要设计一种固定构形的机器人系统用来完成诸多任务是非常困难甚至是不可能的。因此，我们迫切需要一种能够通过改变参数来进行重构，从而能够适应不同任务的机器人。可重构模块机器人即为一类可依据不同任务需要及外界条件的改变而改变自身构形的机器人。通过模块间的重组，可重构模块机器人可以简单快速的装配成不同的构形，以便适应不同的外界环境及任务需要。这种模块的重构包括机械结构的重组以及控制系统的重构。重构后的机器人具备良好的柔性，且能够适应新的工作及任务。可重构模块机器人的研究内容非常丰富，如可重构模块机器人的构形自动生成，优化与评价方法；逆运动学求解方法；模型分解后的不确定性及交联项的处理；故障辨识及容错控制方法等等。因此，对可重构模块机器人进行更为深入的研究有着深远的理论与实际意义。
本文对可重构模块机器人构形自动生成，优化与评价方法进行讨论与研究，并建立了动力学模型。针对机器人动力学轨迹跟踪控制问题提出了基于ESO的反演分散控制方法及基于VGSTA-ESO的滑模分散自抗扰控制方法。全文的主要工作及研究内容如下：
首先，对可重构模块机器人的模块单元进行了划分与设计，并定义了模块链接方式。在此基础上提出了一种新的构形描述方法——构形联结矩阵。通过基于多目标的遗传-模拟退火算法对构形的可达性及位姿最优性进行优化与评价，实现了构形的自动生成，并求出达到任务点的最优解。并采用牛顿-欧拉迭代算法，通过对广义速度、广义加速度进行正向迭代，及广义力的反向迭代可以求得一组迭代形式的牛顿-欧拉方程，由此得出可重构模块机器人的动力学模型。
其次，文中基于Lyapunov稳定性理论和反演技术，提出了一种基于ESO的可重构模块机器人反演滑模分散控制方法。针对可重构模块机器人重复运动性质和非线性强耦合性，基于反演方法设计了滑模分散控制器。由于可重构模块机器人构形频繁变化，求解精确子系统动力学模型是非常困难的，为了解决该问题，利用ESO估计子系统模型不确定项和交联项。通过Lyapunov稳定性理论的证明，确保了系统的稳定性与轨迹跟踪性能。
再次，基于VGSTA算法与自抗扰控制理论，文中提出了一种基于新型ESO的可重构模块机器人滑模分散自抗扰控制方法。该方法不再依赖于固定形式的非线性函数，而是将VGSTA算法与ESO相融合，对系统总体不确定项进行估计，估计误差可以在有限时间内收敛为零。针对可重构模块机器人重复运动性质和非线性强耦合性，通过终端滑模及反演方法设计了滑模分散自抗扰控制器。由于可重构模块机器人构形是不断变化的，因此求解精确的子系统动力学模型非常困难，为了解决该问题，利用新型ESO估计子系统模型不确定项和交联项。通过Lyapunov稳定性理论的证明，确保了新型ESO的稳定性与系统轨迹跟踪性能。并在此基础上，将总体不确定项合理的划分成更为细致的部分，采用不同的方法对每个部分分别进行处理。这种方法不但能够有效的提高系统的响应速度，而且能够更好的跟踪期望轨迹，增强系统的稳定性。通过对两个不同构形的可重构模块机器人的数值仿真，进一步验证了提出的分散自抗扰控制方法的有效性。
最后，作者对全文进行总结，结合自身的研究经验与心得，对今后的研究方向与路线进行了展望。
With the continuous development and maturity of robot technology, the applicationsof modern high-performance robot are expanding. The aspects of traditional industrialproduction, manufacturing, deep space exploration, deep-sea exploration, dangerous andadverse conditions of operations and so on have large numbers of applications withremarkable results. At the same time, in a certain environment, fixed configuration of therobots need to change the corresponding parameters for the specific tasks to the overalldesign in order to perform different tasks. However, the external environment is oftenunknown and varied in the actual task such as nuclear power stations, lunar space station,deep sea polar research station and so on. And the design of a fixed configuration robotsystem which is used to accomplish many tasks is very difficult or even impossible.Therefore, we urgently need a kind of robot which can adapt to different tasks bychanging the parameters to be reconstructed. Reconfigurable manipulator is a kind ofmanipulator which can change its configuration according to the variety of the task orenvironment. Through combine the modules, reconfigurable manipulator can beassembled into a suitable geometric configuration simply and quickly that adapt todifferent tasks. This kind of combination is not only includes a simple mechanicalreconstruction, but also the recombination of control system. After reconstruct, themanipulator is competent for new working environments and tasks, and also possesses agood flexibility. Although the study of reconfigurable modular robot has beenconsiderable part of the outcome, there are still many challenging issues to be furtherin-depth study. Such as the configuration automatically generation, optimization andevaluation methods of reconfigurable modular robot; solving method of inversekinematics; processing of model of the unknown dynamics of subsystem andinterconnection term; fault identification and fault-tolerant control method, and so on. So,there are far-reaching theoretical and practical significance of more in depth study ofreconfigurable modular robot.
In this paper, the problems of reconfigurable modular robots have been researched.Through establishing the dynamic model, automatic generation of reconfigurable modularrobot configuration, optimization and evaluation methods have been discussed. And forthe robot dynamics trajectory tracking control problem, a backstepping decentralizedcontrol method based on ESO and sliding mode decentralized ADRC control methodbased on VGSTA-ESO have been proposed. The full text of the work and research are asfollows:
Firstly, a new multi-objective-based configuration auto-generation, optimization and evaluation method was proposed for reconfigurable modular robot. The modules of robotwere assigned and designed, and the way of module link was defined. Genetic-simulatedannealing algorithm was used for the automatic generation of configuration andmulti-objective optimization. The resulting configuration is described by configurationcoupling matrix. Then base on rigid body Newton-Euler iterative algorithm, a iterativeNewton-Euler function of the system is built by iterative of generalized velocitygeneralized acceleration and inverted iterative of generalized force. The dynamicsfunction of reconfigurable and modular robot is set up.
Secondly, Based on Extended State Observer (ESO) and Lyapunov stability theory, abackstepping sliding mode decentralized control algorithm for reconfigurablemanipulators is proposed. For the nature of repetitive motion and nonlinear strongcoupling of reconfigurable manipulator, the backstepping technology is used to design thesliding mode decentralized controller. Because of the configuration of reconfigurablemanipulator has been changed frequently so that it is very difficult to solve the exactsubsystem dynamics model. ESO is used to model the unknown dynamics of subsystemand the interconnection term can be constructed using the state estimations. The stabilityof system and trajectory tracking performance have been proved by Lyapunov stabilitytheory.
Thirdly, a new ESO based decentralized ADRC control scheme for reconfigurablemanipulators is proposed. This method no longer depends on nonlinear function withfixed form. It combines VGSTA with ESO to estimate the overall uncertainty, and theestimation error can converge to zero in finite time. In view of the nature of repetitivemotion and strong coupling of nonlinear of reconfigurable manipulators, we design adecentralized sliding mode ADRC controller by terminal sliding mode and backsteppingscheme. Because the configuration of reconfigurable manipulators is variable, thus it isdifficult to solve the exact dynamic model of the subsystem. To solve this problem, weuse VGSTA-ESO to estimate the uncertainty items of subsystems and interconnectionterms. By Lyapunov stability theory, we prove that the system of VGSTA-ESO has thestability and tracking performance. This approach will not only effevtively improve thesystem response speed, but also track the desired trajectories better, and enhance thestability of the system. Then, simulation examples are presented to illustrate theeffectiveness of the proposed decentralized ADRC control scheme.
Finally, the results obtained and the lessons learned are summarized, and future workis discussed.
本文对可重构模块机器人构形自动生成，优化与评价方法进行讨论与研究，并建立了动力学模型。针对机器人动力学轨迹跟踪控制问题提出了基于ESO的反演分散控制方法及基于VGSTA-ESO的滑模分散自抗扰控制方法。全文的主要工作及研究内容如下：
首先，对可重构模块机器人的模块单元进行了划分与设计，并定义了模块链接方式。在此基础上提出了一种新的构形描述方法——构形联结矩阵。通过基于多目标的遗传-模拟退火算法对构形的可达性及位姿最优性进行优化与评价，实现了构形的自动生成，并求出达到任务点的最优解。并采用牛顿-欧拉迭代算法，通过对广义速度、广义加速度进行正向迭代，及广义力的反向迭代可以求得一组迭代形式的牛顿-欧拉方程，由此得出可重构模块机器人的动力学模型。
其次，文中基于Lyapunov稳定性理论和反演技术，提出了一种基于ESO的可重构模块机器人反演滑模分散控制方法。针对可重构模块机器人重复运动性质和非线性强耦合性，基于反演方法设计了滑模分散控制器。由于可重构模块机器人构形频繁变化，求解精确子系统动力学模型是非常困难的，为了解决该问题，利用ESO估计子系统模型不确定项和交联项。通过Lyapunov稳定性理论的证明，确保了系统的稳定性与轨迹跟踪性能。
再次，基于VGSTA算法与自抗扰控制理论，文中提出了一种基于新型ESO的可重构模块机器人滑模分散自抗扰控制方法。该方法不再依赖于固定形式的非线性函数，而是将VGSTA算法与ESO相融合，对系统总体不确定项进行估计，估计误差可以在有限时间内收敛为零。针对可重构模块机器人重复运动性质和非线性强耦合性，通过终端滑模及反演方法设计了滑模分散自抗扰控制器。由于可重构模块机器人构形是不断变化的，因此求解精确的子系统动力学模型非常困难，为了解决该问题，利用新型ESO估计子系统模型不确定项和交联项。通过Lyapunov稳定性理论的证明，确保了新型ESO的稳定性与系统轨迹跟踪性能。并在此基础上，将总体不确定项合理的划分成更为细致的部分，采用不同的方法对每个部分分别进行处理。这种方法不但能够有效的提高系统的响应速度，而且能够更好的跟踪期望轨迹，增强系统的稳定性。通过对两个不同构形的可重构模块机器人的数值仿真，进一步验证了提出的分散自抗扰控制方法的有效性。
最后，作者对全文进行总结，结合自身的研究经验与心得，对今后的研究方向与路线进行了展望。
With the continuous development and maturity of robot technology, the applicationsof modern high-performance robot are expanding. The aspects of traditional industrialproduction, manufacturing, deep space exploration, deep-sea exploration, dangerous andadverse conditions of operations and so on have large numbers of applications withremarkable results. At the same time, in a certain environment, fixed configuration of therobots need to change the corresponding parameters for the specific tasks to the overalldesign in order to perform different tasks. However, the external environment is oftenunknown and varied in the actual task such as nuclear power stations, lunar space station,deep sea polar research station and so on. And the design of a fixed configuration robotsystem which is used to accomplish many tasks is very difficult or even impossible.Therefore, we urgently need a kind of robot which can adapt to different tasks bychanging the parameters to be reconstructed. Reconfigurable manipulator is a kind ofmanipulator which can change its configuration according to the variety of the task orenvironment. Through combine the modules, reconfigurable manipulator can beassembled into a suitable geometric configuration simply and quickly that adapt todifferent tasks. This kind of combination is not only includes a simple mechanicalreconstruction, but also the recombination of control system. After reconstruct, themanipulator is competent for new working environments and tasks, and also possesses agood flexibility. Although the study of reconfigurable modular robot has beenconsiderable part of the outcome, there are still many challenging issues to be furtherin-depth study. Such as the configuration automatically generation, optimization andevaluation methods of reconfigurable modular robot; solving method of inversekinematics; processing of model of the unknown dynamics of subsystem andinterconnection term; fault identification and fault-tolerant control method, and so on. So,there are far-reaching theoretical and practical significance of more in depth study ofreconfigurable modular robot.
In this paper, the problems of reconfigurable modular robots have been researched.Through establishing the dynamic model, automatic generation of reconfigurable modularrobot configuration, optimization and evaluation methods have been discussed. And forthe robot dynamics trajectory tracking control problem, a backstepping decentralizedcontrol method based on ESO and sliding mode decentralized ADRC control methodbased on VGSTA-ESO have been proposed. The full text of the work and research are asfollows:
Firstly, a new multi-objective-based configuration auto-generation, optimization and evaluation method was proposed for reconfigurable modular robot. The modules of robotwere assigned and designed, and the way of module link was defined. Genetic-simulatedannealing algorithm was used for the automatic generation of configuration andmulti-objective optimization. The resulting configuration is described by configurationcoupling matrix. Then base on rigid body Newton-Euler iterative algorithm, a iterativeNewton-Euler function of the system is built by iterative of generalized velocitygeneralized acceleration and inverted iterative of generalized force. The dynamicsfunction of reconfigurable and modular robot is set up.
Secondly, Based on Extended State Observer (ESO) and Lyapunov stability theory, abackstepping sliding mode decentralized control algorithm for reconfigurablemanipulators is proposed. For the nature of repetitive motion and nonlinear strongcoupling of reconfigurable manipulator, the backstepping technology is used to design thesliding mode decentralized controller. Because of the configuration of reconfigurablemanipulator has been changed frequently so that it is very difficult to solve the exactsubsystem dynamics model. ESO is used to model the unknown dynamics of subsystemand the interconnection term can be constructed using the state estimations. The stabilityof system and trajectory tracking performance have been proved by Lyapunov stabilitytheory.
Thirdly, a new ESO based decentralized ADRC control scheme for reconfigurablemanipulators is proposed. This method no longer depends on nonlinear function withfixed form. It combines VGSTA with ESO to estimate the overall uncertainty, and theestimation error can converge to zero in finite time. In view of the nature of repetitivemotion and strong coupling of nonlinear of reconfigurable manipulators, we design adecentralized sliding mode ADRC controller by terminal sliding mode and backsteppingscheme. Because the configuration of reconfigurable manipulators is variable, thus it isdifficult to solve the exact dynamic model of the subsystem. To solve this problem, weuse VGSTA-ESO to estimate the uncertainty items of subsystems and interconnectionterms. By Lyapunov stability theory, we prove that the system of VGSTA-ESO has thestability and tracking performance. This approach will not only effevtively improve thesystem response speed, but also track the desired trajectories better, and enhance thestability of the system. Then, simulation examples are presented to illustrate theeffectiveness of the proposed decentralized ADRC control scheme.
Finally, the results obtained and the lessons learned are summarized, and future workis discussed.
引文
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