Microrobots play an essential role in early diagnosis and precision medicine with the increasing demands for controllability in bio-medicine and micromanipulation,which can complete the pre-designed behavior under ext...Microrobots play an essential role in early diagnosis and precision medicine with the increasing demands for controllability in bio-medicine and micromanipulation,which can complete the pre-designed behavior under external stimulation.However,most microrobots are currently made of a single material system and focus on fabricating a driving module as the main structure of microrobots.This hinders the integration of diverse functions in one microrobot to fulfill the complex application.Here,a multi-material and multi-module hand-microrobot based on femtosecond laser direct writing technology is proposed,which has a pH-responsive capturing module and a magnetic-responsive transportation module(MRTM).This microrobot can not only respond to pH for capturing and releasing objects,but also respond to magnetic fields for cargo delivery even with obstacles.The two responding modules of the hand-microrobot are fabricated independently,and can collaborate with each other to achieve the delivery of target objects like polystyrene(PS)microsphere(10µm)or 786-O cell by capturing,transporting,and spatial rolling.Besides,the MRTM can be locally fabricated on any prefabricated static structure,so that the whole microrobot can achieve controllable motion.This strategy is expected to be used to manipulate cells,deliver drugs for precise treatment,and environmental treatment.展开更多
目前已有一些针对路径跟踪控制中信号时滞问题的研究工作,但这些工作大多针对某种特定的控制方法,而在路径跟踪控制方法中,非线性模型预测控制(Nonlinear model predictive control,NMPC)具有能够显式处理系统约束、便于实现多目标优化...目前已有一些针对路径跟踪控制中信号时滞问题的研究工作,但这些工作大多针对某种特定的控制方法,而在路径跟踪控制方法中,非线性模型预测控制(Nonlinear model predictive control,NMPC)具有能够显式处理系统约束、便于实现多目标优化、能够有效利用被控对象前方参考路径信息等优势,但是针对NMPC路径跟踪控制系统中时滞问题的研究较不成熟,制约了这种控制方法的实际应用.为解决上述问题,开展了以下研究工作.首先构建了能够较好地孤立出时滞影响的类车机器人路径跟踪控制系统.接着分析了信号时滞对NMPC路径跟踪控制系统的影响机理,即时滞会导致控制器产生的控制信号不能适应类车机器人在执行控制信号时所处的位置.然后提出了基于增长NMPC预测时域的时滞影响消减方法,即在迭代周期不变的情况下,在无时滞系统较优预测步数的基础上增加二倍时滞周期比以上的整数.最后通过计算机仿真和实验验证了提出方法的有效性.仿真和实验结果表明,信号时滞对NMPC路径跟踪控制系统存在影响,未考虑时滞的NMPC控制算法能够在无时滞系统中实现高精确性路径跟踪,而在有时滞系统中控制失效.通过增长预测时域可以有效消减信号时滞的影响,在信号时滞约为0.2 s的仿真与实验系统中,基于该方法的NMPC控制器可以保证路径跟踪控制的位移误差幅值不超过0.1258 m,航向误差幅值不超过0.0583 rad.展开更多
This paper solves the problem of model-free dual-arm space robot maneuvering after non-cooperative target capture under high control quality requirements.The explicit system model is unavailable,and the maneuvering mi...This paper solves the problem of model-free dual-arm space robot maneuvering after non-cooperative target capture under high control quality requirements.The explicit system model is unavailable,and the maneuvering mission is disturbed by the measurement noise and the target adversarial behavior.To address these problems,a model-free Combined Adaptive-length Datadriven Predictive Controller(CADPC)is proposed.It consists of a separated subsystem identification method and a combined predictive control strategy.The subsystem identification method is composed of an adaptive data length,thereby reducing sensitivity to undetermined measurement noises and disturbances.Based on the subsystem identification,the combined predictive controller is established,reducing calculating resource.The stability of the CADPC is rigorously proven using the Input-to-State Stable(ISS)theorem and the small-gain theorem.Simulations demonstrate that CADPC effectively handles the model-free space robot post operation in the presence of significant disturbances,state measurement noise,and control input errors.It achieves improved steady-state accuracy,reduced steady-state control consumption,and minimized control input chattering.展开更多
基金financial support of the National Key R&D Program of China(Grant Nos.2024YFB4607402 and 2016YFA0200500)National Natural Science Foundation of China(NSFC,Grant Nos.61975213,61475164 and 61205194)International Partnership Program of Chinese Academy of Sciences(GJHZ2021130)。
摘要Microrobots play an essential role in early diagnosis and precision medicine with the increasing demands for controllability in bio-medicine and micromanipulation,which can complete the pre-designed behavior under external stimulation.However,most microrobots are currently made of a single material system and focus on fabricating a driving module as the main structure of microrobots.This hinders the integration of diverse functions in one microrobot to fulfill the complex application.Here,a multi-material and multi-module hand-microrobot based on femtosecond laser direct writing technology is proposed,which has a pH-responsive capturing module and a magnetic-responsive transportation module(MRTM).This microrobot can not only respond to pH for capturing and releasing objects,but also respond to magnetic fields for cargo delivery even with obstacles.The two responding modules of the hand-microrobot are fabricated independently,and can collaborate with each other to achieve the delivery of target objects like polystyrene(PS)microsphere(10µm)or 786-O cell by capturing,transporting,and spatial rolling.Besides,the MRTM can be locally fabricated on any prefabricated static structure,so that the whole microrobot can achieve controllable motion.This strategy is expected to be used to manipulate cells,deliver drugs for precise treatment,and environmental treatment.
基金supported by the National Natural Science Foundation of China(No.12372045)the National Key Research and the Development Program of China(Nos.2023YFC2205900,2023YFC2205901)。
摘要This paper solves the problem of model-free dual-arm space robot maneuvering after non-cooperative target capture under high control quality requirements.The explicit system model is unavailable,and the maneuvering mission is disturbed by the measurement noise and the target adversarial behavior.To address these problems,a model-free Combined Adaptive-length Datadriven Predictive Controller(CADPC)is proposed.It consists of a separated subsystem identification method and a combined predictive control strategy.The subsystem identification method is composed of an adaptive data length,thereby reducing sensitivity to undetermined measurement noises and disturbances.Based on the subsystem identification,the combined predictive controller is established,reducing calculating resource.The stability of the CADPC is rigorously proven using the Input-to-State Stable(ISS)theorem and the small-gain theorem.Simulations demonstrate that CADPC effectively handles the model-free space robot post operation in the presence of significant disturbances,state measurement noise,and control input errors.It achieves improved steady-state accuracy,reduced steady-state control consumption,and minimized control input chattering.