Flight simulator is an important device and a typical high-performance position and speed servo system used in the hardware-in-the-loop simulation of flight control system. Friction is the main nonlinear resistance in...Flight simulator is an important device and a typical high-performance position and speed servo system used in the hardware-in-the-loop simulation of flight control system. Friction is the main nonlinear resistance in the flight simulator servo system, especially in a low-speed state. Based on the description of dynamic and static models of a nonlinear Stribeck friction model, this paper puts forward sliding mode controller to overcome the friction, whose stability is展开更多
A new type of piezoelectric electro-hydraulic servo valve system was proposed. And then multilayer piezoelectric actuator based on new piezoelectric ceramic material was used as the electricity-machine converter of th...A new type of piezoelectric electro-hydraulic servo valve system was proposed. And then multilayer piezoelectric actuator based on new piezoelectric ceramic material was used as the electricity-machine converter of the proposed piezoelectric electro-hydraulic servo valve. The proposed piezoelectric electro-hydraulic servo valve has ascendant performance compared with conventional ones. But the system is of high nonlinearity and uncertainty, it cannot achieve favorable control performance by conventional control method. To develop an efficient way to control piezoelectric electro-hydraulic servo valve system, a high-precise fuzzy control method with hysteresis nonlinear model in feedforward loop was proposed. The control method is separated into two parts: a feedforward loop with Preisach hysteresis nonlinear model and a feedback loop with high-precise fuzzy control. Experimental results show that the hysteresis loop and the maximum output hysteresis by the PID control method are 4.22% and 2.11 μm, respectively; the hysteresis loop and the maximum output hysteresis by the proposed control method respectively are 0.74% and 0.37 μm, respectively; the maximum tracking error by the PID control method for sine wave reference signal is about 5.02%, the maximum tracking error by the proposed control method for sine wave reference signal is about 0.85%.展开更多
针对在GPS信号弱/拒止和环境感知欠缺的环境下可重构海洋浮体的协同控制问题,本文提出了一种基于定相对位姿(Determined relative pose,DRP)视觉伺服模型的鲁棒非线性模型预测控制(Nonlinear model predictive control,NMPC)方案。可重...针对在GPS信号弱/拒止和环境感知欠缺的环境下可重构海洋浮体的协同控制问题,本文提出了一种基于定相对位姿(Determined relative pose,DRP)视觉伺服模型的鲁棒非线性模型预测控制(Nonlinear model predictive control,NMPC)方案。可重构海洋浮体的视觉伺服问题难点主要包括环境干扰强、系统非线性程度高、视觉伺服易陷入局部极值和可见性约束强。为应对这些难题,该视觉伺服控制策略需要实现:被控船仅依靠视觉信息进行多船协同控制;视觉伺服模型收敛性好;控制器具有一定鲁棒性且处理非线性系统和约束条件的能力强。为此,本研究首先建立了单浮体的动力学模型;然后将视觉模型、被控船艏摇信息及相机云台转角信息整合到系统状态中,形成了DRP模型,从而保证了双浮体视觉伺服控制结束后相对位姿的唯一性;接着结合浮体动力学模型和DRP模型,建立了基于图像的视觉伺服(Image based visual servo,IBVS)的系统模型,并对该系统模型进行分析,进而据此设计了鲁棒的NMPC控制器,以保证视觉伺服任务可以在强外界干扰的环境下进行;最后通过大量数值仿真实验验证了该方案的有效性。这些实验结果不仅证明了控制策略的稳定性和准确性,还展示了其在复杂环境下的鲁棒性能。展开更多
机器人和数控机床等高端机械用位置伺服系统的定位性能易受摩擦力矩等干扰的影响,对此提出了一种基于改进粒子群算法(particle swarm optimization algorithm with improved particle velocity and position update formula,IPSO-VP)的...机器人和数控机床等高端机械用位置伺服系统的定位性能易受摩擦力矩等干扰的影响,对此提出了一种基于改进粒子群算法(particle swarm optimization algorithm with improved particle velocity and position update formula,IPSO-VP)的伺服系统摩擦参数辨识及前馈补偿方法。首先,分析并建立基于Stribeck的摩擦模型,在传统粒子群算法(PSO)的基础上,提出了一种基于改进粒子群算法(IPSO-VP)的摩擦参数辨识方法,该方法采用一种新的基于粒子维度信息的位置和速度自适应更新策略,以及一种新的基于Logistic混沌非线性变化惯性权重对模型参数进行辨识;其次,基于辨识获得的摩擦力矩值,将其前馈补偿到伺服系统交轴电流上以补偿摩擦力矩。为了验证算法的有效性,搭建系统进行了测试,结果表明相较于基于传统粒子群算法(PSO)的参数辨识方法,采用基于改进粒子群算法(IPSO-VP)的系统,其参数的辨识精度和迭代收敛速度更高,从而提高了机器人和数控机床等用伺服系统的跟踪控制性能和鲁棒性。展开更多
基金This project was supported by the Aeronautics Foundation of China (00E21022).
文摘Flight simulator is an important device and a typical high-performance position and speed servo system used in the hardware-in-the-loop simulation of flight control system. Friction is the main nonlinear resistance in the flight simulator servo system, especially in a low-speed state. Based on the description of dynamic and static models of a nonlinear Stribeck friction model, this paper puts forward sliding mode controller to overcome the friction, whose stability is
基金Project(2001AA423270) supported by the National High-Tech Research and Development Program of ChinaProject (2005037185) supported by the Postdoctoral Science Foundation of China
文摘A new type of piezoelectric electro-hydraulic servo valve system was proposed. And then multilayer piezoelectric actuator based on new piezoelectric ceramic material was used as the electricity-machine converter of the proposed piezoelectric electro-hydraulic servo valve. The proposed piezoelectric electro-hydraulic servo valve has ascendant performance compared with conventional ones. But the system is of high nonlinearity and uncertainty, it cannot achieve favorable control performance by conventional control method. To develop an efficient way to control piezoelectric electro-hydraulic servo valve system, a high-precise fuzzy control method with hysteresis nonlinear model in feedforward loop was proposed. The control method is separated into two parts: a feedforward loop with Preisach hysteresis nonlinear model and a feedback loop with high-precise fuzzy control. Experimental results show that the hysteresis loop and the maximum output hysteresis by the PID control method are 4.22% and 2.11 μm, respectively; the hysteresis loop and the maximum output hysteresis by the proposed control method respectively are 0.74% and 0.37 μm, respectively; the maximum tracking error by the PID control method for sine wave reference signal is about 5.02%, the maximum tracking error by the proposed control method for sine wave reference signal is about 0.85%.
文摘针对在GPS信号弱/拒止和环境感知欠缺的环境下可重构海洋浮体的协同控制问题,本文提出了一种基于定相对位姿(Determined relative pose,DRP)视觉伺服模型的鲁棒非线性模型预测控制(Nonlinear model predictive control,NMPC)方案。可重构海洋浮体的视觉伺服问题难点主要包括环境干扰强、系统非线性程度高、视觉伺服易陷入局部极值和可见性约束强。为应对这些难题,该视觉伺服控制策略需要实现:被控船仅依靠视觉信息进行多船协同控制;视觉伺服模型收敛性好;控制器具有一定鲁棒性且处理非线性系统和约束条件的能力强。为此,本研究首先建立了单浮体的动力学模型;然后将视觉模型、被控船艏摇信息及相机云台转角信息整合到系统状态中,形成了DRP模型,从而保证了双浮体视觉伺服控制结束后相对位姿的唯一性;接着结合浮体动力学模型和DRP模型,建立了基于图像的视觉伺服(Image based visual servo,IBVS)的系统模型,并对该系统模型进行分析,进而据此设计了鲁棒的NMPC控制器,以保证视觉伺服任务可以在强外界干扰的环境下进行;最后通过大量数值仿真实验验证了该方案的有效性。这些实验结果不仅证明了控制策略的稳定性和准确性,还展示了其在复杂环境下的鲁棒性能。
文摘机器人和数控机床等高端机械用位置伺服系统的定位性能易受摩擦力矩等干扰的影响,对此提出了一种基于改进粒子群算法(particle swarm optimization algorithm with improved particle velocity and position update formula,IPSO-VP)的伺服系统摩擦参数辨识及前馈补偿方法。首先,分析并建立基于Stribeck的摩擦模型,在传统粒子群算法(PSO)的基础上,提出了一种基于改进粒子群算法(IPSO-VP)的摩擦参数辨识方法,该方法采用一种新的基于粒子维度信息的位置和速度自适应更新策略,以及一种新的基于Logistic混沌非线性变化惯性权重对模型参数进行辨识;其次,基于辨识获得的摩擦力矩值,将其前馈补偿到伺服系统交轴电流上以补偿摩擦力矩。为了验证算法的有效性,搭建系统进行了测试,结果表明相较于基于传统粒子群算法(PSO)的参数辨识方法,采用基于改进粒子群算法(IPSO-VP)的系统,其参数的辨识精度和迭代收敛速度更高,从而提高了机器人和数控机床等用伺服系统的跟踪控制性能和鲁棒性。
