The micromation and precision of the Micro-Electromechanical System demand that its manufacturing, measuring and assembling must work in a micro-manufacturing platform with good ability to isolate vibrations. This pap...The micromation and precision of the Micro-Electromechanical System demand that its manufacturing, measuring and assembling must work in a micro-manufacturing platform with good ability to isolate vibrations. This paper develops a vibration isolation system of micro-manufacturing platform. The brains of many kinds of birds can isolate vibrations well, such as woodpecker’s brain. When a woodpecker pecks the wood at the speed as 1.6 times as the velocity of sound, its brain will tolerate the wallop 1 500 times of the weight of itself without any damage. The isolation mechanics and organic texture of woodpecker’s brain that has good isolation characteristics were studied. A structure model of vibration isolation system for the micro-manufacturing platform is established based on the bionics of the bird’s brain vibration isolation mechanism. In order to isolate effectively the high frequency vibrations from the ground, a rubber layer is used to isolate vibrations passively between the micro-manufacturing platform’s pedestal and the ground. This layer corresponds to the cartilage and muscles in the outer meninges of the bird’s brain. The active vibration isolation technique is adopted to isolate vibrations between the micro-manufacturing platform and the pedestal. Air springs are used as elastic components, which correspond to the interspaces between the outer meninges and the encephala of the bird’s brain. Actuators are made of giant magnetostrictive material, and it corresponds to the nerves and neural muscles linking the meninges and the encephala. The actuators and air springs are arranged vertically in parallel to make use of the giant magnetostrictive actuators effectively. The air springs support almost all weight of the micro-manufacturing platform and the giant magnetostrictive actuators support almost no weight. In order to realize high performance to isolate complex micro-vibration, the control method using a three-layer neural network is presented. This vibration control system takes into account the floor disturbance and the direct disturbance acting on the micro-manufacturing platform. The absolute acceleration of the micro-manufacturing platform is used as the performance index of vibration control. The performance of the control system is tested by numerical simulation. Simulation results show that the active vibration isolation system has good isolation performance against the floor disturbance and the direct disturbance acting on the micro-manufacturing platform in all the frequency range.展开更多
为解决传统滤波最小均方差(filtered-x least mean square,FxLMS)算法在收敛速度和稳定性之间存在的矛盾,以及次级通道模型不确定性对控制收敛性能的影响,将反馈FxLMS算法和混合灵敏度鲁棒控制器相结合,提出了一种反馈FxLMS-鲁棒混合控...为解决传统滤波最小均方差(filtered-x least mean square,FxLMS)算法在收敛速度和稳定性之间存在的矛盾,以及次级通道模型不确定性对控制收敛性能的影响,将反馈FxLMS算法和混合灵敏度鲁棒控制器相结合,提出了一种反馈FxLMS-鲁棒混合控制算法,并在工程应用中常见的主动撑杆隔振平台上对该混合算法的振动控制性能进行仿真分析和试验验证。变载荷激励及控制通道变化仿真和试验结果均表明,不同激励下各个阶段的加速度响应衰减均超过80%,且与传统的FxLMS算法相比,所提出的混合控制算法具有更快的收敛速度和更强的鲁棒性。展开更多
文摘The micromation and precision of the Micro-Electromechanical System demand that its manufacturing, measuring and assembling must work in a micro-manufacturing platform with good ability to isolate vibrations. This paper develops a vibration isolation system of micro-manufacturing platform. The brains of many kinds of birds can isolate vibrations well, such as woodpecker’s brain. When a woodpecker pecks the wood at the speed as 1.6 times as the velocity of sound, its brain will tolerate the wallop 1 500 times of the weight of itself without any damage. The isolation mechanics and organic texture of woodpecker’s brain that has good isolation characteristics were studied. A structure model of vibration isolation system for the micro-manufacturing platform is established based on the bionics of the bird’s brain vibration isolation mechanism. In order to isolate effectively the high frequency vibrations from the ground, a rubber layer is used to isolate vibrations passively between the micro-manufacturing platform’s pedestal and the ground. This layer corresponds to the cartilage and muscles in the outer meninges of the bird’s brain. The active vibration isolation technique is adopted to isolate vibrations between the micro-manufacturing platform and the pedestal. Air springs are used as elastic components, which correspond to the interspaces between the outer meninges and the encephala of the bird’s brain. Actuators are made of giant magnetostrictive material, and it corresponds to the nerves and neural muscles linking the meninges and the encephala. The actuators and air springs are arranged vertically in parallel to make use of the giant magnetostrictive actuators effectively. The air springs support almost all weight of the micro-manufacturing platform and the giant magnetostrictive actuators support almost no weight. In order to realize high performance to isolate complex micro-vibration, the control method using a three-layer neural network is presented. This vibration control system takes into account the floor disturbance and the direct disturbance acting on the micro-manufacturing platform. The absolute acceleration of the micro-manufacturing platform is used as the performance index of vibration control. The performance of the control system is tested by numerical simulation. Simulation results show that the active vibration isolation system has good isolation performance against the floor disturbance and the direct disturbance acting on the micro-manufacturing platform in all the frequency range.
文摘为解决传统滤波最小均方差(filtered-x least mean square,FxLMS)算法在收敛速度和稳定性之间存在的矛盾,以及次级通道模型不确定性对控制收敛性能的影响,将反馈FxLMS算法和混合灵敏度鲁棒控制器相结合,提出了一种反馈FxLMS-鲁棒混合控制算法,并在工程应用中常见的主动撑杆隔振平台上对该混合算法的振动控制性能进行仿真分析和试验验证。变载荷激励及控制通道变化仿真和试验结果均表明,不同激励下各个阶段的加速度响应衰减均超过80%,且与传统的FxLMS算法相比,所提出的混合控制算法具有更快的收敛速度和更强的鲁棒性。