Adaptive neural network control method for arc micro-electromechanical system

Abstract

The invention discloses an adaptive neural network control method for an arc micro-electromechanical system, which comprises the steps of a, building a system model of the arc micro-electromechanicalsystem based on the Bernoulli beam; b, constructing an adaptive neural network controller used for suppressing chaotic oscillation of the arc micro-electromechanical system and guaranteeing state constraints of the system, wherein when the adaptive neural network controller is constructed, output constraints of the arc micro-electromechanical system are ensured not to be violated by using a symmetrical obstacle Lyapunov function, an unknown non-linear function is estimated with an arbitrary small error by adopting an RBF neural network with an adaptive law, an extension state tracking differentiator is introduced to process a problem that virtual control items in backstepping control need to be derived repeatedly, a state observer is designed to obtain unmeasured state information, the extension state tracking differentiator and the state observer are integrated in the backstepping framework. The adaptive neural network control method has the characteristics of convenient stability analysis and proving, low requirement for the modeling precision, low computation complexity, high operation speed, good operation stability of the system and high motion accuracy.

Description

technical field [0001] The invention relates to an arc microelectromechanical system, in particular to an adaptive neural network control method for an arc microelectromechanical system. Background technique [0002] Micro-electromechanical systems (MEMS) are complex micro-devices or independent intelligent systems that integrate micro-sensors, micro-actuators, micro-energy sources, signal processing and control circuits, high-performance electronic integrated devices, interfaces, and communications. MEMS technology is a revolutionary new technology, involving microelectronics, information and automatic control, mechanics, materials, mechanics and many other disciplines. It is widely used in high-tech industries. Key technologies for national defense security. [0003] Nonlinear factors (such as modeling uncertainty, environmental changes, component aging, self-excited vibration) are inevitable. Once the MEMS fails, it will inevitably trigger a chain reaction, leading to th...

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Problems solved by technology

[0003] Nonlinear factors (such as modeling uncertainty, environmental changes, component aging, self-excited vibration) are inevitable. Once the MEMS fails, it will inevitably trigger a chain reaction, leading to the failure of the entire equipment, causing major safety accidents and economic losses and adverse social impact

Due to the influence of factors such as manufacturing defects, external disturbances, hysteresis, and unpredictable states, and the uncertainty of the mathematical model of the MEMS, it is difficult to obtain an accurate model of the control object

Arc MEMS is a complex nonlinear system with high-order, multi-field coupling, and time-varying parameters. The existing control methods of MEMS cannot properly solve the problems of output constraints, chaotic oscillation, unpredictable state and Control problems when dynamics are unknown

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