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Neural Network Output Feedback Adaptive Robust Control Method Based on Launch Platform

An adaptive and robust neural network technology, applied in the field of motor servo control of the launch platform, can solve problems such as difficulty in obtaining the true value of the state quantity

Active Publication Date: 2021-09-10
NANJING UNIV OF SCI & TECH
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Problems solved by technology

[0005] The purpose of the present invention is to provide a neural network output feedback adaptive robust control method based on the launch platform, to solve the problem that the real value of the state quantity in the launch platform motor servo system is difficult to obtain

Method used

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  • Neural Network Output Feedback Adaptive Robust Control Method Based on Launch Platform
  • Neural Network Output Feedback Adaptive Robust Control Method Based on Launch Platform
  • Neural Network Output Feedback Adaptive Robust Control Method Based on Launch Platform

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Embodiment

[0109] The simulation parameters are: inertial load parameter J eq =0.01kg·m 2 , torque amplification factor k u =5, viscous friction coefficient B eq =1.025N·s / m, constant interference d n =1.525N.m, pitch and azimuth coupling coefficient c 1 =0.14N.m(rad / s),c 2 =0.13N.m(rad / s), time-varying interference upper bound δ=0.6N·m; The upper bound of δ 2 =0.3N.m; θ min = [0, 0.002, 0.22] T ; θ max =[0.215, 0.01, 0.3] T ; Time-varying interference f(t)=0.5sin(0.5πt)(N m); Position motion equation θ=0.1sin(πt)[1-exp(-0.01t)](rad) in pitch direction; position angle input Signal Take observer parameter kd=20, k=400, kp=200, ko=1.1; F=diag[10,10], controller parameter k 1 =50,k 2 =1,,λ 0 =200,λ 1 =1500,λ 2 = 2000; θ 1n = 300; θ 2n = 20, the selected nominal value of θ is far from the true value of the parameter, in order to examine the effect of the adaptive control law.

[0110] from above Figure 4-Figure 11 It can be seen that the present invention uses the neur...

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Abstract

The invention discloses a neural network output feedback self-adaptive robust control method based on a launch platform. The steps of the method are as follows: firstly, a mathematical model of the launch platform is established, and secondly, a neural network state observer and a neural network state observer based on the neural network state observer are designed. Network output feedback adaptive robust controller; Finally, the stability of the neural network state observer and neural network output feedback adaptive robust controller is proved by using Lyapunov stability theory. The invention solves the problem that the real value of the state quantity in the motor servo system of the launch platform is difficult to obtain.

Description

technical field [0001] The invention relates to the field of motor servo control of a launch platform, in particular to a neural network output feedback adaptive robust control method based on a launch platform. Background technique [0002] The launch platform is widely used in anti-aircraft weapons. It consists of two parts, the azimuth and the pitch servo system. The mathematical models of the two are consistent. Therefore, the present invention can conduct research on the azimuth servo system. [0003] High-precision motion control has become the main development direction of modern DC motors. In the motor servo system, due to the change of working conditions, external disturbances and modeling errors, when designing the controller, there will be a lot of model uncertainty, especially the uncertain nonlinearity, which will seriously deteriorate the obtained control performance, resulting in low control accuracy, limit cycle oscillations, and even system instability. Fo...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): H02P23/00H02P23/12H02P21/00H02P21/13
CPCH02P21/0014H02P21/13H02P23/0018H02P23/12
Inventor 胡健沈旭亮
Owner NANJING UNIV OF SCI & TECH
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