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Neural network output feedback adaptive robust control method based on transmitting platform

An adaptive robust, neural network technology, applied in the field of servo control of launch platform motors, can solve problems such as difficulty in obtaining the true value of state quantities, achieve excellent control performance and increase robustness

Active Publication Date: 2020-02-21
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 transmitting platform
  • Neural network output feedback adaptive robust control method based on transmitting platform
  • Neural network output feedback adaptive robust control method based on transmitting 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, the 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 ...

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Abstract

The invention discloses a neural network output feedback adaptive robust control method based on a transmitting platform, and the method comprises the following steps: firstly building a mathematic model of the transmitting platform, secondly designing a neural network state observer, and a neural network output feedback adaptive robust controller based on the neural network state observer; and finally, performing stability proving on the neural network state observer and the neural network output feedback adaptive robust controller by applying a Lyapunov stability theory. According to the invention, the problem that the real value of the state quantity in the launching platform motor servo system is difficult to obtain is solved.

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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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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