Missile longitudinal attitude control algorithm based on reinforcement learning

A technology of attitude control and reinforcement learning, applied in non-electric variable control, control/regulation system, 3D position/channel control, etc., to achieve the effect of reducing dependence and strong robustness

Active Publication Date: 2020-09-25
HARBIN ENG UNIV
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Problems solved by technology

[0006] The purpose of the present invention is to provide a method for controlling the longitudinal attitude of missiles with modeling uncertainty and model parameters that cannot be accurately ob

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  • Missile longitudinal attitude control algorithm based on reinforcement learning
  • Missile longitudinal attitude control algorithm based on reinforcement learning
  • Missile longitudinal attitude control algorithm based on reinforcement learning

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Embodiment Construction

[0055] The present invention will be further described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0056] Aiming at the modeling uncertainty of the traditional missile longitudinal attitude model and the inability to obtain some information of the model accurately, a missile longitudinal attitude control algorithm based on reinforcement learning is designed to stabilize the missile's longitudinal attitude angle. Specific steps are as follows:

[0057] Step 1) Establish and determine the missile longitudinal attitude dynamic model:

[0058] Based on the principle of small disturbance linearization and ignoring the influence of lateral and lateral variables, the dynamic model of missile longitudinal attitude is:

[0059]

[0060]

[0061] where: ω z is the pitch angular velocity, α is the angle of attack, δ z is the deflection angle of the pitch rudder, m is the mass of the missile, P is the thrust of the missile, θ is the p...

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Abstract

The invention provides a missile longitudinal attitude control algorithm based on reinforcement learning, belongs to the field of missile attitude control research, and relates to an Actor-Critic (AC)structure based on reinforcement learning, which is composed of an action network and an evaluation network, wherein the evaluation network is used for outputting an evaluation value for the state ofthe missile according to the state of the missile, and the action network is used for generating a corresponding elevator deflection angle according to the evaluation value output by the evaluation network, so that the longitudinal attitude of the missile is stably controlled under the condition of not depending on an internal model of the missile. The method comprises the following steps: 1) establishing and determining a missile longitudinal attitude kinetic model; (2) defining a tracking error of the missile attack angle and establishing a performance index related to the error; (3) designing an evaluation network; (4) designing an action network; (5) designing an evaluation network weight updating law; (6) designing an action network weight updating law. The algorithm is mainly applied to the missile longitudinal attitude control.

Description

technical field [0001] The invention relates to a missile longitudinal attitude control algorithm based on reinforcement learning, which belongs to the research field of missile attitude control. Background technique [0002] Aerospace vehicles have received more and more attention in recent years. Due to the expansion of the flight envelope of the aircraft, more and more tasks are required for the aircraft, which means that the flight control of the aircraft is becoming more and more complicated. Due to the complex dynamic characteristics of the missile, the uncertain flight environment and high control precision are required. The control system needs to be robust and adaptive to modeling uncertainties. Based on the above requirements, traditional control methods have been difficult to handle many complex control tasks. [0003] The most widely used in the field of missile attitude control is the PID controller. The PID controller has the characteristics of simple struct...

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Application Information

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IPC IPC(8): G05D1/10
CPCG05D1/107Y02T90/00
Inventor 池海红于馥睿刘兴一周明鑫
Owner HARBIN ENG UNIV
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