Neural network adaptive robust trajectory tracking method and controller

An adaptive robust, trajectory tracking technology, applied in the direction of adaptive control, general control system, control/adjustment system, etc., can solve the problems of poor control effect and poor stability

CN104808487AInactive Publication Date: 2015-07-29TAIZHOU UNIV
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Patent Information

Authority / Receiving Office
CN · China
Current Assignee / Owner
Publication Date
2015-07-29
Estimated Expiration
Not applicable · inactive patent

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Abstract

The embodiment of the invention discloses a neural network adaptive robust trajectory tracking method and a controller applied to the technical field of robot trajectory tracking control, so as to solve the problems of poor stability and poor control effects of the prior robot trajectory tracking control technology. The method comprises steps: a proportion-derivative (PD) controller is acquired, and according to the acquired PD controller, a nominal part of the trajectory tracking system is acquired; on the basis of a radial basis function neural network, uncertain items of the trajectory tracking system are acquired; an adaptive robust controller is acquired, and the uncertain items of the trajectory tracking system are adjusted via the adaptive robust controller; and according to the nominal part, the uncertain items and an uncertain upper limit value of the uncertain items, total control input is acquired, and according to the total control input, an actual output trajectory is acquired.
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Description

technical field

[0001] The invention belongs to the technical field of robot trajectory tracking control, and relates to a neural network self-adaptive robust trajectory tracking method and a controller. Background technique

[0002] When the structure of the robot is determined and the parameters are known, the complete dynamic characteristics of the system can be described by the dynamic model, so that various automatic control theories can be applied to design a model-based controller to realize the trajectory tracking control of the robot, so that the robot's position, Variables such as velocity and acceleration have ideal tracking conditions. However, robot dynamics are actually highly nonlinear and uncertain systems. Therefore, dealing with the nonlinear uncertainty of the system is a very critical research content in the trajectory tracking control of the robot.

[0003] There are two basic solutions for robots with uncertainties such as modeling errors, external di...

Examples

Embodiment Construction

[0073] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some, not all, embodiments of the present invention.

[0074] The example of the present invention combines neural network with robust adaptive control, and proposes an adaptive robust trajectory tracking control strategy based on neural network for uncertain robots. Firstly, the nominal part of the trajectory tracking system is obtained through the PD controller, and then the uncertain items of the trajectory tracking system are obtained through the neural network, and then the adaptive robust controller is used to reduce the approximation error of the neural network, in which the adaptive law is used for Tuning of Uncertain Parameters for Robust Controllers.

[0075] Uncertain robots are those that have unmodeled dynam...