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Double-pendulum crane energy consumption optimal trajectory planning method

A trajectory planning, crane technology, applied in the direction of load hanging components, transportation and packaging, etc.

Active Publication Date: 2017-07-25
NANKAI UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0005] The purpose of the present invention is to solve the problem of optimal energy consumption of the underactuated double pendulum crane system, and to design a trajectory planning method with optimal energy consumption

Method used

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  • Double-pendulum crane energy consumption optimal trajectory planning method
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Experimental program
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Embodiment 1

[0147] 1. Description of experimental steps

[0148] Section 1.1. Constructing an optimization problem based on state quantity constraints

[0149] According to the control objectives of the positioning and swing elimination of the double-pendulum crane system, considering the initial state, target state and state constraints of the system, the optimization problem with system energy consumption as the cost function is constructed as follows:

[0150]

[0151] Among them, min means to minimize, and subject to is followed by constraints that need to be considered. J is the total energy consumption during system operation, and its specific expression is shown in formula (10). is the state vector of the double pendulum crane system, the symbol Indicates matrix / vector transposition, x is the trolley displacement of the double pendulum crane system, is the trolley speed, is the acceleration of the trolley, θ 1 is the swing angle of the hook, θ 2 is the swing angle of t...

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Abstract

The invention discloses a double-pendulum crane energy consumption optimal trajectory planning method, and belongs to the technical field of automatic control of under-actuated mechanical systems. The method comprises the following steps: an energy consumption optimal trajectory planning method aiming at a double-pendulum crane system is designed by fully considering double-pendulum characteristics of a crane system and the energy consumption demands in actual production for realizing the control targets of positioning and pendulum elimination of a double-pendulum crane. Firstly, in order to conveniently analyze and calculate, system kinetic equations are converted. Then, corresponding optimization problems are configured according to each state quantity constraint, an initial state and a target state of the system. Finally, the optimization problems are converted to a form of convex optimization problems, and are solved by a convex optimization tool. The method can guarantee the double-pendulum crane system to reach the target state from the initial state, reaches the lowest energy consumption in the operation process, constrains all system states in a given range, and meanwhile, effectively inhibits and eliminates residual pendulum of the system.

Description

technical field [0001] The invention belongs to the technical field of automatic control of an underactuated mechanical system, and in particular relates to a trajectory planning method with optimal energy consumption applicable to a double pendulum crane system. Background technique [0002] In the past few decades, research on the automatic control of underactuated mechanical systems has received extensive attention from researchers. [1],[2] . Due to the advantages of high flexibility, low energy consumption, low cost, and simple mechanical structure, the underactuated system is currently widely used in modern industrial fields, such as unmanned aerial vehicles [3] ,move robot [4] , mechanical fingers [5] , underwater robotic snake [6] Wait. However, since the control dimension of the underactuated system is less than the number of degrees of freedom to be controlled, there are still difficulties and challenges in the control of the underactuated system. Therefore, r...

Claims

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Application Information

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IPC IPC(8): B66C13/22B66C13/06
CPCB66C13/063B66C13/22
Inventor 孙宁吴易鸣方勇纯陈鹤
Owner NANKAI UNIV
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