Method for optimizing joint angles of under-actuated mechanical arms on basis of improved particle swarm algorithms

Abstract

An embodiment of the invention discloses a method for optimizing joint angles of under-actuated mechanical arms on the basis of improved particle swarm algorithms. The method includes building planarthree-degrees-of-freedom passive-active-active type (PAA type) under-actuated mechanical arm kinetic models; reducing order of each under-actuated mechanical arm kinetic model with non-holonomic constraint characteristics by the aid of back-stepping control thoughts to obtain two passive-active type (PA type) subsystems, and making relations between the joint angles and the locations of the tail ends of mechanical arms definite; utilizing difference values of the locations of the tail ends of the under-actuated mechanical arms and target locations as target functions, leading in simulated annealing Metropolis acceptance criteria and congestion degree factors of artificial fish school algorithms and solving the corresponding optimal joint angles for reaching the target locations. Accordingto the technical scheme, the method has the advantages that the local optimization trapping probability of optimization algorithms can be lowered during under-actuated mechanical arm location control,and the solving precision can be improved.

Description

【Technical field】 [0001] The invention belongs to the technical field of automatic control, relates to model reduction and particle swarm algorithm, in particular to an underactuated mechanical arm joint angle optimization method based on improved particle swarm algorithm. 【Background technique】 [0002] In space, in order for the manipulator to complete complex and diverse tasks, the space manipulator should have the characteristics of light weight, low energy consumption, certain redundancy and high flexibility. The energy consumption of the manipulator is positively correlated with the number of driving devices. Underactuated manipulators require fewer drive motors than the number of joints. Under the premise of ensuring the completion of the task, it is more suitable for working in space. [0003] In the position control of the underactuated manipulator, the dynamics of the manipulator has a high degree of nonlinear coupling. Using the idea of ​​inversion control, the th...

AI Technical Summary

Problems solved by technology

In order to achieve precise position control, it is necessary to accurately solve the target angle of the active joint. The particle swarm algorithm initializes the particles uniformly, updates the particles according to the global optimal and historical optimal, and solves the optimal joint angle corresponding to the target position. However, The accuracy of the particle swarm algorithm in solving the optimal joint angle of the manipulator still needs to be optimized urgently

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