Mechanical arm position cascade fractional order control method and system based on data driving

Abstract

The invention discloses a mechanical arm position cascade fractional order control method and system based on data driving. The method is characterized in that the same control input signal is used for carrying out two-time excitation experiments on joints of a mechanical arm, preset inner and outer ring reference systems and acquired relevant data are used for calculating a virtual reference signal and a following error signal, an ideal filter is used for carrying out filtering processing on the inner ring signal and the outer ring signal, then a setting criterion taking a position cascaded fractional order controller parameter as an optimization variable is constructed, and finally the optimal design of an optimal position cascade fractional order controller is completed. According to the method and system, the design of the controller is carried out by directly utilizing the actually acquired input and output data, the model identification of a controlled object does not need to becarried out, and therefore the influence of unmodeled dynamics and model errors is avoided, the process data of a repeated test are used, so that the influence of data noise is eliminated, moreover, the internal and external ring fractional order controllers can be optimized and set at the same time, the efficiency of the control algorithm is guaranteed, and the robustness and the control precision of the system are improved.

Description

technical field [0001] The invention belongs to the technical field of industrial robot control, and more specifically relates to a data-driven cascaded fractional order control method for the position of a mechanical arm. Background technique [0002] The motion control technology of multi-joint manipulators is a frontier hot research topic in the field of automation control, and high-performance manipulators are one of the basic guarantees for improving the level of "high-tech" equipment in the manufacturing industry. For a multi-joint manipulator, its position control performance will affect the efficiency and positioning accuracy of the manufacturing process. In order to realize the precise position control of the manipulator, the drive system of each joint adopts position cascade control to control it, so the position tracking ability of each joint system will directly determine the control performance of the manipulator. [0003] Position cascade control not only guar...

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Problems solved by technology

[0005] 1) The smooth implementation and application of the controller parameter tuning algorithm requires accurate model identification of the controlled system. However, when the precise model of the controlled object cannot be obtained in real time, and in the case where the structural nonlinearity and uncertain factors cannot be ignored Under such circumstances, this type of model-based position control method is difficult to meet the actual needs of the system;

[0006] 2) This type of method is only suitable for the design of position cascaded integer-order controllers, without considering the fractional-order characteristics in the dynamic response of the manipulator joints, so the control effect is limited;

[0007] 3) These methods do not analyze the interference of data, but for the actual industrial environment, noise interference always exists in the process of data acquisition and transmission

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