Hierarchical identification method applicable to control parameters of teleoperation system

Abstract

The invention relates to a hierarchical identification method applicable to the control parameters of a teleoperation system. The method comprises the steps of simplifying a teleoperation process in which input and output signals are sampled differently into a dual-rate sampling system, building an auxiliary model based on a minimal sampling period by using a re-sampling method, and estimating the middle state value of the re-sampling system; an output sampling period is greater than a re-sampling period, and the middle state value can not be directly corrected by the output estimated differential value of the system, so that the state estimation value in a Kalman forecasting process can be modified by adopting a state changing difference value, i.e. a differential method. According to the method, the parameters of the dual-rate teleoperation system can be identified under the two conditions of known and unknown state values, so that the feasibility and effectiveness of the method can be verified by a simulation result.

Description

technical field [0001] The invention belongs to the field of system control parameter identification, and in particular relates to a hierarchical identification method suitable for remote control system control parameters. Background technique [0002] Dual rate system is a general term for systems with different input sampling frequency and output sampling frequency. The dual-rate system is not only widely used in the field of chemical process control, but also has important significance in the field of aerospace technology applications. The signal is the position and torque signal of the hand controller at the end, and the output feedback signal includes the position, speed, and torque signals at the joints of the teleoperated robot arm. Generally, the frequency of the master control signal is higher than the frequency of the feedback signal received. , on the one hand, this is related to the ability of the on-board computer to process signals, and on the other hand, it i...

AI Technical Summary

Problems solved by technology

Among them, the state-space method is an important method in double-rate identification. It is mainly aimed at the fact that the double-rate data in the discrete state-space model cannot be directly used for identification. The double-rate sampling system is transformed into a time-invariant single rate system model, and identified system parameters with reference to subspace identification methods such as MOESP, N4SID, and CAV. Although the upgrading technology transforms LPTV into an LTI system, which is convenient for the direct application of the identification method, it will also result in the number of parameters to be identified and the The increase in the amount of calculation and the unsatisfactory identification accuracy. In addition, the "improved" frame cycle time only identifies the parameters once, which will cause a long convergence period and a slow convergence speed for the identification parameters.

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