Abstract
In this paper, the theory of RPC (remote parameter control) iteration process of linear situation without and with iteration coefficient as well as nonlinear situation with coefficient is analyzed. The influence of iteration coefficient on iterative convergence control condition is analyzed. Two kinds of optimized control method for iteration coefficient based on the system transfer function estimation are proposed. A lightweight motorcycle and electro-hydraulic servo road vibration test bench are used to verify the feasibility of the optimized control methods for the reproduction of road profiles of SISO (single-input, single-output) system. According to the experiment result, which is the RMS (root mean square) of the NSRE (normalized spectrum of response error) of system, the convergent precision, convergent speed and iteration stability are discussed to present the advantage and disadvantage of the optimized control methods. Compared with three commonly used manual methods, the result shows the rapidity and stability of optimized control methods.
Highlights
Different from direct quantitative determination of speed or torque, the road fluctuation is a kind of random vibration signal, which is difficult to collect [1]
This paper focuses on theory analysis of remote parameter control (RPC) iteration process of linear and nonlinear conditions
The previous experimental theory of RPC and the iterative process of linear system are the work of predecessors, and this paper has summarized and discussed
Summary
Different from direct quantitative determination of speed or torque, the road fluctuation is a kind of random vibration signal, which is difficult to collect [1]. The sinusoidal frequency signal is mainly used as input in an early-stage vibration experiment system [2]. The ultimate goal of remote parameter control (RPC) is to achieve the desired response of the SUT (system under test) in the real environment and reproduce the desired response in the laboratory environment, so that the SUT in the laboratory can achieve the same experimental effect as in the real environment. In most cases, when the SUT is tested in a real environment, only response—but no input—can be obtained, and the response characteristics between the output and input of the SUT are unknown. The RPC could obtain the desired output of the SUT by controlling the input of the SUT through transfer function (TF) estimation and iterative control
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