## 2 Principle  
### RPC Theory  
The RPC was proposed by Dr. [PERSON] of MTS Systems Corp. in 1970s, which is a theory and technology of random environment simulation test [19]. Compared with the early-stage regular wave simulation test, the RPC is closer to the real operation condition. RPC is a closed-loop iterative control method, which takes the difference between the desired response and the current iteration response (response error) as feedback, to obtain the input compensation value (drive correction) through the controller composed with linear TF estimation and iteration coefficient, and then carries out the next iteration. The RPC uses the calculated system inputs, through the system TF, to control the system outputs far away from the inputs, so it is called remote parameter control. The word \"far away\" or \"remote\" in RPC means that the control quantity (input) and the controlled quantity (output) are far away from each other. For example, the control quantity in this paper is the displacement of the actuator of the test bench, and the controlled quantity is the acceleration on the vehicle frame. At the same time, RPC aims to reproduce the desired response of the SUT in the laboratory environment, while the desired response is achieved in the real environment. The laboratory environment and the real environment are also geographically far away from each other. The purpose of RPC is to calculate the input signal with the system characteristics and to get the desired responses by using random function theory. The RPC mainly contains three parts: the desired response acquirement, the linear TF estimation and the iteration test [20; 21], as shown in Figure 1:  
The drive of the Real Test (on a real road) and TF of SUT under the Real Test are unknown, and other signals including response of SUT under the Real Test (desired response), Generated Drive in Linear TF Estimate (standard road) and response of bench test are known. In this paper, the real road is already obtained, but it is just a precondition. The real road is taken as input and the experiment was carried out on the test bench to simulate the experiment process on the real road. The response obtained is taken as the Desired Response and used as the initial condition to verify the control algorithm of this paper, for example, the data acquired by the transducers on the vehicle which runs on the real road. Figure 1: Remote parameter control (RPC) process sketch (solid boxes and arrows represent data and data transfer, dashed boxes and arrows represent process and process change). The linear TF estimation is obtained by vector division with the Fourier transform of generated drive (standard road) and test response. The standard road is usually generated based on standard condition that close to real road or experience. The inverse linear TF is obtained by taking the reciprocal of the linear TF estimation. The iteration coefficient is contained in the drive correction calculation. For RPC, the displacement of the actuator of the test bench is controlled, and it is the corrected drive obtained by adding the previous drive and the drive correction. The iteration test is continuously generating drive and doing bench test until the error between desired response and test response reaches the demand. Otherwise, the response error is used to calculate the drive correction for the new drive, then test process iterates. The detail of calculation will be described later. The bench test means that the SUT is test on the test bench in the experiment lab, while the real test means that the SUT is test on the real road. The outputs of bench test and real test should be the same, because the goal of RPC is to reproduce the desired response of the SUT on the test bench and the desired response is the output of the SUT in real test. We change the iteration coefficient to adjust the \"size\" of drive correction to control the input of iteration so as to make the iterative process more accurate, fast and stable.