Abstract : This paper applies a practical interpolation algorithm to fuzzy control, combined with a proportional self-adjustment algorithm, to design a parameter self-adjusting linear interpolation fuzzy control system. This eliminates the steady-state error and chattering phenomenon caused by quantization error in conventional fuzzy controllers. Simulation results show that the system has fast dynamic response and high steady-state accuracy, meeting the requirements of high-precision AC variable frequency speed control systems. Keywords: Online interpolation; Variable frequency speed control; Fuzzy control; Parameter self-adjustment 0 Introduction With the development of frequency converter technology, AC speed control has been widely used in various industries. However, the variable frequency speed control system is a multi-order, nonlinear, strongly coupled, multivariable system, and the model is not easy to establish. Traditional control algorithms are difficult to achieve the expected results. In recent years, with the development of fuzzy theory, fuzzy control technology has been successfully applied to AC speed control systems. It has advantages such as fast response, strong robustness, and no need to establish an accurate mathematical model. However, conventional fuzzy controllers will produce steady-state error and chattering due to the influence of quantization error. Furthermore, fuzzy control also has the phenomenon of contradictory dynamic and static performance indicators, thus failing to meet the high performance requirements of AC speed control systems. For example, the speed control system of the aero-engine clutch test bench discussed in this paper requires both a fast response speed to simulate the engine start-up process and high steady-state accuracy to simulate the smooth operation of the engine after start-up. To address this, this paper introduces an online interpolation fuzzy controller based on parameter self-adjustment, which is applied to the speed control system of the aero-engine test bench. Simulation and experimental results show that the system exhibits good dynamic and static characteristics and achieves the expected results. 1. Design of a Parameter-Self-Adjusting Online Interpolation Fuzzy Controller Conventional fuzzy controllers require quantization and rounding of the error E and error change EC. The resulting quantization error is the root cause of poor steady-state performance. If the error and error change are not rounded, but interpolated online using a lookup table based on the precise values ​​of E and EC, the problem of poor steady-state performance caused by quantization error can be fundamentally solved. Furthermore, the quantization factor and proportional factor K of fuzzy control affect the dynamic and static performance of the system. From the system output, the causal relationship of adjusting the proportional factor is relatively clear; it directly affects system performance and ultimately influences the overall performance. Therefore, using online self-adjustment of K can achieve good control results without making the system too complex and affecting real-time performance. Based on the above two aspects, a parameter-self-adjusting online interpolation fuzzy control system is proposed, as shown in Figure 1. The transformation and adjustment stage adjusts the E and EC to the set domain. As shown in the figure, the system mainly includes the design of three parts: the interpolation algorithm design, the parameter self-adjustment algorithm design, and the fuzzy lookup table design. [b][align=center]For details, please click: Variable Frequency Speed ​​Control System Based on Online Interpolation Fuzzy Control with Parameter Self-Adjustment[/align][/b]