Abstract: To address the unconventional and non-smooth strong nonlinear hysteresis characteristics exhibited by diffused silicon pressure sensors, a simple inverse hysteresis operator is proposed by increasing the spatial dimension. This operator transforms the multi-valued mapping of hysteresis nonlinearity into a one-to-one mapping, establishes a hysteresis inverse model approximated by the TS fuzzy model, and achieves intelligent compensation for the hysteresis loop. Simulation results demonstrate that the proposed model is effective for hysteresis characteristic modeling and possesses high compensation accuracy. Keywords: diffused silicon pressure sensor; hysteresis; TS model; inverse model; inverse operator Abstract: The hysteresis characteristic of diffused silicon sensor is a kind of non-smooth non-linearity with multivalued mapping and memory. In this method, a hysteretic operator of simple structure is introduced to transform the multivalued mapping of hysteresis into a one-to-one mapping so that TS fuzzy model can be utilized to approximate the characteristic of hysteresis. And the inverse model of the hysteresis. is established, which is put forward to make intelligence compensation to the hysteresis. The results of simulation show the inverse hysteresis model of diffused silicon sensor is effective and of high precision. Key words: diffused silicon pressure sensor;hysteresis;Takagi-Sugeno (TS) model;inverse model;inverse operator 1 Introduction Diffused silicon pressure sensors are widely used in industry, agriculture, meteorology, aerospace and other fields due to their high sensitivity, stable performance, wide range, and mass production, and have great application potential[1]. With the in-depth research on the nonlinearity of the piezoresistive effect and the development of semiconductor process technology, the technical indicators of diffused silicon pressure sensors have been continuously improved. However, the inherent non-conventional and non-smooth hysteresis characteristics of diffused silicon pressure sensors affect their measurement accuracy. At present, the commonly used compensation methods are hardware compensation method and software method, which only treat hysteresis as a general nonlinear characteristic for approximate compensation. Due to the limitations of many factors such as the need for the development of new materials, the effect is still not very satisfactory from the perspective of improving the production process. Therefore, the use of software to replace hardware for nonlinear compensation to improve the sensor accuracy has received widespread attention. In terms of hysteresis nonlinearity compensation, the most commonly used method is to establish an accurate hysteresis inverse model and connect the inverse model with the hysteresis nonlinearity to offset the adverse effects of hysteresis on the system. In order to describe the characteristics of hysteresis nonlinearity, many experts and scholars at home and abroad have modeled and controlled hysteresis from different perspectives. Common hysteresis models include Preisach model[2], KP model[3], PI model[4], Duhem model[5], Bouc-wen model[6], TK model[7]. However, these methods are mainly from the perspective of control and cannot obtain an accurate inverse model. This paper is from the perspective of measurement and requires an accurate hysteresis inverse model. Therefore, establishing an accurate inverse model is the key to solving the problem in this paper. Reference[8] proposes a piecewise exponential function curve to outline the hysteresis operator. This paper is inspired by reference[8]. Based on the method of increasing the spatial dimension, it proposes an inverse operator with a unified mathematical expression and simple structure to increase the input space of hysteresis. In three-dimensional space, the multi-valued mapping of hysteresis is transformed into a one-to-one mapping. The TS fuzzy model is used to approximate this one-to-one mapping and establish the hysteresis inverse model. The simulation results show that the model has good approximation and prediction capabilities. For details, please click: Hysteresis Modeling and Intelligent Compensation of Diffused Silicon Pressure Sensor