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In the cold rolling process, friction coefficient, oil film thickness and other factors vary dramatically with the change in the rolling speed, which seriously affects the strip thickness deviation. This paper aims to improve the strip control precision with the forecast roll gap model based on CF-PSO-SVM approach in the rolling process.

In this paper, a novel forecasting model of the roll gap based on support vector machine (SVM) optimized by particle swarm optimization with compression factor (CF-PSO) is proposed. Based on lots of online data, the roll gap models regressed by PSO-SVM, genetic algorithm (GA)-SVM and CF-PSO-SVM are obtained and verified through evaluating the performances with the decision coefficient (R²), mean absolute error and root mean square error. In addition, with the good forecasting performances of CF-PSO-SVM, a roll gap compensation model is studied.

The results indicate that the proposed CF-PSO-SVM has excellent learning regression ability compared with other optimization algorithms. Meanwhile, a roll gap compensation model based on the rolling speed and plastic coefficient is obtained, which has been proved validated in product.

In this paper, the SVM algorithm is combined with traditional rolling technology to solve the problems in actual production, which has great supporting significance for the improvement of production efficiency.

Tactile sensation is an important sensory function for robots in contact with the external environment. To better acquire tactile information about objects, this paper aims to propose a three-layer structure of the interdigital flexible tactile sensor.

The sensor consists of a bottom electrode layer, a middle pressure-sensitive layer and a top indenter layer. First, the pressure sensitive material, structure design, fabrication process and circuit design of the sensor are introduced. Then, the calibration and performance test of the designed sensor is carried out. Four functions are used to fit and calibrate the relationship between the output voltage of the sensor and the contact force. Finally, the contact force sensing test of different weight objects and the flexible test of the sensor are carried out.

The performance test results show that the sensitivity of the sensor is 0.93 V/N when it is loaded with 0–3 N and 0.23 V/N when it is loaded with 3–5 N. It shows good repeatability, and the cross-interference between the sensing units is generally low. The contact force sensing test results of different weight objects show that the proposed sensor performs well in contact force. Each part of the sensor is a flexible material, allowing the sensor to achieve bending deformation, so that the sensor can better perceive the contact signs of the grasped object.

The sensor can paste the surface of the paper robot’s gripper to measure the contact force of the grasping object and estimate the contour of the object.

In this paper, a three-layer interdigital flexible tactile sensor is proposed, and the structural parameters of the interdigital electrode are designed to improve the sensitivity and response speed of the sensor. The indenter with three shapes of the prism, square cylinder and hemisphere is preliminarily designed and the prism indenter with better conduction force is selected through finite element analysis, which can concentrate the external force in the sensing area to improve the sensitivity. The sensor designed in this paper can realize the measurement of contact force, which provides a certain reference for the field of robot tactile.