Research on Control of Intelligent Vehicle Human-Simulated Steering System Based on HSIC

Abstract

The experienced drivers with good driving skills are used as objects of learning, and road steering test data of skilled drivers are collected in this article. First, a nonlinear fitting was made to the driving trajectory of skilled driver in order to achieve human-simulated control. The segmental polynomial expression was solved for two typical steering conditions of normal right-steering and U-turn, and the hp adaptive pseudo-spectral method was used to solve the connection problem of the vehicle segmental driving trajectory. Second, a new Electric Power Steering (EPS) system was proposed, and the intelligent vehicle human-simulated steering system control model based on human simulated intelligent control (HSIC) was established in Simulink/Carsim joint simulation environment to simulate and analyze. Finally, in order to further verify the effectiveness of the proposed algorithm in this article, an intelligent vehicle steering system test bench with a steering resistance torque simulation device was built, and the dSPACE rapid prototype controller was used to realize human-simulated intelligent control law. The results show that the human-simulated steering control algorithm is superior to the traditional proportion integration differentiation (PID) control in the tracking effect of the steering characteristic parameters and passenger comfort. The steering wheel angle and torque can better track the angle and torque variation curve of real vehicle steering experiment of the skilled driver, and the effectiveness of the intelligent vehicle human-simulated steering control algorithm based on HSIC proposed in this article is verified.

General Periodic Cruise Guidance Optimization for Hypersonic Vehicles

“…where Φ, φ, and C are continuous functions defined on interval. The detailed description of GPM can be found in [31][32][33][34][35]. In GPM, the original optimal control problem can be approximated as static nonlinear programming (NLP).…”

“…To date, there is no professional software that can handle periodic optimization problems in a unified framework. Therefore, we must apply existing and mature optimization software to deal with this problem.In recent years, direct methods, especially pseudo-spectral methods (PSM), have become increasingly popular in the preliminary design phase of the aerospace industry with the development of computers and the corresponding optimization software, GPOPS (Gauss Pseudo-spectral OPtimization Software), which is based on some effective nonlinear programming methods, such as SQP (Sequential Quadratic Programming) [31][32][33][34][35]. GPOPS has been successfully applied to many trajectory optimization problems.…”

Power-Efficient Trainable Neural Networks towards Accurate Measurement of Irregular Cavity Volume

“…This is because insufficient samples collected in the real world cannot meet the training requirements of the deep neural networks. The Hilbert-Schmidt independence criterion (HSIC) is proposed for training deep neural networks, and current studies have reported the extensions [15,16]. These methods show that the HSIC is comparable to cross-entropy-based back-propagation methods on popular classification datasets.…”

Establishing the State Function to Determine the Turning Radius of the Vehicle When Steering

“…This is the value of the minimum turning radius, it is determined based on the size of the vehicle and the maximum steering angle as formula below. Also, many studies on improving steering effectiveness have been conducted and introduced [7][8][9][10]. To determine the turning radius of the vehicle, various dynamic models were used as single-track, double-track,… [11][12][13][14].…”