Permanent magnet synchronous motor (PMSM) exhibits chaotic behavior when its parameters are within a certain range which seriously affect the stable work of PMSM. In order to eliminate the chaos, many approaches have been proposed. Most of them considered asymptotic stability of the system, while finite-time stability makes more sense in practice. In addition, parameters of PMSM may be uncertain because of some external factors, then adaptive control is a good method to be considered. In this paper, adaptive finite-time stabilization problem is considered to eliminate the chaos in PMSM system with uncertain parameters. To show the effectiveness of the proposed method, some simulation results are provided.

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The test methods of autonomous driving are mainly divided into SIL, MIL, VIL, real vehicle test, etc.; the scenario-based virtual simulation verification method has huge technical advantages in test coverage, test repeatability, test safety, etc., and is an effective method for future autonomous driving function test verification. With the improvement of technology and demand, autonomous driving developers have gradually increased their investment in simulation testing. How to evaluate the comparison between simulation test results and actual test authenticity is a major challenge for autonomous driving. The high-definition map software used in this paper can realize intelligent lane fitting and fast connection, and realize fast and smooth connection in advance while ensuring the consistency between the edited road network and the actual environment. By collecting real scene maps, a high-definition map conforming to the Open Drive format that can be used in real vehicles and simulations is generated, which solves the problem of common use of lane-level high-definition maps in intelligent driving vehicle testing and simulation testing.

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