Loading...
Please wait, while we are loading the content...
Similar Documents
Real-Time Weight Optimization of a Nonlinear Model Predictive Controller Using a Genetic Algorithm for Ship Trajectory Tracking
| Content Provider | MDPI |
|---|---|
| Author | Yu, Dunjing Deng, Fang Wang, Hongyan Hou, Xiuhui Yang, Hualin Shan, Tikun |
| Copyright Year | 2022 |
| Description | This paper presents a weight optimization method for a nonlinear model predictive controller (NMPC) based on the genetic algorithm (GA) for ship trajectory tracking. The weight coefficients Q and R of the objective function in NMPC are obtained via the real-time optimization of the genetic algorithm instead of the trial and error method, which improves the efficiency and accuracy of the controller. In addition, targeted improvements are made to the internal crossover operator, mutation operator, crossover rate, and mutation rate of the genetic algorithm. The simulation comparison of trajectory tracking between NMPC with real-time-optimized weight coefficients and the one with constant coefficients is performed. Finally, the simulation result shows that the controller with real-time-optimized weight coefficients has a better trajectory tracking effect than that with constant weight coefficients. |
| Starting Page | 1110 |
| e-ISSN | 20771312 |
| DOI | 10.3390/jmse10081110 |
| Journal | Journal of Marine Science and Engineering |
| Issue Number | 8 |
| Volume Number | 10 |
| Language | English |
| Publisher | MDPI |
| Publisher Date | 2022-08-12 |
| Access Restriction | Open |
| Subject Keyword | Journal of Marine Science and Engineering Marine Engineering Nonlinear Model Predictive Control Genetic Algorithm Ship Trajectory Tracking Parameter Optimization |
| Content Type | Text |
| Resource Type | Article |
