Feedback of sports intelligent learning system based on model predictive control and artificial intelligence

Abstract

Abstract The numerical solution of the sports intelligent learning system has high complexity during operation, which restricts the online application of optimal control. In order to improve the optimization effect of the feedback delay of the sports intelligent learning system, this paper discusses the method of efficiently solving the optimal control problem of the differential-algebraic system from the aspects of improving the efficiency of the integration process and selecting an appropriate constraint processing strategy. Moreover, this paper proposes an efficient calculation method for solving the index-1 DAE optimal control problem under continuous inequality constraints. This method avoids a large number of interior point constraints introduced by discretization of continuous inequality constraints and makes it possible to solve optimal control problems under continuous inequality constraints. In addition, this paper designs a one-step advanced model predictive control algorithm to solve the NLP problem one sampling period in advance, and then correct the solution of the NLP problem through sensitivity analysis. Finally, this paper designs experiments to study the performance of the method proposed in this paper. The research results show that the method constructed in this paper is effective.