Model Predictive Path Integral PID Control for Learning-Based Path Following
Classical proportional--integral--derivative (PID) control remains widely used in industrial control systems, while model predictive control (MPC) is actively studied to achieve higher performance for systems with nonlinear dynamics. Model predictive path integral (MPPI) control is a sampling-based MPC method that optimizes control inputs without gradient calculations and can handle non-differentiable models and objective functions. However, conventional MPPI directly samples control-input sequences, which can produce large temporal input increments and causes the optimization dimension to grow with the prediction horizon. This study proposes MPPI--PID control, which uses MPPI to optimize...
| Authors | Teruki Kato, Koshi Oishi, Seigo Ito |
|---|---|
| Primary category | eess.SY |
| Published | 31 March 2026 |
| Last updated at source | 6 July 2026 |
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