Model-Driven and Data-Driven Reachable Set Estimation for Multirate Sampled-Data Truck-Trailer System

The concept of reachable set and state space ellipsoid is used in this article to determine the optimal safe range of the truck-trailer driving by allowing the constrained variables to move freely within a given range. A method of returning the truck to the desired position is proposed by analysing the movement trajectory of the truck. Two results are certified. The first result considers the issue of reachable set estimation (RSE) for the multirate sampled-data (MRSD) system in the aperiodic sampled-data framework based on the model knowledge. By constructing loop-based Lyapunov functional (LBLF), we obtain the sufficient condition that all the state trajectories are confined to target ellipsoid. This article also provides a computational method for an MRSD controller considering RSE. The second result provides the data-driven control tactics for the unknown sampled-data system to consider the RSE problem for the aperiodic sampled-data system, using only the noisy data. In addition, this article extends the data-driven control scheme to the design of MRSD controllers and ensures the stability of the system in agreement with the measured data. Simulation results show that the MRSD controller under both the model-driven method and the data-driven method is valid and achieves better control effect compared to the single-rate sampled-data (SRSD).