Performance analysis of predictive functional control for automobile adaptive cruise control system - Zainuddin, Mohamed Al-Sideque; Abdullah, Muhammad; Ahmad, Salmiah; Uzair, Mohd Suhaimi; Ahmad Baidowi, Zaid Mujaiyid Putra (IIUM Press, 2023)
This paper presents the performance analysis of Predictive Functional Control (PFC) forAdaptive Cruise Control (ACC) application. To cope with multiple driving objectives of modernACC systemssuch as passenger comfort, safe distancing,and fast time response, an advanced optimal controller such as Model Predictive Control (MPC) is often used. Nevertheless, MPCrequires a high computation load due to its complex formulation and may overload the processing power of a microcontroller. Thus, the prime objective of this work is to propose a PFCalgorithm as an alternative controller, while providing a formal comparisonbetweenMPCand the traditional Proportional Integral (PI) controller. A standard kinematic model for vehicle longitudinal dynamics was modelledandused to derive the control law of PFC. Since the open-loop dynamic of the derived transfer function is not stable, the second objective is to propose a pre-stabilized loopor cascade PFC structurefor the system. A complete tuning procedure and analysis were presented. The simulation result shows that although MPC performance is the best for the ACC application with Root Mean Square Error (RMSE) of 1.4873, PFC has shown a promising response with RMSEof 1.5501, which is better compared to the PI controller with RMSE of 1.6219. All the imposed driving constraints, such as maximum acceleration, maximum deceleration and safe distance, were satisfied in the car following application. Thus, the findings from this work can become a good initial motivation to explore further the capability of the PFC algorithm for future ACC development.