Title :
Sampled Data Model Predictive Idle Speed Control of Ultra-Lean Burn Hydrogen Engines
Author :
Sharma, Ritu ; Nesic, D. ; Manzie, Chris
Author_Institution :
Sch. of Inf. Technol. & Electr. Eng., Univ. of Queensland, Brisbane, QLD, Australia
Abstract :
A model-based approach for the idle speed control of ultra-lean burn engines is presented. The results from model predictive control (MPC) are extended and collectively used with the existing sampled data control theory to obtain a rigorously developed idle speed control strategy. Controller is designed using MPC theory and facilitated by successive online linearizations of the nonlinear discrete-time model at each sampling instant. Simultaneously, the approximations due to the discretization of the nonlinear engine model are explicitly considered by designing the control within a previously proposed control design framework to obtain appropriate stability guarantees of an exact (unknown) discrete-time engine model. The proposed idle speed control method is experimentally validated on a prototype 6-cylinder hydrogen engine.
Keywords :
control system synthesis; discrete time systems; internal combustion engines; linearisation techniques; nonlinear control systems; predictive control; sampled data systems; stability; velocity control; MPC theory; control design framework; controller design; discrete-time engine model; idle speed control method; idle speed control strategy; model predictive control; model-based approach; nonlinear discrete-time model; nonlinear engine model; online linearizations; prototype 6-cylinder hydrogen engine; sampled data control theory; sampled data model predictive idle speed control; sampling instant; stability guarantees; ultra-lean burn engines; ultra-lean burn hydrogen engines; Approximation methods; Computational modeling; Data models; Engines; Optimization; Stability analysis; Velocity control; Hydrogen engines; idle speed control; model predictive control (MPC); sampled data control; ultra-lean burn engines;
Journal_Title :
Control Systems Technology, IEEE Transactions on
DOI :
10.1109/TCST.2012.2185238