This paper presents a performance assessment of the recently developed receding horizon sliding control (RHSC) algorithm. The RHSC strategy is extended to multi-input multi-output systems and will be evaluated using a model predictive control (MPC) approach as a benchmark. The focus of this investigation is on comparing performance in computational logistics and output-tracking between the two control strategies. We show that RHSC can improve the level of tracking accuracy when compared to classical MPC. At the same time, it is on average more computationally efficient. The case study for evaluation is a nonlinear automotive engine cold-start emissions system.
['Shreyas Sudhakar', 'Andreas Hansen', 'J. Karl Hedrick']
Algorithmic performance of receding horizon sliding control for engine emission reduction