... and rescue, and agricultural automation while addressing challenges related to coordination, communication, and task assignment. Model predictive control (MPC) stands out as a promising controller for multirobot control due to its preview capability and effective constraint handling. However, MPC's...

...Michele Ambrosino; Miguel Castroviejo-Fernandez; Jordan Leung; Ilya Kolmanovsky This paper analyzes the suboptimal implementation of shrinking horizon model predictive control (SHMPC) when a fixed number of solver iterations and a warm-start are utilized at each time-step to solve the underlying...

... in all three directions, i.e., vertical, roll, and pitch. Considering this kind of multi-objective coordinated control problem, Model Predictive Control (MPC) gains lots of attention in the recent decade. However, the MPC algorithm is expensive for real-time implementations due to its computational...

...Linhe Ge; Yang Zhao; Shouren Zhong; Zitong Shan; Fangwu Ma; Konghui Guo; Zhiwu Han Model predictive control (MPC) is the mainstream method in the motion control of autonomous vehicles. However, due to the complex and changeable driving environment, the perturbation of vehicle parameters will cause...

... into a multihorizon model predictive control (MH-MPC) for integrated power and thermal management (iPTM) of connected vehicles. The results of design and evaluation of the performance of the proposed data-informed MH-MPC for iPTM of connected hybrid electric vehicles (HEVs) using traffic data for real-world city...

... is updated continuously online using collected sensor data to capture the variations in system dynamics, rectify the OANN prediction, and eventually minimize the discrepancy between the OANN-predicted and actual response. The combined OANN–NNC model then reconfigures the model predictive control (MPC) online...

...). Then a direct yaw-moment control (DYC) strategy employing an unbiased adaptive model predictive control (MPC) algorithm is proposed to compensate for the influences. An unbiased estimation strategy is developed to update the time-variant prediction model for the adaptive MPC system. An extended magic formula...

...Bin Xu; Adamu Yebi; Dhruvang Rathod; Simona Onori; Zoran Filipi; Mark Hoffman This paper discusses an experimental validation of a real-time augmented control scheme for an organic Rankine cycle (ORC) waste heat recovery (WHR) system. A nonlinear model predictive control (NMPC) is designed...

... EASUREMENT, AND C ONTROL . Manuscript received November 13, 2018; final manuscript received March 15, 2019; published online May 2, 2019. Assoc. Editor: Huiping Li. 13 11 2018 15 03 2019 adaptive cruise control model predictive control multi-objective control nonlinear dynamics...

... is required for ammonia generation. The purpose of this study is to develop a model-predictive control (MPC) scheme for a lean-burn gasoline engine coupled with a passive SCR system to minimize the total equivalent fuel penalty associated with passive SCR operation while satisfying stringent NO x and ammonia...

... control performance than model predictive control (MPC) in both studies. In the first study, MPC was shown to get worse as the process lag increases but FBPC was unaffected by process lag. In the diabetes simulation study, for five surrogate type 1 diabetes subjects, the standard deviation of G about its...

...Prem Kumar; B. Bhavya Anoohya; Radhakant Padhi Inspired by fast model predictive control (MPC), a new nonlinear optimal command tracking technique is presented in this paper, which is named as “Tracking-oriented Model Predictive Static Programming (T-MPSP).” Like MPC, a model-based prediction...