Titlebook: Lasso-MPC – Predictive Control with ℓ1-Regularised Least Squares; Marco Gallieri Book 2016 Springer International Publishing Switzerland 2

LEERY

都相信我的话

有特色

文字

Principles of LASSO MPC,Least Absolute Selection and Shrinking Operator (LASSO) is a powerful regression technique, which aims to induce sparseness in the solution (Tibshirani .; Osborne and Presnell .; Kim et al. .; Ohlsson .; Schmidt .; Schuet .).

男生如果明白

Robust Tracking with Soft Constraints,It is becoming standard among researchers to use a terminal constraint in MPC. This constraint generally depends on the particular set-point we want to regulate the plant to. For changing set-points this means changing the terminal constraint, which could make the problem infeasible.

沉着

Concluding Remarks,This is suitable, for instance, for control applications where the control signals are required to be sparse in their magnitudes or in their time-increments.

certain

https://doi.org/10.1007/978-3-319-27963-3Asychronous actuator interventions; LASSO Model Predictive Control; LASSO cost function; Least Absolute

承认

Introduction,ance automatic systems necessarily features the design of smart control algorithms, for scenarios such as power generation or energy saving. In general, an automatic system has to satisfy a particular performance specification, which is tightly related to its particular application field.

Servile

angina-pectoris

Ship Roll Reduction with Rudder and Fins,ddressed in the control literature as surveyed in Perez, Ship motion control: course keeping and roll stabilization using rudder and fins (.). The considered set-up is shown in Fig. .. The system, controlled by rudder and fins, is ..