Symmetry in Optimal Control: A Multiobjective Model Predictive Control Approach

2020 ◽  
pp. 209-237
Author(s):  
Kathrin Flaßkamp ◽  
Sina Ober-Blöbaum ◽  
Sebastian Peitz
Keyword(s):  
Optimal Control ◽  
Model Predictive Control ◽  
Predictive Control ◽  
Control Approach

A distributed model predictive control approach to cooperative adaptive cruise control of the heterogeneous platoon

2021 ◽  
pp. 095440702110705
Author(s):  
Guangming Nie ◽  
Bo Xie ◽  
Zixu Hao ◽  
Hangwei Hu ◽  
Yantao Tian
Keyword(s):  
Optimal Control ◽  
Model Predictive Control ◽  
Control Problem ◽  
Predictive Control ◽  
Control Algorithm ◽  
Sampling Period ◽  
Distributed Model ◽  
Cruise Control ◽  
Control Approach ◽  
Distributed Model Predictive Control

This paper presents a distributed model predictive control algorithm to solve the cruise control problem of a heterogeneous platoon. Each following vehicle in the platoon can use the communication equipment to receive the information of the leading vehicle and its preceding adjacent one. The vehicles in the platoon are dynamically decoupled and have different dynamic parameters. Each vehicle solves a local optimal control problem independently. The cost function of each vehicle’s local optimal control algorithm is designed with traceability as the control objective, and its asymptotic stability is guaranteed by using the terminal constraint method. In addition, the timestamps of all vehicles in the platoon are synchronous, which means that in each sampling period, a specific vehicle in the platoon cannot obtain the solution results of other vehicles’ local optimal control problems at the current sampling moment. Under this restriction, the constraints that each vehicle needs to meet to realize the platoon’s string stability are also designed. Finally, the simulation results show the effectiveness of the algorithm.

Optimal control of the blowing mode parameters during basic oxygen furnace steelmaking process

2021 ◽  
pp. 94-96
Author(s):  
Yurii Mariiash ◽  
Oleksandr Stepanets
Keyword(s):  
Optimal Control ◽  
Model Predictive Control ◽  
Predictive Control ◽  
System Modeling ◽  
Basic Oxygen Furnace ◽  
Steel Scrap ◽  
Quadratic Functional ◽  
Steelmaking Process ◽  
Basic Oxygen ◽  
Control Approach

The oxygen converter is intended for production of steel from liquid cast iron and steel scrap at blowing by oxygen. Nowadays, Basic Oxygen Furnace process is the main method for steelmaking. The main disadvantage of the basic oxygen furnace is the limited ability to increase the part of scrap metal. The task of the proposed approach is to control of the blowing mode parameters to establish the optimal level of CO2 that will ensure a minimum specific cost of steel in the presence of restrictions and boundary conditions of basic oxygen furnace steelmaking process. A model predictive control taking into account the constraints on the input signals and the quadratic functional is proposed.  The design of Model Predictive Control is based on mathematical model of an object. This approach minimizes the cost function that characterizes the quality of the process. The result of the automatic control system modeling shows that the Model Predictive Control approach provides retention of carbon dioxide level when oxygen consumption is changing. The obtained quadratic functional is optimized to find the optimal control of blowing parameters.

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