scholarly journals The World of Control Engineering. Spreading it's Territory. Model Predictive Control-Integration of Instrument and Control Algorithm.

1997 ◽  
Vol 117 (10) ◽  
pp. 691-694
Author(s):  
KEN'ICHI KUROTANI
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Control Algorithm ◽  
Control Engineering ◽  
The World ◽  
And Control ◽  
Control Integration

scholarly journals IMPLEMENTATION OF MODEL PREDICTIVE CONTROL AND AUTO TUNING BASED PID FOR EFFECTIVE TEMPERATURE CONTROL IN CSTR

2012 ◽  
pp. 72-77
Author(s):  
CHENIMINENI KISHORE ◽  
SYED FASEEHA SHEEREEN ◽  
T. VANDHANA ◽  
S.SRINIVASULU RAJU
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Pid Control ◽  
Dynamic State ◽  
Model Design ◽  
Control Engineering ◽  
Diverse Range ◽  
Real Model ◽  
And Control ◽  
State Analysis

Continuous Stirrer Tank Reactor (CSTR) is an important topic in process control and offering a diverse range of researches in the area of chemical and control engineering. A simulation on mathematical model has several advantages over the experiment on a real model or system, which is used for steady state analysis and dynamic state analysis. The main objective is to control the temperature of CSTR in the presence of disturbance. Various control approaches have been applied on CSTR to control its parameters through PID control and MODEL PREDICTIVE CONTROL (MPC). Model design and simulation are done in MATLAB SIMULINK.

scholarly journals How Imitation Learning and Human Factors Can Be Combined in a Model Predictive Control Algorithm for Adaptive Motion Planning and Control

Sensors ◽  
2021 ◽  
Vol 21 (12) ◽  
pp. 4012
Author(s):  
Milad Karimshoushtari ◽  
Carlo Novara ◽  
Fabio Tango
Keyword(s):  
Model Predictive Control ◽  
Motion Planning ◽  
Predictive Control ◽  
Urban Areas ◽  
Control Algorithm ◽  
Transportation Systems ◽  
Imitation Learning ◽  
Planning And Control ◽  
Computation Efficiency ◽  
And Control

Interest in autonomous vehicles (AVs) has significantly increased in recent years, but despite the huge research efforts carried out in the field of intelligent transportation systems (ITSs), several technological challenges must still be addressed before AVs can be extensively deployed in any environment. In this context, one of the key technological enablers is represented by the motion-planning and control system, with the aim of guaranteeing the occupants comfort and safety. In this paper, a trajectory-planning and control algorithm is developed based on a Model Predictive Control (MPC) approach that is able to work in different road scenarios (such as urban areas and motorways). This MPC is designed considering imitation-learning from a specific dataset (from real-world overtaking maneuver data), with the aim of getting human-like behavior. The algorithm is used to generate optimal trajectories and control the vehicle dynamics. Simulations and Hardware-In-the-Loop tests are carried out to demonstrate the effectiveness and computation efficiency of the proposed approach.

scholarly journals IMPLEMENTATION OF MODEL PREDICTIVE CONTROL AND AUTO TUNING BASED PID FOR EFFECTIVE TEMPERATURE CONTROL IN CSTR

2013 ◽  
pp. 84-89
Author(s):  
CHENIMINENI KISHORE ◽  
T. VANDHANA ◽  
SHEEREEN HUSSAIN ◽  
S.SRINIVASULU RAJU
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Pid Control ◽  
Dynamic State ◽  
Model Design ◽  
Control Engineering ◽  
Diverse Range ◽  
Real Model ◽  
And Control ◽  
State Analysis

Continuous Stirrer Tank Reactor (CSTR) is an important topic in process control and offering a diverse range of researches in the area of chemical and control engineering. A simulation on mathematical model has several advantages over the experiment on a real model or system, which is used for steady state analysis and dynamic state analysis. The main objective is to control the temperature of CSTR in the presence of disturbance. Various control approaches have been applied on CSTR to control its parameters through PID control and MODEL PREDICTIVE CONTROL (MPC). Model design and simulation are done in MATLAB SIMULINK

scholarly journals Reference Tracking using a Non-Cooperative Distributed Model Predictive Control Algorithm

2016 ◽  
Vol 49 (7) ◽  
pp. 1079-1084 ◽  
Author(s):  
Anca Maxim ◽  
Clara M. Ionescu ◽  
Constantin F. Caruntu ◽  
Corneliu Lazar ◽  
Robin De Keyser
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Control Algorithm ◽  
Distributed Model ◽  
Reference Tracking ◽  
Distributed Model Predictive Control ◽  
Model Predictive Control Algorithm

The Research of Air Precooling System Based on Generalize Predictive Control Strategy

2013 ◽  
Vol 433-435 ◽  
pp. 1091-1098
Author(s):  
Wei Bo Yu ◽  
Cui Yuan Feng ◽  
Ting Ting Yang ◽  
Hong Jun Li
Keyword(s):  
Predictive Control ◽  
Control Strategy ◽  
Control Algorithm ◽  
Exchange Process ◽  
Generalized Predictive Control ◽  
Matlab Simulation ◽  
Control Effect ◽  
Heat Exchange Process ◽  
Complex Control System ◽  
And Control

The air precooling system heat exchange process is a complex control system with features such as: nonlinear, lag and random interference. So choose Generalized Predictive Control Algorithm that has low model dependence, good robustness and control effect, as well as easy to implement. But due to the large amount of calculation of traditional generalized predictive control and can't juggle quickness and overshoot problem, an improved generalized predictive control algorithm is proposed, then carry out the MATLAB simulation, the experimental results show that the algorithm can not only greatly reduce the amount of computation, but also can restrain the overshoot and its rapidity.

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