scholarly journals Advanced Construction of the Dynamic Matrix in Numerically Efficient Fuzzy MPC Algorithms

Algorithms ◽  
2021 ◽  
Vol 14 (1) ◽  
pp. 25
Author(s):  
Piotr M. Marusak
Keyword(s):  
Process Model ◽  
Linear Models ◽  
Control Plant ◽  
Fuzzy Model ◽  
Nonlinear Process ◽  
Linear Constraints ◽  
Good Prediction ◽  
Dynamic Matrix ◽  
Prediction And Control ◽  
And Control

A method for the advanced construction of the dynamic matrix for Model Predictive Control (MPC) algorithms with linearization is proposed in the paper. It extends numerically efficient fuzzy algorithms utilizing skillful linearization. The algorithms combine the control performance offered by the MPC algorithms with nonlinear optimization (NMPC algorithms) with the numerical efficiency of the MPC algorithms based on linear models in which the optimization problem is a standard, easy-to-solve, quadratic programming problem with linear constraints. In the researched algorithms, the free response obtained using a nonlinear process model and the future trajectory of the control signals is used to construct an advanced dynamic matrix utilizing the easy-to-obtain fuzzy model. This leads to obtaining very good prediction and control quality very close to those offered by NMPC algorithms. The proposed approach is tested in the control system of a nonlinear chemical control plant—a CSTR reactor with the van de Vusse reaction.

scholarly journals Identification and control of a heat flow system based on the Takagi-Sugeno fuzzy model using the grey wolf optimization algorithm

2021 ◽  
pp. 324-324
Author(s):  
Radisa Jovanovic ◽  
Vladimir Zaric
Keyword(s):  
Heat Flow ◽  
Linear Models ◽  
Fuzzy Controller ◽  
Flow System ◽  
Fuzzy Model ◽  
Grey Wolf ◽  
Optimization And Control ◽  
Takagi Sugeno ◽  
And Control ◽  
Operating Points

Even though, it is mostly used by process control engineers, the temperature control remains an important task for researchers. This paper addressed two separate issues concerning model optimization and control. Firstly, the linear models for the three different operating points of the heat flow system were found. From these identified models a Takagi-Sugeno model is obtained using fixed membership functions in the premises of the rules. According to the chosen objective function, parameters in the premise part of Takagi-Sugeno fuzzy model were optimized using the grey wolf algorithm. Furthermore, by using the parallel distributed compensation a fuzzy controller is developed via the fuzzy blending of three proportional + sum controllers designed for each of the operating points. In order to evaluate performance, a comparison is made between the fuzzy controller and local linear controllers. Moreover, the fuzzy controllers from the optimized and initial Takagi-Sugeno plant models are compared. The experimental results on a heat flow platform are presented to validate efficiency of the proposed method.

An insight into Case Management and Challenges in Veteran Suicide Prevention

2020 ◽  
pp. 14-25
Author(s):  
Tamara Green
Keyword(s):  
Case Management ◽  
Suicide Prevention ◽  
Suicide Risk ◽  
Digital Transformation ◽  
Prevention Science ◽  
Historical Records ◽  
Military Members ◽  
Prediction And Control ◽  
And Control ◽  
Insight Into

Much of the literature, policies, programs, and investment has been made on mental health, case management, and suicide prevention of veterans. The Australian “veteran community is facing a suicide epidemic for the reasons that are extremely complex and beyond the scope of those currently dealing with them.” (Menz, D: 2019). Only limited work has considered the digital transformation of loosely and manual-based historical records and no enablement of Artificial Intelligence (A.I) and machine learning to suicide risk prediction and control for serving military members and veterans to date. This paper presents issues and challenges in suicide prevention and management of veterans, from the standing of policymakers to stakeholders, campaigners of veteran suicide prevention, science and big data, and an opportunity for the digital transformation of case management.

Modelling and control of an alkaline water electrolysis process

2018 ◽  
Vol 1 (2) ◽  
pp. 9-14
Author(s):  
Marisol Cervantes-Bobadilla ◽  
Ricardo Fabricio Escobar Jiménez ◽  
José Francisco Gómez Aguilar ◽  
Tomas Emmanuel Higareda Pliego ◽  
Alberto Armando Alvares Gallegos
Keyword(s):  
Process Model ◽  
Water Electrolysis ◽  
Alkaline Water Electrolysis ◽  
Alkaline Water ◽  
Electrolysis Process ◽  
Linear Dynamic ◽  
Energy Current ◽  
Identification Technique ◽  
Nonlinear Static ◽  
And Control

In this research, an alkaline water electrolysis process is modelled. The electrochemical electrolysis is carried out in an electrolyzer composed of 12 series-connected steel cells with a solution 30% wt of potassium hydroxide. The electrolysis process model was developed using a nonlinear identification technique based on the Hammerstein structure. This structure consists of a nonlinear static block and a linear dynamic block. In this work, the nonlinear static function is modelled by a polynomial approximation equation, and the linear dynamic is modelled using the ARX structure. To control the current feed to the electrolyzer an unconstraint predictive controller was implemented, once the unconstrained MPC was simulated, some restrictions are proposed to design a constrained MPC (CMPC). The CMPC aim is to reduce the electrolyzer's energy consumption (power supply current). Simulation results showed the advantages of using the CMPC since the energy (current) overshoots are avoided.

The Frustration Regulation Journal: A Reflective Framework for Educators

Relay Journal ◽  
2019 ◽  
Author(s):  
Sam Morris
Keyword(s):  
Emotion Regulation ◽  
Process Model ◽  
Negative Impact ◽  
Language Education ◽  
Short Article ◽  
Language Classroom ◽  
As Stress ◽  
And Control ◽  
Important System ◽  
Behavioural Strategies

Teachers and advisors involved in the emotional business of language education feel frustrated from time to time, and if such emotions are not managed healthily, they may lead to negative outcomes such as stress and burnout. One important system for taking control of frustration is emotion regulation, the cognitive and behavioural strategies through which individuals manage their emotions. In this short article, I define frustration and discuss its negative impact on the language classroom. I then introduce a structured reflective journaling tool, built upon Gross’s Process model of emotion regulation (Gross, 2014, 2015) which may help teachers and advisors develop greater awareness and control over experiences of frustration.

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