Proceedings ArticleDOI
Controller design based on Model Predictive Control for a nonlinear process
Nithya Venkatesan,N. Anantharaman +1 more
- pp 1-6
TLDR
In this paper, the controller design is compared based on conventional Proportional Integral (PI) based on Skogestad's settings with Model Predictive Control (MPC).Abstract:
Nowadays process industries require accurate, efficient and flexible operation of the plants. The need for development of innovative technologies for process modeling, dynamic trajectory optimization and high performance industrial process control is always a challenge. The process considered for modeling is a conical tank liquid level system. Control of liquid level in a conical tank is nonlinear due to the variation in the area of cross section with change in shape. Black box modeling is used to identify the system, which is identified to be nonlinear and approximated to be a First Order Plus Dead Time (FOPDT) model. Here the controller design is compared based on conventional Proportional Integral (PI) based on Skogestad's settings with Model Predictive Control (MPC).read more
Citations
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Journal ArticleDOI
Model based Controller Design for Conical Tank System
TL;DR: This paper proposes to obtain the mathematical modelling of a conical tank system and to design model based controller (Internal Model Control) for controlling the level in it and to have better closed loop performance and robustness when compared to PID controller.
Proceedings ArticleDOI
Disturbance observer structure based internal model control for time delay systems
TL;DR: A Disturbance Observer (DOB) like structure of Internal Model Control (IMC) for Single-Input-Single-Output (SISO) time delay systems and robustness with respect to parametric uncertainty have been evaluated using simulation.
Journal Article
Direct Inverse Control for a Conical Tank byUsing Takagi-Sugeno Fuzzy Model
TL;DR: The neural network is obtained without training and testing and its complexity in terms of neuron number is reduced and the robustness of the proposed controllers to changes in the plant model is demonstrated.
Dissertation
Aportaciones al control inverso con modelo de referencia basado en lógica borrosa, redes neuronales y algoritmos genéticos
TL;DR: In this article, a modelo borroso mediante the Takagi-Sugeno algorithm is used to represent a planta with modelos locales lineales and for ello se modela de forma borrosa mediantee el tipo Takagi Sugeno, obtenido a partir del algoritmo de agrupamiento Gustafson-Kessel modificado.
References
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Journal ArticleDOI
Optimum Settings for Automatic Controllers
J. G. Ziegler,N. B. Nichols +1 more
TL;DR: In this paper, the three principal control effects found in present controllers are examined and practical names and units of measurement are proposed for each effect and corresponding units for a classification of industrial processes in terms of two principal characteristics affecting their controllability.
Journal ArticleDOI
Model predictive control: theory and practice—a survey
TL;DR: The flexible constraint handling capabilities of MPC are shown to be a significant advantage in the context of the overall operating objectives of the process industries and the 1-, 2-, and ∞-norm formulations of the performance objective are discussed.
Book
Model Predictive Control
TL;DR: In this article, the authors present a model predictive controller for a water heating system, which is based on the T Polynomial Process (TOP) model of the MPC.
Optimum Settings for Automatic Controllers
TL;DR: In this paper, the three principal control effects found in present controllers are examined and practical names and units of measurement are proposed for each effect.
Journal ArticleDOI
Model predictive control: past, present and future
Manfred Morari,Jay H. Lee +1 more
TL;DR: In this article, a theoretical basis for model predictive control (MPC) has started to emerge and many practical problems like control objective prioritization and symptom-aided diagnosis can be integrated into the MPC framework by expanding the problem formulation to include integer variables yielding a mixed-integer quadratic or linear program.