scholarly journals Some Control and Observation Issues in Cellular Automata

2021 ◽  
Vol 30 (3) ◽  
pp. 391-413
Author(s):  
Samira El Yacoubi ◽  
◽  
Théo Plénet ◽  
Sara Dridi ◽  
Franco Bagnoli ◽  
...  
Keyword(s):  
Cellular Automata ◽  
Control Theory ◽  
State Space Model ◽  
Review Article ◽  
Distributed Parameter ◽  
Space Model ◽  
Key Concepts ◽  
Discrete Counterpart ◽  
Controllability And Observability ◽  
Work First

This review article focuses on studying problems of observability and controllability of cellular automata (CAs) considered in the context of control theory, an important feature of which is the adoption of a state-space model. Our work first consists in generalizing the obtained results to systems described by CAs considered as the discrete counterpart of partial differential equations, and in exploring possible approaches to prove controllability and observability. After having introduced the notion of control and observation in cellular automata models, in a similar way to the case of discrete-time distributed parameter systems, we investigate these key concepts of control theory in the case of complex systems. For the controllability issue, the Boolean class is particularly studied and applied to the regional case, while the observability is approached in the general case and related to the reconstructibility problem for linear or nonlinear CAs.

scholarly journals Incremental State-Space Model Predictive Control of a Fresnel Solar Collector Field

Energies ◽  
2018 ◽  
Vol 12 (1) ◽  
pp. 3 ◽  
Author(s):  
Eduardo Camacho ◽  
Antonio Gallego ◽  
Adolfo Sanchez ◽  
Manuel Berenguel
Keyword(s):  
Model Predictive Control ◽  
Power Systems ◽  
State Space ◽  
Predictive Control ◽  
State Space Model ◽  
Distributed Parameter ◽  
Space Model ◽  
Luenberger Observer ◽  
Predictive Controller ◽  
Nonlinear Distributed Parameter Model

Model predictive control has been demonstrated to be one of the most efficient control techniques for solar power systems. An incremental offset-free state-space Model Predictive Controller (MPC) is developed for the Fresnel collector field located at the solar cooling plant installed on the roof of the Engineering School of Sevilla. A robust Luenberger observer is used for estimating the states of the plant which cannot be measured. The proposed strategy is tested on a nonlinear distributed parameter model of the Fresnel collector field. Its performance is compared to that obtained with a gain-scheduling generalized predictive controller. A real test carried out at the real plant is presented, showing that the proposed strategy achieves a very good performance.

scholarly journals Modal-Decomposition-Dependent State-Space Modeling and Modal Analysis of a Rigid-Flexible, Coupled, Multifreedom Motion System: Theory and Experiment

2020 ◽  
Vol 2020 ◽  
pp. 1-16
Author(s):  
Qian Tang ◽  
Fuyu Guo ◽  
Tao Huang ◽  
Kaiming Yang ◽  
Yu Zhu ◽  
...  
Keyword(s):  
Modal Analysis ◽  
State Space ◽  
Degrees Of Freedom ◽  
State Space Model ◽  
Standard State ◽  
Modal Decomposition ◽  
Space Model ◽  
Motion System ◽  
Controllability And Observability ◽  
Dependent State

In a multiple degrees of freedom motion system with rigid-flexible coupling, the flexible internal dynamics have a significant negative impact on performance because the degrees of freedom are coupled. Inspired by this problem, a multi-input multioutput state-space model based on modal coordinates is proposed to decouple the rigid body and flexible modes. The closed-loop subspace identification method based on orthogonal is utilized to develop an unbiased standard state-space model. Based on the similarity principle, a modal analysis method is proposed to transfer the standard state-space model to the proposed modal-decomposition-dependent state-space model. Controllability and observability criteria are met to guarantee the minimum realization of the proposed state-space model. Finally, a modeling and modal analysis experiment is conducted on a developed wafer stage of lithographic tool. The results verify the effectiveness and accuracy of the proposed modeling method, as well as the controllability and observability of the proposed model.

scholarly journals The Cascade Control of Natural Gas Pipeline Systems

2019 ◽  
Vol 9 (3) ◽  
pp. 481
Author(s):  
Kai Wen ◽  
Jing Gong ◽  
Yan Wu
Keyword(s):  
Natural Gas ◽  
Control Theory ◽  
State Space ◽  
State Space Model ◽  
The State ◽  
Gas Pipeline ◽  
Cascade Control ◽  
Gas Pipelines ◽  
Space Model ◽  
Natural Gas Pipelines

With the boost of natural gas consumption, an automatic gas pipeline scheduling method is required to replace the dispatchers in decision making. Since the state space model is the fundamental work of modern control theory, it is possible that the classical controller synthesis method can be used for the complicated gas pipeline controller design. In this paper, a cascade control algorithm is proposed based on the state space model that is used for the transient flow simulation of the natural gas pipelines. A linear quadratic regulator is designed following the classical optimal control theory. Finally, the transient process with different control methods shows the effectiveness of the cascade control using information of the entire pipeline. According to the hardware configuration of natural gas pipelines, automatic scheduling process is ready to deploy as one step to the intelligent natural gas pipelines.

Multivariable modeling and control of an activated sludge process

1998 ◽  
Vol 37 (12) ◽  
pp. 149-156 ◽  
Author(s):  
Carl-Fredrik Lindberg
Keyword(s):  
Activated Sludge ◽  
Nitrate Concentration ◽  
State Space Model ◽  
Activated Sludge Process ◽  
Invariant State ◽  
Linear Quadratic ◽  
Modeling And Control ◽  
Space Model ◽  
And Control ◽  
Time Invariant

This paper contains two contributions. First it is shown, in a simulation study using the IAWQ model, that a linear multivariable time-invariant state-space model can be used to predict the ammonium and nitrate concentration in the last aerated zone in a pre-denitrifying activated sludge process. Secondly, using the estimated linear model, a multivariable linear quadratic (LQ) controller is designed and used to control the ammonium and nitrate concentration.

Development of L1-norm sliding mode observer for sensor fault diagnosis of an industrial gas turbine

2021 ◽  
pp. 095965182199617
Author(s):  
Mahyar Akbari ◽  
Abdol Majid Khoshnood ◽  
Saied Irani
Keyword(s):  
Fault Detection ◽  
State Space ◽  
Gas Turbine ◽  
Sliding Mode ◽  
State Space Model ◽  
Sensor Fault ◽  
Space Model ◽  
Decision Logic ◽  
Sensor Fault Detection ◽  
Industrial Gas Turbine

In this article, a novel approach for model-based sensor fault detection and estimation of gas turbine is presented. The proposed method includes driving a state-space model of gas turbine, designing a novel L1-norm Lyapunov-based observer, and a decision logic which is based on bank of observers. The novel observer is designed using multiple Lyapunov functions based on L1-norm, reducing the estimation noise while increasing the accuracy. The L1-norm observer is similar to sliding mode observer in switching time. The proposed observer also acts as a low-pass filter, subsequently reducing estimation chattering. Since a bank of observers is required in model-based sensor fault detection, a bank of L1-norm observers is designed in this article. Corresponding to the use of the bank of observers, a two-step fault detection decision logic is developed. Furthermore, the proposed state-space model is a hybrid data-driven model which is divided into two models for steady-state and transient conditions, according to the nature of the gas turbine. The model is developed by applying a subspace algorithm to the real field data of SGT-600 (an industrial gas turbine). The proposed model was validated by applying to two other similar gas turbines with different ambient and operational conditions. The results of the proposed approach implementation demonstrate precise gas turbine sensor fault detection and estimation.

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