An approximation procedure is presented for a class of hybrid systems in which switching occurs only when the continuous state trajectory crosses thresholds defined by a rectangular partitioning of the state space. Th...
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Model Predictive control Technology has been successfully applied to industry for more than two decades. Most of the applications appear in refining and petrochemical industry. Relatively few applications could be fou...
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Model Predictive control Technology has been successfully applied to industry for more than two decades. Most of the applications appear in refining and petrochemical industry. Relatively few applications could be found in the chemical industry. In this paper, the approach to evaluate the benefit that could be obtained by implementing MPC as a supervisory controller to a specialty chemical plant is explained in detail. The process and the basic plantwide control structures are simulated in Speedup. The plant pie-testing and plant testing are both done in Speedup. DMC+ commercial software is used to identify the linear model from the plant, build the controller, and tune the controller. By using the interface software between Speedup and DMC+, the process operating under DMC+ can be successfully simulated. The benefits from DMC+ can also be clearly identified in the simulation study. Some important issues in this approach are also pointed out.
The need to achieve reliable and effective automatic control systems has directed numerous research efforts towards the development of monitoring and assessment methods of the closed-loop performance. A new controller...
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The need to achieve reliable and effective automatic control systems has directed numerous research efforts towards the development of monitoring and assessment methods of the closed-loop performance. A new controller assessment index, called Relative Variance Index or RVI, is introduced in this work, according to which the closed loop performance is compared with the theoretically best control action (minimum variance control) and no control action. For the estimation of RVI, an identification method is employed to extract the system models and an estimate of the process unit delays. The proposed index, RVI, is in agreement with the classical deterministic closed-loop assessment measures and thus can be utilized for the controller performance evaluation more effectively.
Model predictive control technology has been successfully applied within the industry for more than 20 years. Most of the applications appear in the refining and petrochemicals industry, with few in specialty chemical...
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Model predictive control technology has been successfully applied within the industry for more than 20 years. Most of the applications appear in the refining and petrochemicals industry, with few in specialty chemical plant. In this paper DMC+ commercial multivariable control software is evaluated for a specialty chemicalprocess using offline simulation. The relative benefit that can be obtained from DMC+ above and beyond advanced regulatory plantwide control is carefully studied. In this study, DMC+ is built as a supervisory controller on the decentralized SISO plantwide control structure. DMC+ uses the setpoints of PI controllers as the manipulated variables. In this paper, different plantwide control structures are used and the performance of DMC+ on top of all these different plantwide control structures are compared. It will be shown that a well designed regulatory plantwide control structure is necessary to stabilize and linearize the process around some operating point. Good plantwide control design will give a better performance for DMC+.
Pseudo-linear neural networks (PNN) based modeling and control strategy for a class of nonlinear dynamic systems is proposed. The training of the PNN is implemented by using a recursive prediction error (RPE) algorith...
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Pseudo-linear neural networks (PNN) based modeling and control strategy for a class of nonlinear dynamic systems is proposed. The training of the PNN is implemented by using a recursive prediction error (RPE) algorithm. The control strategy is based on one-step-ahead prediction, in which a direct controller design for an affine nonlinear system and the second order based optimization for a general nonlinear system are adopted. The stability of the closed loop control system is investigated, and some sufficient conditions for the local asymptotic stability are derived. The some simulated examples showed the good results of proposed control strategies in this paper.
The task of verifying the correct (with respect to a given specification) behaviour of discrete event controllers for continuous processes requires to combine model types of continuous and of discrete nature. In this ...
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The task of verifying the correct (with respect to a given specification) behaviour of discrete event controllers for continuous processes requires to combine model types of continuous and of discrete nature. In this contribution, the verification problem is treated by approximating the continuous dynamics using automata models, and by carrying out a reachability analysis in the discrete domain. The focus is on different methods to generate timed automata and hybrid automata from switched continuous systems. Furthermore, some model properties and their effects on the analysis results are discussed.
This paper presents a general methodology for developing Nonlinear Low Order Model (NLLOM) from data collected from large detailed nonlinear models. This methodology is divided into two tasks: development of an Averag...
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This paper presents a general methodology for the development of Nonlinear Low Order Models (NLLOM) from data collected from detailed nonlinear simulation models. This methodology is divided into two tasks: developmen...
This paper presents a general methodology for the development of Nonlinear Low Order Models (NLLOM) from data collected from detailed nonlinear simulation models. This methodology is divided into two tasks: development of a Average Linear Low Order Model (ALLOM) and augmentation of the ALLOM to form a NLLOM, the latter task being the focus of this paper. The tools examined for the nonlinear augmentation of the ALLOM include stepwise regression and nonlinear optimization. Results will be presented for the application of these techniques towards the development of an NLLOM from a detailed high purity distillation simulation.
A steady state, multivariable, and nonlinear measure is presented for assessing the input-output, open-loop controllability of a process. This measure is ascertaining the inherent controllability of the process, as it...
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A steady state, multivariable, and nonlinear measure is presented for assessing the input-output, open-loop controllability of a process. This measure is ascertaining the inherent controllability of the process, as it is calculated in the absence of any regulatory control structure. It is also independent of the inventory control structure that might be assumed present in order to keep the inventory levels constant. This measure evaluates the ability of a design to reach all points of the desired output space and to reject the expected disturbances utilizing input action not exceeding the available input space. Besides being applicable to a SISO case, its multivariable character is shown to be more accurate than existing measures such as RGA, minimum singular value, and condition number.
The implementation of a new estimation method with alternative process models for the state estimation of the baker’s yeast fermentation is presented. Some of the implementation issues are discussed using the data ob...
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The implementation of a new estimation method with alternative process models for the state estimation of the baker’s yeast fermentation is presented. Some of the implementation issues are discussed using the data obtained from simulation tests.
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