In already installed fieldbus instrumentations, a configuration-free and manufacturer-independent access to field device information sets is still missing. Due to the lack of suitable and simple models, as well as of ...
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In already installed fieldbus instrumentations, a configuration-free and manufacturer-independent access to field device information sets is still missing. Due to the lack of suitable and simple models, as well as of interaction patterns of field devices in various information worlds of processcontrolengineering, the practical use made of device novelties is rather complex. This affects high investments for engineering this information in various applications of processcontrolengineering. Modern field devices contain embedded information sets that are ever-increasing, and provide great opportunity for innovative asset management functionality. In this paper we present an information server, serving as an additional information channel between field and plant level in process industry. We show that this so-called asset management box provides the configuration-free analysis of fieldbus segments, the open access to installed field devices and the automatically updated, structured and self-descriptive presentation of their embedded information sets. Its basic functionality fulfills one prerequisite of an efficient asset management system: the analysis of the actual state of a fieldbus installation, without prior knowledge about the installed field devices and enhanced investments in engineering. We discuss several asset management applications, implemented on the asset management box. To prevent excessive investments for engineering of asset management applications themselves, widest flexibility and extensibility of the management systems' functionality is required. The box's structure permits easy extensibility of plant and client-specific applications as well as the easy integration of specific fieldbus hardware, the box provides a universal fieldbus interface.
In this paper, a direct learning control method for a class of switched systems is proposed. The objective of direct learning is to generate the desired control profile for a newly switched system without any feedback...
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In this paper, a direct learning control method for a class of switched systems is proposed. The objective of direct learning is to generate the desired control profile for a newly switched system without any feedback, even if the system may have uncertainties. This is achieved by exploring the inherent relationship between any two systems before and after a switch. The new method is applicable to a class of linear time varying, uncertain and switched systems, when the trajectory tracking control problem is concerned. A numerical simulation demonstrates the effectiveness of the proposed method.
The paper discusses possible ways how to incorporate an existing controller into the predictive control framework. This idea is used in anti-wind up framework, where the performance can degrade in some cases. The basi...
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The paper discusses possible ways how to incorporate an existing controller into the predictive control framework. This idea is used in anti-wind up framework, where the performance can degrade in some cases. The basic requirements are to meet the performance of the nominal controller in the unconstrained case and to guarantee stability in the constrained case.
Disturbance rejection performance is usually the most important aspect in designing controller in the process and the chemical industries. On the other hand, such tuned control loop may exhibit large overshoots on ref...
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Disturbance rejection performance is usually the most important aspect in designing controller in the process and the chemical industries. On the other hand, such tuned control loop may exhibit large overshoots on reference tracking. The only way to decrease overshoot is to use two-degrees-of-freedom (2-DOF) controllers. Unfortunately, reducing the overshoot usually results in slower tracking response when using some of the most common 2-DOF controller structures. This paper suggests using additional first-order filter on the set-point of the PI controller in order to improve tracking performance. The calculation of compensator's parameters is straightforward and can be easily performed in practice. Several examples confirmed the efficiency of the proposed approach.
In this paper a non-linear fuzzy autopilot for ship track-keeping is presented. The proposed autopilot has four inputs (actual and desired heading, rate of change of heading and offset from the desired path) and one o...
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In this paper a non-linear fuzzy autopilot for ship track-keeping is presented. The proposed autopilot has four inputs (actual and desired heading, rate of change of heading and offset from the desired path) and one output (command rudder angle). The track-keeping problem is decomposed into two subtasks: (i) followthe desired heading, and (ii) bring the ship onto the desired path and keep tracking. Internally, the autopilot consists of two autopilots that fulfil these tasks simultaneously. The proposed control scheme has been verified using a non-linear model of a Mariner-class vessel and steering mechanism under the influence of wave and current disturbances. Results presented show how such a control strategy enables improved tracking performance.
This paper describes the application of a technique for the two-dimensional frequency domain analysis of the closed-loop performance of a cross-directional papermaking process under industrial model predictive control...
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This paper describes the application of a technique for the two-dimensional frequency domain analysis of the closed-loop performance of a cross-directional papermaking process under industrial model predictive control (MPC). For such spatially-distributed systems, the process model and the linear portion of the controller are approximated as linear, spatially-invariant, and time-invariant. The closed-loop performance of these systems can then be analyzed in terms of a family of SISO systems by diagonalizing the large-scale transfer matrices across spatial frequencies. Familiar concepts from controlengineering such as bandwidth and stability margin are extended into the two-dimensional frequency domain.
This paper describes the principles of an intelligent automaton for controlling the secondary stage of a wastewater treatment plant. The automaton has been implemented as a finite state machine that can be integrated ...
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This paper describes the principles of an intelligent automaton for controlling the secondary stage of a wastewater treatment plant. The automaton has been implemented as a finite state machine that can be integrated into the existing supervisory control and data acquisition system of any wastewater treatment plant. Human knowledge, in the form of linguistic rules, is embedded in the automaton, which has been shown to be capable of controlling the process very satisfactorily in all but extreme conditions.
The paper presents a control system design technique in delta domain for IMC (Internal Model control) structure. Also a generalised form for delta domain Dead-beat control algorithm is given, a hybrid implementation o...
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The paper presents a control system design technique in delta domain for IMC (Internal Model control) structure. Also a generalised form for delta domain Dead-beat control algorithm is given, a hybrid implementation of the controller (Z-domain combined with delta domain) is presented and its architecture is compared with the pure deltadomain implementation. The effect of placing the limitations in the IMC structure is also studied. The hybrid control structure is compared with a similar Dead-beat controller in Z-domain for second and third order plants (benchmarks). An illustrative sensitivity analysis between the hybrid control system and the Z-domain system has been performed.
For predictive control in industry often very long horizons for control error and manipulated signal are used because of the slow processes which take place in the petrochemical industry. In order to reduce the comput...
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For predictive control in industry often very long horizons for control error and manipulated signal are used because of the slow processes which take place in the petrochemical industry. In order to reduce the computational effort some commercial predictive control program packages offer the ability to reduce the number of points in both horizons but do not recommend how to select the points which have to be considered in the horizon of the control error and manipulated variable. In this work the authors introduce an optimal choice not only of the horizon lengths itself but also for the strategy of reducing the number of points in the horizons. A genetic optimization algorithm was used both for the search for the optimal length of the horizons and for the best allocation of the points in the horizons. The results of the optimization process where used to deduct a simple rule.
Most industrial processes are nonlinear. In such a case only a nonlinear model valid for the whole working area can ensure a good controller design. The nonlinear process is approximated by a multi-model consisting of...
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Most industrial processes are nonlinear. In such a case only a nonlinear model valid for the whole working area can ensure a good controller design. The nonlinear process is approximated by a multi-model consisting of the intelligent combination of some linear sub-models. As a very practical way the following identification strategy was used: independent model parameter estimation in the different working points and the calculation of the global valid model output as the weighted sum of the sub-models. As a weighting function the Gaussian function is used. The parameters of the Gaussian function were chosen either without or with optimization of the identification cost function. The global valid nonlinear model was used for model based predictive control. A heat exchanger example illustrates the method.
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