The aim of this paper is to present a new method for the nonlinear controller design. The underlying theory evolves from the introduced transfer function of nonlinear systems, that can be used in similar way as transf...
详细信息
The aim of this paper is to present a new method for the nonlinear controller design. The underlying theory evolves from the introduced transfer function of nonlinear systems, that can be used in similar way as transfer functions of classical linear systems. The presented algebra of transfer functions is the same as the linear one. Therefore, the controller design can follow the linear system synthesis. The paper shows, how to design a nonlinear PID controller using the direct method synthesis and also shows that the nonlinear state controller following the pole-placement method is equivalent to the exact linearization method. Since the presented method leads to results identical with the exact linearization method, it has been denoted as the exact velocity linearization method.
This paper presents a new topological structure for use in the context of hierarchical radiosity combined with discontinuity meshing. This is most useful for a new strategy adopted for subdividing the elements of a sc...
详细信息
This paper presents a new topological structure for use in the context of hierarchical radiosity combined with discontinuity meshing. This is most useful for a new strategy adopted for subdividing the elements of a scene consisting of convex polygons. The subdivision is done in a local optimization manner keeping the aspect ratios of produced polygons low. The generated meshes give high visual accuracy.
Measurement error due to sensor degradation (fouling, miscalibration, etc.) is more difficult to identify compared to catastrophic sensor failure. Passive methods previously proposed for sensor-level monitoring are ba...
详细信息
Measurement error due to sensor degradation (fouling, miscalibration, etc.) is more difficult to identify compared to catastrophic sensor failure. Passive methods previously proposed for sensor-level monitoring are based on power spectrum or multiscale analysis of sensor data. These methods have limitations caused by not accounting for various noise sources and assumptions about sensor noise characteristics, thus resulting in false and missed alarms. In this paper, an online sensor fault detection scheme based on the identification of sensor response characteristics is proposed and evaluated. We develop both robust passive and active in situ techniques to identify sensor response characteristics that relate directly to its health. Using the identified sensor model, various kinds of sensor faults are quantified and mapped into the model parameters. A dynamic model-based estimator is proposed for data reconciliation. These ideas were experimentally validated using thermocouples, flowmeters, and resistance thermometric devices on laboratory-scale processes. The proposed approach was seen to accurately quantify the sensor model parameters and aid in measurement reconstruction.
This paper presents an approach to calculate prefilters that are insensitive to parameter deviations. The cost function chosen for this approach is the magnitude of the time-delay filter transfer function. By approxim...
详细信息
This paper presents an approach to calculate prefilters that are insensitive to parameter deviations. The cost function chosen for this approach is the magnitude of the time-delay filter transfer function. By approximating the cost function with a polynomial, the effort of calculating minimax robust profiles can be reduced. The resulting control profiles yield a performance similar to the minimax robust controller. This is verified by the numerical results included in this paper.
In this paper, a genetic algorithm based on Infeasibility Degree (IFD) selection is proposed for constrained optimization problems. Initial solutions and intermediate solutions are allowed to be feasible as well as in...
详细信息
ISBN:
(纸本)0780379527
In this paper, a genetic algorithm based on Infeasibility Degree (IFD) selection is proposed for constrained optimization problems. Initial solutions and intermediate solutions are allowed to be feasible as well as infeasible as penalty function methods. The infeasibility degree of a solution (IFD) is defined as the sum of the square value of all the constraints violation and the infeasibility degree selection of the population is designed through checking whether the IFD of a solution is less than or equal to a threshold value or not to decide the candidate solution is acceptable or refusable. The method is divided into two stages: first, initial IFD selection is carried out to produce enough initial feasible solution;then the GAs based on Annealing IFD selection is applied to search for the feasible optimum solution. Two selected problems are used to test the algorithm performance.
With predictive control most of the computation time is spent for the simulation of the predicted variables and for the optimization if constraints or nonlinear processes are assumed. In addition to the known blocking...
详细信息
With predictive control most of the computation time is spent for the simulation of the predicted variables and for the optimization if constraints or nonlinear processes are assumed. In addition to the known blocking technique for the manipulated variable another possibility is calculating the control error not in each sampling point of the prediction horizon but only in some coincidence points. It will be shown that the best choice is to allocate the coincidence points exponentially thus that with small prediction steps more and with increasing prediction steps less coincidence points are considered. As a practical example the multivariable control of a distillation column model illustrates the benefits of the method presented.
Long-range optimal prediction algorithms use the predicted output for several steps ahead. The prediction based on traditionally estimated model parameters does not result in an optimal prediction if the measurements ...
详细信息
Long-range optimal prediction algorithms use the predicted output for several steps ahead. The prediction based on traditionally estimated model parameters does not result in an optimal prediction if the measurements are noisy or/and model structure differs from real process structure. In this paper two different identification schemes are presented and compared: long-range predictive single-model identification and simultaneous multi-step-ahead prediction identification. It is shown that the first method is easier to realize but the second one leads to more accurate results. Both methods are derived for a first-order model in details. Simulation runs and a level control example illustrate the algorithms presented.
Traditional approaches to controller designs that guarantee fast compensation of load torque and reference variations result in design iterations and most of the time in poorer response for load torque variations. In ...
详细信息
Traditional approaches to controller designs that guarantee fast compensation of load torque and reference variations result in design iterations and most of the time in poorer response for load torque variations. In this paper a reference model for desired drive behavior generation and optimization methods has been applied to achieve controller integral time constant lower than the maximum time constant of the PM brushless DC motor drive. Presented simulation results show that using reference model for desired drive behavior generation, it is possible to determine optimal controller parameters for faster (10 time) and better (2 time) load torque compensation than in the case of traditional design of speed controller parameters. Response due to reference input with constrained overshoot has been achieved using a filter in the servosystem input. Thereby, the proposed method demonstrates the design of a speed controller that is optimal for both load torque and reference variations and its verification with simulation are accomplished for a permanent magnet brushless dc motor drive.
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 ...
详细信息
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...
详细信息
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.
暂无评论