This paper discusses issues of model adaptation in a Wiener model based nonlinear predictive control (WNPC). WNPC is an extension of state-space generalized predictive control with a Wiener model. It combines the adva...
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This paper discusses issues of model adaptation in a Wiener model based nonlinear predictive control (WNPC). WNPC is an extension of state-space generalized predictive control with a Wiener model. It combines the advantages of predictive control with the ability to control highly nonlinear processes, while retaining a moderate level of computational demand. It is aimed at a class of nonlinear processes that can be described with a Wiener structure. Model adaptation is required when the process is affected by nonmeasurable disturbances that severely affect the nonlinear characteristics of the system. It is shown that better disturbance rejection performance can be achieved at the cost of an increased computational demand, and that robust tuning of the estimator is a difficult problem. The method is evaluated with a pH neutralisation process case study.
The problem addressed in this paper is as follows. Consider a nonlinear discrete time system with parameters, which can be a priori classified into two groups: constant parameters and time varying ones. It is also ass...
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The problem addressed in this paper is as follows. Consider a nonlinear discrete time system with parameters, which can be a priori classified into two groups: constant parameters and time varying ones. It is also assumed that loose attributes like "slow" or "fast" express the only prior information concerning the dynamics of varying parameters. The question of interest is how to estimate the constant parameters of the process (on the basis of a recorded batch of input and output data) so that possible alterations of the parameters that are expected to vary with time are taken into account. To deal with this kind of nonlinear fixed-interval smoothing problem a two-level procedure based on rectangular window technique and Gauss-Newton method is presented. All the computations are performed offline. The procedure is applicable in a pre-processing stage of adaptive parameter estimation where the parameters that are evidently time invariant are identified from past records. Thus the number of parameters that have to be tracked (i.e. estimated) on-line is reduced. The efficiency of the scheme is illustrated on a simulated industrial process.
The main motivation of the presented work is to realise a prototype of the CAD tool that supports the whole life cycle of the diagnostic system development process. In the proposed approach, the fault trees are automa...
The main motivation of the presented work is to realise a prototype of the CAD tool that supports the whole life cycle of the diagnostic system development process. In the proposed approach, the fault trees are automatically derived from component models. The automatic synthesis incorporates the feedback control loop structure. Fault trees are then transformed into diagnostic rules. The implemented CAD tool allows for rule processing by using the Transferable Belief Model (TBM). The limitations of the component-based synthesis of fault trees are discussed.
We propose a multithreaded Java microcontroller (called Komodo microcontroller) with a new hardware event handling mechanism that allows handling of simultaneous overlapping events with hard real-time requirements. Re...
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We propose a multithreaded Java microcontroller (called Komodo microcontroller) with a new hardware event handling mechanism that allows handling of simultaneous overlapping events with hard real-time requirements. Real-time Java threads are used as interrupt service threads (ISTs) instead of interrupt service routines (ISRs). Our proposed Komodo microcontroller supports multiple ISTs with zero-cycle context switching overhead. We evaluate the basic architectural attributes using real-time event parameters of an autonomous guided vehicle. When calculating the maximum vehicle speed without violating the real-time constraints, ISTs dominate ISRs by a speed increase of 28%.
A toolbox for model-based fault detection and isolation (FDI) has been developed in the MATLAB/SIMULINK environment. It includes methods relying on analytical or qualitative models of the supervised process. A demonst...
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In this paper, three neural network based d-step-ahead prediction strategies, i.e. a recursive d-step-ahead neural predictor, a non-recursive d-step-ahead neural predictor, and a Smith type neural predictor are presen...
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In this paper, three neural network based d-step-ahead prediction strategies, i.e. a recursive d-step-ahead neural predictor, a non-recursive d-step-ahead neural predictor, and a Smith type neural predictor are presented for time-delay compensation for nonlinear systems. Both the recursive and the non-recursive predictors have been extended to the case of long-range prediction. Finally, the proposed neural network based predictors are applied to the prediction of the manifold pressure process in an automotive engine. The predictive result of the corresponding first principles model based nonlinear predictor is also illustrated for comparison. The experimental results show that the neural network based predictive methods have obtained better performance.
In this paper the robust fault detection and isolation (FDI) problem in linear systems, which are subjected to multiple faults and time varying system perturbations is discussed. The detection and isolation problem is...
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In this paper the robust fault detection and isolation (FDI) problem in linear systems, which are subjected to multiple faults and time varying system perturbations is discussed. The detection and isolation problem is treated by using algebraic methods and geometric design concepts. The idea of the classical Luenberger observer is generalized in an attempt that residual generators for solving the robust FDI problem can be designed.
In this paper a realization theory and associated algorithms are presented for the construction of minimal realizations on the basis of a sequence of expansion coefficients in a generalized orthonormal basis. Both the...
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In this paper a realization theory and associated algorithms are presented for the construction of minimal realizations on the basis of a sequence of expansion coefficients in a generalized orthonormal basis. Both the exact and the partial realization problem are addressed and solved, leading to extended versions of the classical Ho-Kalman *** the construction of the realization algorithms, fruitful use is made of a system analysis in the transform domain, being induced by the choice of basis functions. The resulting algorithms can also be applied in approximate realization and in system approximation.
A toolbox for model-based fault detection and isolation (FDI) has been developed in the MATLAB/SIMULINK environment. It includes methods relying on analytical or qualitative models of the supervised process. A demonst...
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A toolbox for model-based fault detection and isolation (FDI) has been developed in the MATLAB/SIMULINK environment. It includes methods relying on analytical or qualitative models of the supervised process. A demonstration of each approach can be performed on a simulation of either a three-tank system, a cocurrent or a countercurrent heat exchanger. The results are displayed in a common format, which allows performance comparison. A user manual including guidelines for tuning method specific parameters is available.
This paper presents a new real-time architecture for motion control of industrial robots. The new control system obtained has two main advantages: first it provides a total open control architecture and the second adv...
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This paper presents a new real-time architecture for motion control of industrial robots. The new control system obtained has two main advantages: first it provides a total open control architecture and the second advantage is the simplicity and the interactivity of the platform developed. Experimental evaluation of a passivity-based control scheme shows the benefits of the architecture which is unique in the sense that open and advanced control can be combined with built-in safety logic as required in industrial applications.
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