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The present paper is devoted to a study of constrained controllability and controllability for linear dynamic systems if the controls are taken to be non-negative. By analogy to the usual definition of controllability it is possible to introduce the concept of positive controllability. Weshall concentrate on approximate positive controllability for linear infinite-dimensional dynamic systems when...
In this paper, we consider the design of tracking controllers for linear MIMO systems described by an input-output model. The presence of known 'weak' interactions among SISO or MIMO subsystems may allow the designer to achieve objectives by using independent controllers of lower complexity than are necessary in general (control decentralization problem). Sufficient conditions for asymptotic tracking...
An on-line fault diagnosis system, designed to be robust to the normal transient behaviour of the process, is described. The overall system consists of an expert system cascade with a hierarchical structure of fuzzy neural networks, corresponding to a multi-stage fault detection and isolation system. The fault detection is performed through the expert system by means of fault detection heuristic rules,...
A multi-objective Pareto-optimisation procedure for the design of residual generators which constitute a primary instrument for model-based fault detection and isolation (FDI) in systems of plant monitoring and control is considered. An evolutionary approach to the underlying multi-objective optimisation problem is utilised. The resulting robust observer detector allows for FDI, taking into account...
The paper presents an idea of decomposition of diagnostic tasks in complex systems. Such decomposition consists in splitting basic diagnostic functions into lower-level units existing in decentralised structures of automatic control and supervision of the process. An example of a unit that realises this concept and includes a positioner that controls and diagnoses an assembly consisting of a servomotor...
Application of fuzzy logic in fault isolation is proposed. The introduced methods assume the industrial requirements such as integration of different detection algorithms, system complexity, data and knowledge uncertainties. Algorithms of decreasing the calculation expenditures for diagnosing large-scale systems are also introduced. An example of the application is also shown. The proposed technique...
Fault detection and isolation in Wiener and Hammerstein systems via generation and processing of residual sequences is considered. We assume that some models of the unfaulty Wiener and Hammerstein systems under consideration are known. For Wiener systems, we also assume that their static nonlinear subsystems are invertible. Then, based on a serial-parallel definition of the residual error, new fault...
This paper deals with the family of CMAC neural networks. The most important properties of this family are the extremely fast learning capability and a special architecture that makes effective digital hardware implementation possible. The paper gives an overview of the classical binary CMAC, shows the limitations of its modelling capability, gives a critical survey of its different extensions and...
Model-based fault detection becomes rather questionable if a supervised plant belongs to the class of systems with distributed parameters and significant delays. Two methods of fault detection have been developed for this class of plants, namely a method of functional (anisochronic) state observer and a modified internal model control scheme adopted for that purpose. Both these model schemes are employed...
The paper suggests a neural-network approach to the design of robust fault diagnosis systems. The main emphasis is placed upon the development of neural observer schemes. They are built based on dynamic neural networks, i.e. dynamic multi-layer perceptrons with mixed structure. The goal is to achieve an adequate approximation of process outputs for known classes of the process behaviour. The obtained...
Recent approaches to fault detection and isolation (FDI) for dynamic systems using methods of integrating quantitative and qualitative model information, based upon artificial intelligence (AI) techniques are surveyed. In this study, the use of AI methods is considered an important extension to the quantitative model-based approach for residual generation in FDI. When quantitative models are not readily...
This paper describes an application of sensitivity theory to the analysis of a certain class of fuzzy systems which can be used for fault detection and isolation (FDI). The work is divided into three main tasks. The first is the mathematical representation of some class of fuzzy systems. This is followed by an application of sensitivity theory to fuzzy systems based on the approach detailed in the...
A fault diagnosis scheme for unknown nonlinear dynamic systems with modules of residual generation and residual evaluation is considered. Main emphasis is placed upon designing a bank of neural networks with dynamic neurons that model a system diagnosed at normal and faulty operating points.To improve the quality of neural modelling, two optimization problems are included in the construction of such...
A public-key cryptosystem, using generalized quasigroup-based streamciphers is presented. It is shown that such a cryptosystem allows one to transmit securely both a cryptogram and a secret portion of the enciphering key using the same insecure channel. The system is illustrated by means of a simple, but non-trivial, example.
Design and stability analysis of fuzzy multi-regional digital controllers is considered in the paper. The controllers are based on a notion of NARMAX systems, very similar to the Takagi-Sugeno fuzzy model. The nonlinear system is approximated by a number of linear subsystems. Linear controllers are designed for all subsystems. It can be made in a classical way due to the subsystems linearity. The...
Complex diagnosis problems, defined by high-level models, often lead to constraint-based discrete optimization tasks. A logical description of large, complex systems usually contains numerous variables. The first test of the logical description is typically to check the feasibility in order to know that there is no contradiction in the model. This can be formulated as an optimization problem and methods...
A comparison is made between problem-oriented databases for multistage decision making and general-purpose databases. An exemplary problem-oriented database IDEN for supporting the process of multistage identification is discussed in detail. An equivalence condition for problem-oriented databases is formulated and then the equivalence with respect to data structures and operations is proved for hierarchical,...
This paper deals with a numerical method for data fitting and estimation of continuous higher-order derivatives of a given signal from its non-exactsampled data. The proposed algorithm is a generalization of the algorithm proposed by Reinsch (1967). This algorithm is conceived as a key element in the structure of the numerical observer discussed in our recent papers. Satisfactory results are obtained...
In this paper, a constructive approach to the fuzzy model selection problem is developed. First, the selection of membership functions is decoupled from parameter calculations using an orthogonalization procedure. Since each membership function depends only on its own parameters, the selection of rules is performed in a sequential manner. At each learning step, a new membership function is created...
This note is devoted to the problem of global stabilization of continuous systems by adding an integrator. The goal is to prove that if a continuous non-linear system dot x =f(x,u) is globally asymptotically stable at the origin for u equiv 0, then the augmented system obtained by adding an integrator is stabilizable by means of a continuous feedback.
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