This paper investigates a control strategy which uses an identified reference model to produce appropriate chaotic and nonchaotic reference trajectories. Although it is possible to dispense with the reference model in...
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This paper investigates a control strategy which uses an identified reference model to produce appropriate chaotic and nonchaotic reference trajectories. Although it is possible to dispense with the reference model in many applications, it is often desirable to obtain a model of the system in order to guarantee that the reference signal is a genuine trajectory of the system to be controlled and to reduce the effects of transients and the control effort. The influence of measurement noise and the relation between the control effort and the dynamics of the uncontrolled system are also discussed. Examples which use the Duffing-Ueda system and a discrete reference model identified from input/output records with no a priori information, are included to illustrate the main points of the paper.
This paper presents an investigation into the performance evaluation issues involved in real-time parallel signal processing and control. Issues such as algorithm partitioning, mapping, interprocessor communication, g...
This paper presents an investigation into the performance evaluation issues involved in real-time parallel signal processing and control. Issues such as algorithm partitioning, mapping, interprocessor communication, granularity, regularity, compiler efficiency for numerical computation, and code optimization with several signal processing and control algorithms are investigated and presented. Several algorithms are considered and implemented on a number of uniprocessor and multiprocessor, homogeneous and heterogeneous, parallel architectures, A comparative performance evaluation of the architectures is made, demonstrating the critical problems encountered in real-time parallel signal processing and control. (C) 1997 Academic Press.
In designing controllers for complex dynamical systems there are needs that are not sufficiently addressed by conventional control theory. These relate mainly to the problem of environmental uncertainty and often call...
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In designing controllers for complex dynamical systems there are needs that are not sufficiently addressed by conventional control theory. These relate mainly to the problem of environmental uncertainty and often call for human-like decision making requiring the use of heuristic reasoning and learning experience. Learning is required complexity of a problem or the uncertainty thereof prevents a priori specification of a satisfactory solution. Such solutious are then only possible through accumulating information about the problem and using this information to dynamically generate an acceptable solution. Such systems can be referred to as intelligent controlsystems. In recent years, 'intelligent control' has come to embrace diverse methodologies combining conventional control theory and emergent techniques based on physiological metaphors, such as neural networks, fuzzy logic, artificial intelligence, genetic algorithms and a wide variety of search and optimisation techniques. The paper reviews aspects of these emergent techniques, in particular, fuzzy logic, neural networks and genetic algorithms that pertain to realisation of intelligent controlsystems. The fundamental concepts and design techniques of each paradigm are discussed, providing a compact reference for their application.
Antipsychotics and antidepressants are essential psychotropic medications used for treating various mental health conditions such as depression, schizophrenia, and bipolar disorder. However, when exposed to light, the...
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LiDAR-camera extrinsic calibration (LCEC) is the core for data fusion in computer vision. Existing methods typically rely on customized calibration targets or fixed scene types, lacking the flexibility to handle varia...
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In Part 1 of this paper the concept of a bound for the output frequency response magnitude characteristics of nonlinear systems was proposed, and general calculation and analysis procedures were developed. In this, Pa...
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In Part 1 of this paper the concept of a bound for the output frequency response magnitude characteristics of nonlinear systems was proposed, and general calculation and analysis procedures were developed. In this, Part 2 of the paper, a new recursive algorithm for the computation of the gain bounds for the generalized frequency response functions of the polynomial nonlinear autoregressive model with exogenous input is proposed, and effective procedures for the practical computation of the new bound are developed. Simulated examples are included to verify the effectiveness of the proposed procedures.
The author looks at the history of automaticcontrol in four main periods as follows: early control up to 1900; the pre-classical period 1900-1940; the classical period 1935-1960; and modem control post 1955. This art...
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The author looks at the history of automaticcontrol in four main periods as follows: early control up to 1900; the pre-classical period 1900-1940; the classical period 1935-1960; and modem control post 1955. This article is concerned with the first three of the above; other articles in this issue deal with the more recent period.
A generic supervisory systems architecture is presented for control of two different types of systems;medical systems and industrial systems. It is structured in a hierarchical manner, consisting of a basic-level fuzz...
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A generic supervisory systems architecture is presented for control of two different types of systems;medical systems and industrial systems. It is structured in a hierarchical manner, consisting of a basic-level fuzzy logic controller supervised by a higher level decision-maker, which employs fuzzy logic theory to represent the human expertise used in supervising the plant including both the controller and the process. The supervisory level tasks consist of tuning, generating control rules, fault detection and diagnosis, together with an alarm and monitoring system. The paper is concerned more with the fault detection and diagnosis methods incorporated in the system. Simulation results for a medical system application are presented.
An improved method for on-line identification of a first order plus dead-time process model under proportional-integral control is proposed. The proposed method eliminates some of the disadvantages of the Yuwana and S...
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An improved method for on-line identification of a first order plus dead-time process model under proportional-integral control is proposed. The proposed method eliminates some of the disadvantages of the Yuwana and Seborg method while retaining the simplicity of the method. Simulation results show that the proposed method performs well on a range of processes.
A symbolic manipulation procedure, which both computes and automatically decomposes the generalized frequency response functions of nonlinear rational, polynomial and integrodifferential equation models into a set of ...
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A symbolic manipulation procedure, which both computes and automatically decomposes the generalized frequency response functions of nonlinear rational, polynomial and integrodifferential equation models into a set of closed-form nth order transfer functions, is presented. The symbolic representation exposes the explicit relationship between the model parameters and the nonlinear transfer functions in the frequency domain and leads to important insights into the characterization of nonlinear systems. Examples for each model type are included to demonstrate the symbolic transfer function approach.
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