In this paper a hierarchical structure of several artificial neural networks has been developed for fault isolation purposes. Two different approaches have been considered. The hierarchical structure is the same for b...
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Fault diagnosis systems have an important role in industrial plants because the early fault detection and isolation (FDI) can minimize damages in the plants. The main aim of this work is to propose a two-stage neuro-f...
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Fault diagnosis systems have an important role in industrial plants because the early fault detection and isolation (FDI) can minimize damages in the plants. The main aim of this work is to propose a two-stage neuro-fuzzy approach as a fault diagnosis system in dynamic processes. The first stage of the system is responsible for fault detection and is implemented using a neuro-fuzzy (N-F) model. The second stage of the system is responsible for fault isolation and is built using an hierarchical structure of fuzzy neural networks. The FDI system is applied to fault diagnosis in the actuators of one sugar factory.
In this paper a hierarchical structure of several artificial neural networks has been developed for fault isolation purposes. Two different approaches have been considered. The hierarchical structure is the same for b...
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In this paper a hierarchical structure of several artificial neural networks has been developed for fault isolation purposes. Two different approaches have been considered. The hierarchical structure is the same for both approaches, but one uses multi-layer feedforward artificial neural networks and the other uses fuzzy neural networks. A result comparison between the two architectures will be presented. It is aimed to isolate multiple simultaneous abrupt and incipient faults from only single abrupt fault symptoms. A continuous binary distillation column has been used as test bed of the current approaches.
Repetitive processes are a distinct class of 2D systems of both theoretical and applications interest. They are characterized by a series of sweeps through a set of dynamics with explicit interaction between the outpu...
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Repetitive processes are a distinct class of 2D systems of both theoretical and applications interest. They are characterized by a series of sweeps through a set of dynamics with explicit interaction between the outputs, or pass profiles, produced on successive passes. Their essential unique features are that (i) information propagation is over a finite duration in one of the two separate directions of information propagation; and (ii) the explicit interaction between successive pass profiles can lead to oscillations in the sequence of pass profiles that increase in amplitude in the pass to pass direction. In the case of processes with linear dynamics (either differential or discrete) a reasonably rich systems theory is available for models which are standard (or nonsingular). In this paper, we provide the first substantial results on discrete linear repetitive processes described by a singular state space model.
A new methodology is proposed for the design of path following systems for autonomous marine craft in the presence of constant but unknown currents. Convergence to reference paths is achieved with a nonlinear control ...
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A new methodology is proposed for the design of path following systems for autonomous marine craft in the presence of constant but unknown currents. Convergence to reference paths is achieved with a nonlinear control strategy that takes explicitly into account the dynamics of the vehicle as well as those of a current estimator. Formal convergence proofs are indicated. Simulation results with the model of a prototype marine craft are presented to illustrate the performance of the path following system derived.
A new methodology is proposed for the design of path following systems for autonomous marine vehicles in the presence of constant but unknown currents. Convergence to reference paths is achieved with a nonlinear contr...
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A new methodology is proposed for the design of path following systems for autonomous marine vehicles in the presence of constant but unknown currents. Convergence to reference paths is achieved with a nonlinear control strategy that takes explicitly into account the dynamics of the vehicle as well as those of a current estimator. Formal convergence proofs are indicated. Simulation results with the model of a prototype marine craft are presented to illustrate the performance of the path following system derived.
Interlaced systems constitute a class of systems only characterized by the zero entries of their matrix configuration and a local stabilizability condition. All these systems are globally stabilizable by a recursive d...
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ISBN:
(纸本)9783952426906
Interlaced systems constitute a class of systems only characterized by the zero entries of their matrix configuration and a local stabilizability condition. All these systems are globally stabilizable by a recursive design procedure which combines steps of backstepping and forwarding. When a nonlinear system misses this structural characterization, other types of conditions (sign, growth) are needed to ensure global stabilization.
We develop tools for backstepping with Lyapunov functions and control laws which are locally Lipschitz but not differentiable. We use Clarke’s generalized gradient and its associated calculus to show that the locally...
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We develop tools for backstepping with Lyapunov functions and control laws which are locally Lipschitz but not differentiable. We use Clarke’s generalized gradient and its associated calculus to show that the locally Lipschitz backstepping construction is essentially the same as the differentiable one. Our recursive method is constructive and yields an explicit expression for the control law.
For nonlinear systems in extended strict feedback form, where unmeasured states enter linearly, we construct dynamic partial state feedback controllers that achieve the global asymptotic tracking of given reference tr...
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For nonlinear systems in extended strict feedback form, where unmeasured states enter linearly, we construct dynamic partial state feedback controllers that achieve the global asymptotic tracking of given reference trajectories while maintaining internal boundedness.
We consider nonlinear control systems for which an estimate x/spl circ/ of the system state x is available for feedback. We assume x/spl circ/=x+d/sub m/, where d/sub m/(t) is an unknown locally bounded state measurem...
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We consider nonlinear control systems for which an estimate x/spl circ/ of the system state x is available for feedback. We assume x/spl circ/=x+d/sub m/, where d/sub m/(t) is an unknown locally bounded state measurement disturbance. We present conditions under which we can design a smooth feedback law u=/spl mu/(x/spl circ/) which renders the mapping from d/sub m/ to x globally input/output stable. For any initial condition, such a feedback law will guarantee that no finite escape times occur, that bounded disturbances d/sub m/ produce bounded signals, and that x/spl rarr/0 when d/sub m//spl rarr/0. We show that the class of systems for which such feedback laws exist include systems in strict feedback form. One important application is in the output feedback stabilization problem, where the disturbance d/sub m/ comes from a separately designed observer.< >
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