This paper describes the design of an adaptive autopilot for a containership. Well-known results of linear adaptive theory are extended through the use of neural network to the case where the plant dynamics are descri...
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This paper describes the design of an adaptive autopilot for a containership. Well-known results of linear adaptive theory are extended through the use of neural network to the case where the plant dynamics are described by a set of non-linear equations. The desired behaviour of the containership during course-changing manoeuvre is defined by the response of a referencemodel. Using an indirect approach, the controller parameters are adjusted based on the definition of an estimation error. The proposed adaptivecontroller is tested by a simulation study based on a non-linear model, describing the dynamics of a containership in four degrees of freedom. In order to take into account the wave effects, a stochastic model of the ship wave-induced motion is considered. Shallow water effect is also considered by changing some of the hydrodynamics parameters. Copyright (C) 2000 John Wiley & Sons, Ltd.
A new design method of discrete-time model reference adaptive control for nonminimum phase systems is presented, with disturbances using approximate inverse systems obtained from the long division method. It is assume...
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A new design method of discrete-time model reference adaptive control for nonminimum phase systems is presented, with disturbances using approximate inverse systems obtained from the long division method. It is assumed that the disturbances are described by a polynomial function of time with known degree and unknown coefficients. The proposed scheme uses only input and output data, and the existence of bounds for all signals is proved. This scheme also assures that plant output converges to the referencemodel output. The results of computer simulation are also presented to illustrate the effectiveness of the proposed method.
The aim of the work is to present the state-of-the-art in this filed of adaptivecontrol. Some development trends based especially on the general stability theory are analyzed. The characteristics of basic model refer...
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The aim of the work is to present the state-of-the-art in this filed of adaptivecontrol. Some development trends based especially on the general stability theory are analyzed. The characteristics of basic model reference adaptive control (MRAC) structures and algorithms are given in order to provide an insight into the development of the theory and to indicate the possibilities of their practical application. As the paper makes only a survey of the subject area, the stability proofs of the presented algorithms are omitted. The plant to be controlled is assumed to be described by a linear model.
model reference adaptive control (MRAC) has been developed in many modifications. The stability proofs have been given under the assumption that the plant model is linear. However, MRAC approaches give often convergen...
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model reference adaptive control (MRAC) has been developed in many modifications. The stability proofs have been given under the assumption that the plant model is linear. However, MRAC approaches give often convergent solutions even for nonlinear systems. The aim of this paper is to show that for nonlinear systems with the model in canonical form, the standard MRAC with state feedback structure can be used to obtain the perfect model matching. The stability proof is derived using the general Laypunov stability theory. At the end of paper, an example of adaptivecontrol of third order nonlinear system is presented, where a considerable improvement of control system dynamical behavior has been obtained.
A Direct model reference adaptive control (DMRAC) approach is developed for large-scale precision aerospace structures with persistent disturbances. Stability is proved via Lyapunov-Barbalat theory. The DMRAC produces...
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A new control method that is a model reference adaptive control method (MRAC) based on the combination of PID control and the Genetic Algorithm (GA) is introduced. It implements the characteristic of the Genetic Algor...
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ISBN:
(纸本)0780341236
A new control method that is a model reference adaptive control method (MRAC) based on the combination of PID control and the Genetic Algorithm (GA) is introduced. It implements the characteristic of the Genetic Algorithm's global optimization to optimize the PID's three control parameters: Kp, Ki, Kd, to obtain the best control effect. This paper gives an example using this method to control a nonlinear system - Continuous Stirred Tank Reactor system (CSTR). Because the state of the CSTR system con not be gotten, a neural network is used to estimate the value of the state. This neural network is training by the GA. The simulation results are given.
This paper presents a new analysis method for model reference adaptive control(MRAC) with arbitrary bounded input nonlinearities. The reduced-order plant is assumed to be of an arbitrary relative degree. In the absenc...
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ISBN:
(纸本)9783952426906
This paper presents a new analysis method for model reference adaptive control(MRAC) with arbitrary bounded input nonlinearities. The reduced-order plant is assumed to be of an arbitrary relative degree. In the absence of unmodeled dynamics and bounded disturbances, the tracking error depends on input nonlinearities. A new modified MRAC scheme is also proposed to improve the transient and steady state performances. The output error is used directly in the contro law to generate a modified control signal to compensate possible bad performances of the robust adaptivecontrollers, and the ideal asymptotic properties of MRAC is not destroyed.
In the conventional mine winder control systems, S-curve control and PI control are mainly utilized. Since the control parameters of these control methods are constant, they can not adapt sufficiently to the large cha...
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In the conventional mine winder control systems, S-curve control and PI control are mainly utilized. Since the control parameters of these control methods are constant, they can not adapt sufficiently to the large change of the wire rope length. In this work, we propose a new robust winder control system using the adaptivemodel output following control based on Backstepping strategy. It is shown that the effectiveness and robustness of the proposed control method are confirmed through experiments using an experimental winder model with a maximum length of 15 meters of wire rope.
The discrete-time version of continuous-time combined model reference adaptive control (CMRAC) is presented in this paper. A global stability proof of the overall adaptive scheme is given using arguments similar to th...
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The discrete-time version of continuous-time combined model reference adaptive control (CMRAC) is presented in this paper. A global stability proof of the overall adaptive scheme is given using arguments similar to those used in discrete-time direct model reference adaptive control (DMRAC) but properly modified to account for the different structure of CMRAC with respect to DMRAC. (C) 1997 by John Wiley & Sons, Ltd.
A novel neural network speed identification scheme for the speed sensorless direct torque control (DTC) of an induction motor drive system is presented in the paper. The system uses current and voltage sensors for rot...
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ISBN:
(纸本)780003464X
A novel neural network speed identification scheme for the speed sensorless direct torque control (DTC) of an induction motor drive system is presented in the paper. The system uses current and voltage sensors for rotor speed and rotor flux estimation with a digital signal processor (DSP) TMS320F240 in a closed loop control system. Rotor speed identification is based on the model reference adaptive control (MRAC) theory with a neural network using the backpropagation (BP) algorithm. The suggested speed identification method has been validated by a simulation study.
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