• Journal of Power Electronics
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• v.18 no.5
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• pp.1380-1397
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• 2018

The synchronous reluctance motor (SynRM) servo-drive system has highly nonlinear uncertainties owing to a convex construction effect. It is difficult for the linear control method to achieve good performance for the SynRM drive system. The nonlinear backstepping control system using upper bound with switching function is proposed to inhibit uncertainty action for controlling the SynRM drive system. However, this method uses a large upper bound with a switching function, which results in a large chattering. In order to reduce this chattering, a nonlinear backstepping control system using an adaptive law is proposed to estimate the lumped uncertainty. Since this method uses an adaptive law, it cannot achiever satisfactory performance. Therefore, a nonlinear backstepping control system using a reformed recurrent Hermite polynomial neural network with an adaptive law and an error estimated law is proposed to estimate the lumped uncertainty and to compensate the estimated error in order to enhance the robustness of the SynRM drive system. Further, the reformed recurrent Hermite polynomial neural network with two learning rates is derived according to an increment type Lyapunov function to speed-up the parameter convergence. Finally, some experimental results and a comparative analysis are presented to verify that the proposed control system has better control performance for controlling SynRM drive systems.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.5
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• pp.482-489
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• 2015

CSTR (Continuous Stirred Tank Reactor) which plays a key role in the chemical plants exhibits highly nonlinear behavior as well as time-varying behavior during operation. The control of CSTRs in the whole operating range has been a challenging problem to control engineers. So, a variety of feedback control forms and their tuning methods have been implemented to guarantee the satisfactory performance. This paper presents a scheme of designing a nonlinear PID controller incorporating with a GA (Genetic Algorithm) for the temperature control of a CSTR. The gains of the NPID controller are composed of easily implementable nonlinear functions based on the error and/or the error rate and its parameters are tuned using a GA by minimizing the ITAE (Integral of Absolute Error). Simulation works for reference tracking and disturbance rejecting performances and robustness to parameter changes show the feasibility of the proposed method.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.1
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• pp.1-8
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• 2005

A new discretization algorithm for nonlinear systems with delayed input is proposed. The algorithm is represented by Taylor series expansion and ZOH assumption. This method is applied to the sampled-data representation of a nonlinear system with the time-delay input. Additionally, the delay in input is time varying and its amplitude is bounded. The maximum time-delay in input is assumed to be two sampling periods. The mathematical expressions of the discretization method are presented and the ability of the algorithm is tested for some of the examples. The computer simulation proves the proposed algorithm discretizes the nonlinear system with the variable time-delay input accurately.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.4
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• pp.207-211
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• 2004

We consider a class of uncertain nonlinear systems containing the uncertainties without a priori information except that they are bounded. For such systems, we assume that the upper bound of the uncertainties is represented as a Fredholm integral equation of the first kind and we propose an adaptation law that is capable of estimating the upper bound. Using this adaptive upper bound, a continuous robust control which renders uncertain nonlinear systems uniformly ultimately bounded is designed.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.836-841
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• 1993

For a class of discrete-time nonlinear systems, an iterative learning control method is proposed and a sufficient condition is derived for the convergence of the output error. The proposed method is shown to be less sensitive to modelling errors and the uniform boundedness of the output error is guaranteed even in the presence of initial state errors. It is illustrated by simulations that the actual output converges to a desired output within the tolerance bound and convergence performance is improved by the presented method.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.40.4-40
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• 2001

This paper addresses the problem of designing robust adaptive output tracking control for a class of MIMO nonlinear systems which have different number of inputs and outputs The stability of the whole closed-loop system is guaranteed in the sense of Lyapunov and uniformly Itimately boundedness of the tracking error vector as well as estimated parameters are shown. In addition, we show that the restrictive assumptions on input gain matrix which is presumed in the past works can be eliminated by using proposed control law.

• International Journal of Precision Engineering and Manufacturing
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• v.2 no.4
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• pp.61-68
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• 2001

A new approach for motion control of constrained mechanical systems is proposed in this paper. The approach uses a new equations of motion which is proposed by Udwadia and Kalaba and named Udwadia-Kalaba's equations of motion in this paper. This paper reveals that the Udwadia-Kalaba's equations of motion is more adequate to model constrained mechanical systems rather than the famous Lagrange's equations of motion at least for control purpose. The proposed approach coverts most of constraints including holonomic and nonholonomic constraints. Comparison of simulation results of two systems which are well-known in the literature show the superiority of the proposed approach. Furthermore, a special constrained mechanical system which includes nonlinear generalized velocities in its constraint equations, which has been considered to be difficult to control, can be controlled easily. It shows the possibility of the proposed approach to being a general framework for motion control of constrained mechanical systems with various kinds of constraints.

• Journal of Power System Engineering
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• v.2 no.2
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• pp.55-59
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• 1998

In practice, the property of nonlinearity is contained in all physical systems. In other word, all physical systems are nonlinear to some degree. Therefore it is important that we acquires a facility for analyzing feedback control systems with varying degrees of nonlinearity. To operate the system linearly over wide range of variation of signal amplitude and frequency, the system requires components of an extremely high quality. Such a system would probably be impractical in the view points of cost, space and weight. In this context of view, it is worth noting that the nonlinearities may be intentionally introduced into a system in order to compensate for the effects of other undesirable nonlinearities or to obtain better performance than what could be achieved using linear element only. A simple example of an intentional nonlinearity is the use of a nonlinear damped system to optimize response in accordance with the magnitude of error. In this paper, an on-off type nonlinear controller is introduced and the applicability and validity of a simple on-off controller are presented by the experimental result.

• International Journal of Control, Automation, and Systems
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• v.3 no.spc2
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• pp.278-287
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• 2005

In this paper a new excitation control scheme that improves the transient stability of multi machine power systems is proposed. To this end the backstepping technique is used to transform the system to a suitable partially linear form. On this system, a combination of both feedback linearization and adaptive control techniques are used to confront the nonlinearities. As shown in the paper, the resulting nonlinear control law ensures the uniform boundedness of all the state and estimated variables. Furthermore, it is proven that all the error variables are uniformly ultimately bounded (DUB) i.e. they converge to arbitrarily selected small regions around zero in finite-time. Simulation tests on a two generator infinite bus power system demonstrate the effectiveness of the proposed control.

• Structural Engineering and Mechanics
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• v.38 no.1
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• pp.39-63
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• 2011

Referring to the formulation of physical stochastic optimal control of structures and the scheme of optimal polynomial control, a nonlinear stochastic optimal control strategy is developed for a class of structural systems with hysteretic behaviors in the present paper. This control strategy provides an amenable approach to the classical stochastic optimal control strategies, bypasses the dilemma involved in It$\hat{o}$-type stochastic differential equations and is applicable to the dynamical systems driven by practical non-stationary and non-white random excitations, such as earthquake ground motions, strong winds and sea waves. The newly developed generalized optimal control policy is integrated in the nonlinear stochastic optimal control scheme so as to logically distribute the controllers and design their parameters associated with control gains. For illustrative purposes, the stochastic optimal controls of two base-excited multi-degree-of-freedom structural systems with hysteretic behavior in Clough bilinear model and Bouc-Wen differential model, respectively, are investigated. Numerical results reveal that a linear control with the 1st-order controller suffices even for the hysteretic structural systems when a control criterion in exceedance probability performance function for designing the weighting matrices is employed. This is practically meaningful due to the nonlinear controllers which may be associated with dynamical instabilities being saved. It is also noted that using the generalized optimal control policy, the maximum control effectiveness with the few number of control devices can be achieved, allowing for a desirable structural performance. It is remarked, meanwhile, that the response process and energy-dissipation behavior of the hysteretic structures are controlled to a certain extent.