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Nonlinear Plant (nonlinear + plant)
Selected AbstractsSupport vector machines-based generalized predictive controlINTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL, Issue 17 2006S. Iplikci Abstract In this study, we propose a novel control methodology that introduces the use of support vector machines (SVMs) in the generalized predictive control (GPC) scheme. The SVM regression algorithms have extensively been used for modelling nonlinear systems due to their assurance of global solution, which is achieved by transforming the regression problem into a convex optimization problem in dual space, and also their higher generalization potential. These key features of the SVM structures lead us to the idea of employing a SVM model of an unknown plant within the GPC context. In particular, the SVM model can be employed to obtain gradient information and also it can predict future trajectory of the plant output, which are needed in the cost function minimization block. Simulations have confirmed that proposed SVM-based GPC scheme can provide a noticeably high control performance, in other words, an unknown nonlinear plant controlled by SVM-based GPC can accurately track the reference inputs with different shapes. Moreover, the proposed SVM-based GPC scheme maintains its control performance under noisy conditions. Copyright © 2006 John Wiley & Sons, Ltd. [source] Some results in nonlinear QFTINTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL, Issue 2 2001A. Baños Abstract Nonlinear QFT (quantitative feedback theory) is a technique for solving the problem of robust control of an uncertain nonlinear plant by replacing the uncertain nonlinear plant with an ,equivalent' family of linear plants. The problem is then finding a linear QFT controller for this family of linear plants. While this approach is clearly limited, it follows in a long tradition of linearization approaches to nonlinear control (describing functions, extended linearization, etc.) which have been found to be quite effective in a wide range of applications. In recent work, the authors have developed an alternative function space method for the derivation and validation of nonlinear QFT that has clarified and simplified several important features of this approach. In particular, single validation conditions are identified for evaluating the linear equivalent family, and as a result, the nonlinear QFT problem is reduced to a linear equivalent problem decoupled from the linear QFT formalism. In this paper, we review this earlier work and use it in the development of (1) new results on the existence of nonlinear QFT solutions to robust control problems, and (2) new techniques for the circumvention of problems encountered in the application of this approach. Copyright © 2001 John Wiley & Sons, Ltd. [source] Minimizing operating points for way point tracking of an unstable nonlinear plantASIAN JOURNAL OF CONTROL, Issue 1 2010Guangyu Liu Abstract Stability analysis of way point tracking of an open loop unstable nonlinear system is overwhelmingly ignored in the literature. Taking a spherical inverted pendulum as an example, the stability issue of way point tracking for an unstable nonlinear system is properly addressed and solved by incorporating nonlinear stabilizing controllers that could minimize the number of operating points. The underlying principle in stability analysis of way point tracking easily extends to other unstable nonlinear systems. Effectiveness of the proposed idea is evaluated in computer simulation. Copyright © 2009 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society [source] Real-Time Control and Identification of a Thermal Process Based on Multiple-Modeling ApproachASIA-PACIFIC JOURNAL OF CHEMICAL ENGINEERING, Issue 3-4 2005A. Aminzadeh This article presents implementation of Real-Time Control and Identification algorithms based on a Multiple-Modeling approach for an experimental thermal process. The thermal process is a nonlinear plant; therefore, based on variations of the input and disturbance, four local operating regimes are defined. The linear local ARMAX models are identified for different regimes and integrated into a NARMAX model by combining them via proper validity and interpolation functions. Results of modeling the plant with a single model and multiple models show superior performance of the Multiple-Modeling technique which is also more flexible. Moreover, the Real-Time Control of the plant with four locally designed controllers is addressed. The platform used for the Real-Time implementation is Matlab/Simulink/Real-Time-Workshop with Visual C++ and Watcom compilers using a DAQ interface. The Real-Time application of the global controller based on the Multiple-Model approach demonstrates excellent performance for this design when compared to a single PID controller. [source] A levenberg,marquardt learning applied for recurrent neural identification and control of a wastewater treatment bioprocessINTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS, Issue 11 2009Ieroham S. Baruch The paper proposed a new recurrent neural network (RNN) model for systems identification and states estimation of nonlinear plants. The proposed RNN identifier is implemented in direct and indirect adaptive control schemes, incorporating a noise rejecting plant output filter and recurrent neural or linear-sliding mode controllers. For sake of comparison, the RNN model is learned both by the backpropagation and by the recursive Levenberg,Marquardt (L,M) learning algorithm. The estimated states and parameters of the RNN model are used for direct and indirect adaptive trajectory tracking control. The proposed direct and indirect schemes are applied for real-time control of wastewater treatment bioprocess, where a good, convergence, noise filtering, and low mean squared error of reference tracking is achieved for both learning algorithms, with priority of the L,M one. © 2009 Wiley Periodicals, Inc. [source] Tracking for nonlinear plants with multiple unknown time-varying state delays using sliding mode with adaptationINTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL, Issue 13 2010Boris Mirkin Abstract In this paper, we develop a sliding mode model reference adaptive control (MRAC) scheme for a class of nonlinear dynamic systems with multiple time-varying state delays, which is robust with respect to unknown plant delays, to a nonlinear perturbation, and to an external disturbance with unknown bounds. An appropriate Lyapunov,Krasovskii-type functional is introduced to design the adaptation algorithms, and to prove stability. Copyright © 2009 John Wiley & Sons, Ltd. [source] Controller design based on similar skew-symmetric structure for nonlinear plantsASIAN JOURNAL OF CONTROL, Issue 1 2010Yicheng Liu Abstract This paper proposes a novel controller design approach for nonlinear plants. A class of stable nonlinear systems with a similar skew-symmetric structure is chosen as the objective closed loop system, and two design methods are proposed with backstepping and direct construction. Compared with the conventional backstepping method, the proposed backstepping method need not construct a Lyapunov function step by step, thus the design procedure is simplified. The direct construction method can be applied to some nonlinear plants for which the conventional backstepping is not feasible; and the design can be accomplished in only one step. Furthermore, for some nonlinear plants which have a lower triangular structure with two subsystems, simpler controllers can be derived by the proposed direct construction method than those derived by backstepping design. In addition, the proposed methods are both system structure oriented, therefore their designs are more intuitive than the conventional backstepping design. Two controllers are derived for satellite attitude control by employing the proposed methods; simulation results demonstrate their effectiveness. Copyright © 2009 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society [source] | ||||||||||