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Retrospective cost adaptive control for nonminimum-phase systems with uncertain nonminimum-phase zeros using convex optimization
2011
Proceedings of the 2011 American Control Conference
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Specifically, a convex constraint is imposed on the poles of the controller in order to prevent the adaptive controller from attempting to cancel the nonminimum-phase zeros. ...
Retrospective cost adaptive control (RCAC) can be applied to command following and disturbance rejection problems with plants that are possibly MIMO, unstable, and nonminimum phase. ...
As shown in [2] , [4] , RCAC has the ability to adaptively control nonminimum-phase systems if the locations of the nonminimum-phase zeros are known. ...
doi:10.1109/acc.2011.5990991
fatcat:wv5oxo4uqjaarjnrarzj43sqne
Closed Loop Direct Adaptive Inverse Control for Linear Plants
2014
The Scientific World Journal
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CDAIC and DAIC are compared using computer simulations for disturbance free and disturbed discrete type nonminimum phase linear plants. ...
CDAIC is applicable to stable or stabilized, minimum or nonminimum phase linear plants. ...
Adam Khan and Ghulam Ishaq Khan Institute of Engineering Sciences and Technology for their help and support. ...
doi:10.1155/2014/658497
pmid:24574907
pmcid:PMC3916100
fatcat:k7qyw5cfijf4vdg265v5jjgyui
Adaptive control using retrospective cost optimization with RLS-based estimation for concurrent Markov-parameter updating
2009
Proceedings of the 48h IEEE Conference on Decision and Control (CDC) held jointly with 2009 28th Chinese Control Conference
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We present a discrete-time adaptive control law that is effective for systems that are MIMO and either minimum phase or nonminimum phase. ...
The adaptive control algorithm provides guidelines concerning the modeling information needed for implementation. ...
These results are noteworthy since nonminimum-phase zeros are known to be challenging for adaptive control algorithms [13] . ...
doi:10.1109/cdc.2009.5400822
dblp:conf/cdc/SantilloHHB09
fatcat:mqewfniy2bdyhao5gg5kwvv544
Adaptive static-output-feedback stabilization using retrospective cost optimization
2010
Proceedings of the 2010 American Control Conference
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We present a discrete-time, adaptive, staticoutput-feedback control law that is effective for systems that are unstable, MIMO, and/or nonminimum phase. ...
In particular, we present numerical examples to provide guidelines concerning the modeling information required for controller implementation. ...
The goal of this paper is to present a discrete-time, adaptive, MIMO, static-output-feedback controller that is effective for systems that are unstable, nonsquare, and/or nonminimum-phase. ...
doi:10.1109/acc.2010.5531519
fatcat:qhp2mlq3azgftmjjiasjd5h6r4
A retrospective correction filter for discrete-time adaptive control of nonmiminum-phase systems
2008
2008 47th IEEE Conference on Decision and Control
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We present a discrete-time adaptive control law that is effective for systems that are unstable, MIMO, and/or nonminimum phase. ...
The adaptive control algorithm provides guidelines concerning the modeling information needed for implementation. ...
Accordingly, we present an adaptive control law based on [3] and [21] for systems that are unstable, MIMO, and/or nonminimum phase. ...
doi:10.1109/cdc.2008.4739238
dblp:conf/cdc/SantilloB08
fatcat:kk5ymbp2efhllojmzevspm6w2i
Adaptive Control Based on Retrospective Cost Optimization
2010
Journal of Guidance Control and Dynamics
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x 6.1 Closed-loop system including the RCF adaptive control algorithm with concurrent RLS identification for Markov parameter updates. . . . . . 154 6.2 Closed-loop disturbance rejection response for a ...
The control is turned on at t = 5 sec, and, at t = 15 sec, the system suffers a 75% loss of control effectiveness. The estimated Markov parameters are used in the adaptive controller update law. ...
The adaptive control algorithm is shown to be effective for systems that are unstable, MIMO, and/or nonminimum phase. ...
doi:10.2514/1.46741
fatcat:76nfwgqh45dqfbjuwxynd6aszu
ADAPTIVE INVERSE CONTROL
[chapter]
1987
Adaptive Systems in Control and Signal Processing 1986
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A stable inverse can be obtained even if the plant is nonminimum-phase. No direct feedback is used, except that the plant output is monitored and utilized to adapt the parameters of the controller. ...
A model-reference inverse control system can learn to approximate a desired reference-model dynamics. ...
for a nonminimum-phase plant. half the length of the adaptive filter, or less. ...
doi:10.1016/b978-0-08-034085-2.50006-7
fatcat:dlrwtaqujrh7xonm7tdgulkmwi
Adaptive Inverse Control
1987
IFAC Proceedings Volumes
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A stable inverse can be obtained even if the plant is nonminimum-phase. No direct feedback is used, except that the plant output is monitored and utilized to adapt the parameters of the controller. ...
A model-reference inverse control system can learn to approximate a desired reference-model dynamics. ...
for a nonminimum-phase plant. half the length of the adaptive filter, or less. ...
doi:10.1016/s1474-6670(17)55929-7
fatcat:hukwbva32ncoleukor23k7rp2e
Page 4376 of Mathematical Reviews Vol. , Issue 86i
[page]
1986
Mathematical Reviews
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stable control of nonminimum phase systems. ...
This collection of papers provides a detailed and comprehensive review of adaptive control techniques and methodology for lin- ear and nonlinear systems, including nonminimum phase systems. ...
Adaptive neurofuzzy controller to regulate UTSG water level in nuclear power plants
2005
IEEE Transactions on Nuclear Science
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Index Terms-Adaptive neurofuzzy system, nonminimum phase dynamics, Takagi-Sugeno fuzzy model, U-tube steam generator. ...
A data-driven adaptive neurofuzzy controller is presented for the water-level control of U-tube steam generators in nuclear power plants. ...
Moon (Korea Atomic Energy Research Institute, Daejeon, Korea) for his advise and guidance for this work. ...
doi:10.1109/tns.2004.842723
fatcat:ghwt6jfhezgmviakgdv372t7rq
System identification using a retrospective correction filter for adaptive feedback model updating
2009
2009 American Control Conference
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In this paper we use a retrospective correction filter (RCF) to identify MIMO LTI systems. This method uses an adaptive controller in feedback with an initial model. ...
Minimum-phase and nonminimum-phase SISO and MIMO examples are considered. The identification signals used include zero-mean Gaussian white noise as well as sums of sinusoids. ...
In the present paper, we focus on the retrospective correction filter-based (RCF) adaptive control algorithm presented in [14] because of its ability to control nonminimum-phase systems. ...
doi:10.1109/acc.2009.5160650
dblp:conf/amcc/SantilloDB09
fatcat:famxbkh3areavdyevmtsxjg5he
Page 1233 of Mathematical Reviews Vol. , Issue 91B
[page]
1991
Mathematical Reviews
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Adaptive linearization of MIMO systems is briefly dis- cussed. Ramon R. Costa (Rio de Janeiro)
91b:93102 93C40 93C55
Tsypkin, Ya. Z.
Nonminimum phase in discrete adaptive control systems. ...
In particular, nonminimum phase discrete-time control is discussed. Specific features and limitations of identification algo- ...
An Adaptive Learning Rate for RBFNN Using Time-Domain Feedback Analysis
2014
The Scientific World Journal
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An intelligent adaptation rule is developed for the learning rate of RBFNN which gives faster convergence via an estimate of error energy while giving guarantee to thel2stability governed by the upper ...
Radial basis function neural networks are used in a variety of applications such as pattern recognition, nonlinear identification, control and time series prediction. ...
This technique was introduced for stable, minimum phase linear systems; however, with appropriate modification it can also be used for nonminimum phase and nonlinear systems [17] . ...
doi:10.1155/2014/850189
pmid:24987745
pmcid:PMC3980919
fatcat:ezj3eavgnzdp7c5jppjaq4lofa
Adaptive inverse control of linear and nonlinear systems using dynamic neural networks
2003
IEEE Transactions on Neural Networks
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The techniques work to control minimum-phase or nonminimum-phase, linear or nonlinear, single-input-single-output (SISO) or multiple-input-multiple-ouput (MIMO), stable or stabilized systems. ...
In this paper, we see adaptive control as a three-part adaptive-filtering problem. First, the dynamical system we wish to control is modeled using adaptive system-identification techniques. ...
Excellent control and disturbance canceling for minimum-phase or nonminimum-phase plants is achieved. Fig. 1 . 1 Adaptive inverse control system.
Fig. 2 . 2 Adaptive plant modeling. ...
doi:10.1109/tnn.2003.809412
pmid:18238019
fatcat:cmjjz67ykrg5hev25quhuokuvq
Robustness of retrospective cost adaptive control to Markov-parameter uncertainty
2011
IEEE Conference on Decision and Control and European Control Conference
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RCAC is applicable to MIMO possibly nonminimum-phase (NMP) plants without the need to know the locations of the NMP zeros. ...
In this paper we investigate the robustness of an extended version of retrospective cost adaptive control (RCAC), in which less modeling information is required than in prior versions of this method. ...
For example, for the 2 nd -order nonminimum-phase system G zu (z) = In this case, adaptive regularization prevents RCAC from destabilizing the closed-loop system, and the performance z(k) converges to ...
doi:10.1109/cdc.2011.6161472
dblp:conf/cdc/SumerDMHB11
fatcat:sxsndgy64jf7rih7hcygflha7e
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