Ho, Charlotte YukFan and Ling, Bingo WingKuen and Liu, YanQun and Tam, Peter KwongShun and Teo, KokLay (2008) Optimum design of discretetime differentiators via semiinfinite programming approach. IEEE Transactions on Instrumentation and Measurement, 57 (10). pp. 22262230. ISSN 00189456
Full content URL: http://dx.doi.org/10.1109/TIM.2008.922090
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Item Type:  Article 

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Abstract
In this paper, a general optimum full band high order discretetime differentiator design problem is formulated as a peak constrained least square optimization problem.
That is, the objective of the optimization problem is to minimize the total weighted square error of the magnitude response subject to the peak constraint of the weighted
error function. This problem formulation provides a great flexibility for the tradeoff between the ripple energy and the ripple magnitude of the discretetime differentiator.
The optimization problem is actually a semiinfinite programming problem. Our recently developed dual parametrization algorithm is applied for solving the problem. The main advantage of employing the dual parameterization algorithm for solving the problem is the guarantee of the convergence of the algorithm and the obtained solution being the global optimal solution that satisfies the corresponding continuous constraints. Moreover, the computational cost of the algorithm is lower than that of algorithms implementing the semidefinite programming approach.
Additional Information:  In this paper, a general optimum full band high order discretetime differentiator design problem is formulated as a peak constrained least square optimization problem. That is, the objective of the optimization problem is to minimize the total weighted square error of the magnitude response subject to the peak constraint of the weighted error function. This problem formulation provides a great flexibility for the tradeoff between the ripple energy and the ripple magnitude of the discretetime differentiator. The optimization problem is actually a semiinfinite programming problem. Our recently developed dual parametrization algorithm is applied for solving the problem. The main advantage of employing the dual parameterization algorithm for solving the problem is the guarantee of the convergence of the algorithm and the obtained solution being the global optimal solution that satisfies the corresponding continuous constraints. Moreover, the computational cost of the algorithm is lower than that of algorithms implementing the semidefinite programming approach. 

Keywords:  Discretetime differentiators, Semiinfinite programming, Dual parameterization algorithm, Peak constrained least square approach, Eigen approach, Remez approach, Semidefinite programming approach 
Subjects:  H Engineering > H660 Control Systems H Engineering > H661 Instrumentation Control H Engineering > H310 Dynamics 
Divisions:  College of Science > School of Engineering 
ID Code:  2692 
Deposited On:  13 Jun 2010 13:33 
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