Active filters tuning interface

A complete system for automated control and test of RF tunable circuits is presented in this paper. The proposed system has been conceived to calibrate and tune variable active filters, but without lack of generality, it is suitable to be used for any voltage-controlled active circuit. It is based on a hardware interface and a dedicated optimization software based on a modified version of the Differential Evolution. The device that has been conceived requires a Vector Network Analyzer (VNA), which is used to acquire the S-parameters of the Device Under Test (DUT) and a computation platform (a personal computer, for instance). The system reads the current measurements and acts on the circuit control voltages optimizing its transfer function accordingly to the desired calibration goals. Test and measurements have shown the capability of the system to achieve good performances in terms of convergence speed and accuracy.

[1]  R. Storn,et al.  Differential Evolution: A Practical Approach to Global Optimization (Natural Computing Series) , 2005 .

[2]  S. Safavi-Naeini,et al.  Computer diagnosis and tuning of microwave filters using model-based parameter estimation and multi-level optimization , 2000, 2000 IEEE MTT-S International Microwave Symposium Digest (Cat. No.00CH37017).

[3]  Kawthar A. Zaki,et al.  Computer-aided diagnosis and tuning of cascaded coupled resonators filters , 2002 .

[4]  R. Storn,et al.  On the usage of differential evolution for function optimization , 1996, Proceedings of North American Fuzzy Information Processing.

[5]  Ajith Abraham,et al.  Mixed Mutation Strategy Embedded Differential Evolution , 2009, 2009 IEEE Congress on Evolutionary Computation.

[6]  Leonardo Pantoli,et al.  Tunable Active filters for RF and microwave Applications , 2014, J. Circuits Syst. Comput..

[7]  Raafat R. Mansour,et al.  Fully Automated RF/Microwave Filter Tuning by Extracting Human Experience Using Fuzzy Controllers , 2008, IEEE Transactions on Circuits and Systems I: Regular Papers.

[8]  Rainer Storn,et al.  Differential Evolution – A Simple and Efficient Heuristic for global Optimization over Continuous Spaces , 1997, J. Glob. Optim..

[9]  H. Chaloupka,et al.  Computer-aided tuning and diagnosis of microwave filters using sequential parameter extraction , 2004, 2004 IEEE MTT-S International Microwave Symposium Digest (IEEE Cat. No.04CH37535).

[10]  Gao-yang Li,et al.  The summary of differential evolution algorithm and its improvements , 2010, 2010 3rd International Conference on Advanced Computer Theory and Engineering(ICACTE).

[11]  Mohammad Bagher Menhaj,et al.  A modified differential evolution algorithm based on a new mutation strategy and chaos local search for optimization problems , 2014, 2014 4th International Conference on Computer and Knowledge Engineering (ICCKE).

[12]  Leonardo Pantoli,et al.  Low-noise tunable filter design by means of active components , 2016 .

[13]  P. Harscher,et al.  Automated filter tuning using generalized low-pass prototype networks and gradient-based parameter extraction , 2001 .