Stability-Guaranteed Two-Phase Design of Odd-Order Variable-Magnitude Digital Filters

2016 ◽  
Vol 26 (02) ◽  
pp. 1750033
Author(s):  
Tian-Bo Deng
Keyword(s):  
Transfer Function ◽  
Digital Filter ◽  
Digital Filters ◽  
Tuning Parameter ◽  
Second Phase ◽  
Variable Model ◽  
Odd Order ◽  
Order Variable ◽  
The Stability ◽  
Fifth Order

Guaranteeing the stability is one of the most critical issues in designing a variable recursive digital filter. In this paper, we first present an odd-order recursive variable model (transfer function) that is used for designing an odd-order variable-magnitude (VM) digital filter, and then we replace the original coefficients of the denominator of the odd-order transfer function with a set of new parameters. These new parameters can ensure that they can take arbitrary values without incurring instability of the designed odd-order VM filter. To make the VM filter coefficients variable, we find all the VM filter coefficients as polynomial functions of the tuning parameter, which includes two phases. The first phase designs a set of recursive digital filters with fixed coefficients (constant filters), and the second phase utilizes a curve-fitting scheme to represent each coefficient as a polynomial function. As a result, the VM filter coefficients become variable, and the proposed parameter-substitution-based denominator coefficients ensure the filter stability. This is the most important contribution of the parameter-substitution-based design scheme. This paper uses the fifth-order demonstrative example to verify the stability guarantee as well as the design accuracy of the obtained the fifth-order VM filter.

scholarly journals Design of IIR Digital Filters with Arbitrary Flatness Using Iterative Quadratic Programming

2015 ◽  
Vol 2015 ◽  
pp. 1-8
Author(s):  
Yasunori Sugita
Keyword(s):  
Transfer Function ◽  
Digital Filters ◽  
Design Method ◽  
Infinite Impulse Response ◽  
Linear Matrix ◽  
Linear Phase ◽  
Iir Filters ◽  
Matrix Equality ◽  
Iir Digital Filters ◽  
The Stability

This paper presents a design method of Chebyshev-type and inverse-Chebyshev-type infinite impulse response (IIR) filters with an approximately linear phase response. In the design of Chebyshev-type filters, the flatness condition in the stopband is preincorporated into a transfer function, and an equiripple characteristic in the passband is achieved by iteratively solving the QP problem using the transfer function. In the design of inverse-Chebyshev-type filters, the flatness condition in the passband is added to the constraint of the QP problem as the linear matrix equality, and an equiripple characteristic in the stopband is realized by iteratively solving the QP problem. To guarantee the stability of the obtained filters, we apply the extended positive realness to the QP problem. As a result, the proposed method can design the filters with more high precision than the conventional methods. The effectiveness of the proposed design method is illustrated with some examples.

Generalized Stability-Triangle for Guaranteeing the Stability-Margin of the Second-Order Digital Filter

2016 ◽  
Vol 25 (08) ◽  
pp. 1650094 ◽  
Author(s):  
Tian-Bo Deng
Keyword(s):  
Digital Filter ◽  
Upper Bound ◽  
Digital Filters ◽  
Stability Margin ◽  
Second Order ◽  
Recursive Digital Filter ◽  
The Stability ◽  
Special Case ◽  
Recursive Digital Filters ◽  
Generalized Stability

In the design of recursive digital filters, the stability of the recursive digital filters must be guaranteed. Furthermore, it is desirable to add a certain amount of margin to the stability so as to avoid the violation of stability due to some uncertain perturbations of the filter coefficients. This paper extends the well-known stability-triangle of the second-order digital filter into more general cases, which results in dented stability-triangles and generalized stability-triangle. The generalized stability-triangle can be viewed as a special case of the dented stability-triangles if the two upper bounds on the radii of the two poles are the same, which is a generalized version of the existing conventional stability-triangle and can guarantee the radii of the two poles of the second-order recursive digital filter below some prescribed upper bound. That is, it is able to provide a prescribed stability-margin in terms of the upper bound of the pole radii. As a result, the generalized stability-triangle increases the flexibility for guaranteeing a prescribed stability-margin. Since the generalized stability-triangle is parameterized by using the upper bound of pole radii, i.e., the stability-margin is parameterized as a function of the upper bound, the proposed generalized stability-triangle facilitates the stability-margin guarantee in the design of the second-order as well as high-order recursive digital filters.

scholarly journals Testing Stability of Digital Filters Using Optimization Methods with Phase Analysis

Energies ◽  
2021 ◽  
Vol 14 (5) ◽  
pp. 1488
Author(s):  
Damian Trofimowicz ◽  
Tomasz P. Stefański
Keyword(s):  
Unit Circle ◽  
Phase Analysis ◽  
Characteristic Equation ◽  
Digital Filter ◽  
Digital Filters ◽  
Computing Time ◽  
Complex Function ◽  
Stochastic Methods ◽  
Final Population ◽  
Candidate Regions

In this paper, novel methods for the evaluation of digital-filter stability are investigated. The methods are based on phase analysis of a complex function in the characteristic equation of a digital filter. It allows for evaluating stability when a characteristic equation is not based on a polynomial. The operation of these methods relies on sampling the unit circle on the complex plane and extracting the phase quadrant of a function value for each sample. By calculating function-phase quadrants, regions in the immediate vicinity of unstable roots (i.e., zeros), called candidate regions, are determined. In these regions, both real and imaginary parts of complex-function values change signs. Then, the candidate regions are explored. When the sizes of the candidate regions are reduced below an assumed accuracy, then filter instability is verified with the use of discrete Cauchy’s argument principle. Three different algorithms of the unit-circle sampling are benchmarked, i.e., global complex roots and poles finding (GRPF) algorithm, multimodal genetic algorithm with phase analysis (MGA-WPA), and multimodal particle swarm optimization with phase analysis (MPSO-WPA). The algorithms are compared in four benchmarks for integer- and fractional-order digital filters and systems. Each algorithm demonstrates slightly different properties. GRPF is very fast and efficient; however, it requires an initial number of nodes large enough to detect all the roots. MPSO-WPA prevents missing roots due to the usage of stochastic space exploration by subsequent swarms. MGA-WPA converges very effectively by generating a small number of individuals and by limiting the final population size. The conducted research leads to the conclusion that stochastic methods such as MGA-WPA and MPSO-WPA are more likely to detect system instability, especially when they are run multiple times. If the computing time is not vitally important for a user, MPSO-WPA is the right choice, because it significantly prevents missing roots.

Random filters which preserve the stability of random inputs

1988 ◽  
Vol 20 (2) ◽  
pp. 275-294 ◽  
Author(s):  
Stamatis Cambanis
Keyword(s):  
Transfer Function ◽  
Moving Average ◽  
Random Processes ◽  
Time Shift ◽  
Linear Filter ◽  
Random Inputs ◽  
The Stability ◽  
Non Gaussian ◽  
Random Gain

A stationary stable random processes goes through an independently distributed random linear filter. It is shown that when the input is Gaussian or harmonizable stable, then the output is also stable provided the filter&s transfer function has non-random gain. In contrast, when the input is a non-Gaussian stable moving average, then the output is stable provided the filter&s randomness is due only to a random global sign and time shift.

Dynamic analysis and control of an active engine mount system

2002 ◽  
Vol 216 (11) ◽  
pp. 921-931 ◽  
Author(s):  
Y-W Lee ◽  
C-W Lee
Keyword(s):  
Transfer Function ◽  
Dynamic Characteristics ◽  
Performance Test ◽  
Adaptive Controller ◽  
Lms Algorithm ◽  
Equivalent Mass ◽  
Engine Mount ◽  
Active Engine ◽  
The Stability ◽  
Mass Spring

Dynamic characteristics of a prototype active engine mount (AEM), designed on the basis of a hydraulic engine mount, have been investigated and an adaptive controller for the AEM has been designed. An equivalent mass-spring-damper AEM model is proposed, and the transfer function that describes the dynamic characteristics of the AEM is deduced from mathematical analysis of the model. The damping coefficient of the model is derived by considering the non-linear flow effect in the inertia track. Experiments confirmed that the model precisely describes the dynamic characteristics of the AEM. An adaptive controller using the filtered-X LMS algorithm is designed to cancel the force transmitted through the AEM. The stability of the LMS algorithm is guaranteed by using the secondary path transfer function derived on the basis of the dynamic model of the AEM. The performance test in the laboratory shows that the AEM system is capable of significantly reducing the force transmitted through the AEM.

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