Stability Study of PWM Feedback Systems

1964 ◽  
Vol 86 (1) ◽  
pp. 80-86 ◽  
Author(s):  
E. I. Jury ◽  
T. Nishimura

A fundamental equation which yields the limit-cycle feature of PWM feedback system is derived in this paper. The application of this equation to obtain the response of the autonomous as well as the forced PWM system is indicated. The application of this fundamental equation to other types of nonlinear sampled-data feedback systems is also demonstrated. The maximum mode of the limit cycles that can exist in relay-mode oscillations of PWM systems as well as the limitations on the maximum period is obtained in this paper. Based on the foregoing derivations, the sufficient conditions for eliminating all saturated oscillations is derived. The experimental study performed on the digital computer confirms the theoretical results. Stability curves for certain PWM systems are being calculated which will aid considerably in this design. The basic advantage of PWM controllers on relay sampled-data systems with regard to sensitivity and stability is well pointed out in this paper as well as a few examples illustrating the application of the fundamental equations derived.

1982 ◽  
Vol 104 (1) ◽  
pp. 49-57 ◽  
Author(s):  
Guy Jumarie

The concept of entropy in information theory is used to investigate the sensitivity and the stability of sampled-data systems in the presence of random perturbations. After a brief background on the definition, the practical meaning and the main properties of the entropy, its relations with asymptotic insensitiveness are exhibited and then some new results on the sensitivity and the stochastic stability of linear and nonlinear multivariable sampled data systems are derived. A new concept of stochastic conditional asymptotic stability is obtained which seems to be of direct application in the analysis of large-scale systems. Sufficient conditions for stability are stated. This approach provides a new look over stochastic stability. In addition, variable transformations act additively on entropy, via Jacobian determinant, and as a result the corresponding calculus is very simple.


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