This paper represents a survey of the recent literature in the area of process identification and parameter estimation techniques applicable to lumped-parameter, deterministic, dynamical systems. Methods reviewed include statistical estimation techniques, direct and indirect methods based on optimal control theory, functional expansion, impulse response, frequency response and a number of other specific methods. Each method is presented in a consistent format which includes an outline of the general characteristics, calculational techniques, experimental techniques, reliability estimates and applications. The overall objective is to provide a basis for comparison of the methods and a guide to particular applications which will assist the reader in selecting the best method for his specific problem Comments and additions are solicited: see page 263.

Performance of process models

A review of process identification and parameter estimation techniques

The fault-tolerant evolutionary design based on negative-correlation redundancy technique is an effective way to improve the fault-tolerance of analog circuits with uncertain faults. In the existing negative-correlation redundancy evolutionary framework (ENCF), the negative-correlation penalty coefficient plays an important role, and it affects the performance of ENCF greatly. However, the value of the negative-correlation penalty coefficient is heavily dependent on the experience of designers. In this paper, we propose a new negative-correlation redundancy evolutionary framework based on stochastic ranking strategy. In order to make comparisons with the existing researches, we employ analog filter as a design example. Experimental results show that the framework proposed in this paper can generate negatively correlated redundancies without specifying the penalty coefficient, and it shows a relatively high ability to convergence compared to ENCF.

A Novel Negative-Correlation Redundancy Evolutionary Framework Based on Stochastic Ranking for Fault-Tolerant Design of Analog Circuit

Analog circuit design is significant and challenging. In this paper, we propose a group-crossover-based variable-length differential evolution (GVDE) for automatic synthesis of analog circuit. We present two experimental results obtained using the proposed GVDE, including a low-pass filter and an inverting amplifier. The results showed that GVDE is able to evolve with variable-length chromosome, which allows both the topology and sizing of analog circuit to be evolved. The proposed GVDE is an efficient algorithmic approach for automatic synthesis of analog circuit.

Performance of process models

Citations

A review of process identification and parameter estimation techniques

A Novel Negative-Correlation Redundancy Evolutionary Framework Based on Stochastic Ranking for Fault-Tolerant Design of Analog Circuit

Differential Evolution with Group Crossover for Automatic Synthesis of Analog Circuit

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