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The purpose of this paper is to present a separable identification algorithm for a multiple-input single-output (MISO) continuous-time (CT) system.

This paper proposes an optimal method for the identification of MISO CT systems with unknown time delays by using the Simplified Refined Instrumental Variable method.

Simulations results are presented to show the performance of the proposed approach in the presence of additive output measurement noise.

This paper presents an optimal and robust method to separable delays and parameter identification of a MISO CT system with unknown time delays from sampled input/output data.

A fast identification algorithm for a linear monotonic process from a step response is proposed in this paper, from which the parameters of a first‐order plus dead‐time model can be obtained directly.

The study is based on a non‐asymptotic distributional estimation technique initiated without delay in the framework of systems. Such a technique leads to simple realization schemes, involving integrators, multipliers and piecewise polynomial or exponential time functions and shows a possible link between simultaneous identification and generalized eigenvalue problems. Thus, it allows for a real‐time implementation.

The effectiveness of the identification method has been demonstrated through a number of simulation examples and a real‐time test.

This paper presents a novel method to simultaneous delay and parameters identification of a stable first‐order plus time delay model from step response that can model a widespread class of systems.