Identification of the Thermoelectric Cooler Using Hybrid Multi-Verse Optimizer and Sine Cosine Algorithm Based Continuous-Time Hammerstein Model

Abstract

This paper presents the identification of the ThermoElectric Cooler (TEC) plant using a hybrid method of Multi-Verse Optimizer with Sine Cosine Algorithm (hMVOSCA) based on continuous-time Hammerstein model. These modifications are mainly for escaping from local minima and for making the balance between exploration and exploitation. In the Hammerstein model identification a continuous-time linear system is used and the hMVOSCA based method is used to tune the coefficients of both the Hammerstein model subsystems (linear and nonlinear) such that the error between the estimated output and the actual output is reduced. The efficiency of the proposed method is evaluated based on the convergence curve, parameter estimation error, bode plot, function plot, and Wilcoxon’s rank test. The experimental findings show that the hMVOSCA can produce a Hammerstein system that generates an estimated output like the actual TEC output. Moreover, the identified outputs also show that the hMVOSCA outperforms other popular metaheuristic algorithms.

Metaheuristics algorithms to identify nonlinear Hammerstein model: a decade survey

“…This tuning step is iteratively performed until the last iteration. This section also explains the Hammerstein model that is widely used to identify real nonlinear plants and processes [16], [17], including Thermoelectric cooler [18], [19], amplified piezoelectric tube actuators [20], forecast of wind speed [21], giant magnetostrictive actuators (GMAs) [22], boiler superheated steam pressure [23], boost converter of DC/DC [24], intelligent pneumatic actuator (IPA) [25], hydraulic mini excavator [26], ultrasonic motor [27], proton exchange membrane fuel cell (PEMFC) [28], turntable servo system [29], valve Stiction [30] and electrically stimulated muscle [31]. The Hammerstein model can accurately model actuators to solve control issues and strengthen nonlinearity system identification.…”