Department of Electrical Engineering, Langarud Branch, Islamic Azad University, Langarud, Iran
Abstract
The objective of this paper is to design an optimal regulator for the stabilization of a specific category of chaotic systems following a two-step process. First, the chaotic system is transformed into state-dependent equations. Second, the State Dependent Riccati Equation (SDRE) is solved using the power series method to locate the optimal control law. For the proper regulatory response, an intuitive nature optimization algorithm is employed, and the weight matrices in the SDRE equation are optimized. To design an optimal regulator using this algorithm, we obtain weighted matrices through the Artificial Bee Colony (ABC) algorithm. The honey bee algorithm is used to design the appropriate values of the gain coefficients by minimizing the fitness function. The fitness function we have chosen is the sum of squares of system state errors, which allows the regulator to effectively stabilize the chaotic system with less error, faster response, and lower control costs. The simulation compares the efficacy of regulators designed to stabilize and control chaotic systems, specifically analyzing the regulatory response of this algorithm versus the SDRE method.
Khoshhal Rudposhti, M. (2023). Design Of a New Optimal Controller for a Particular Class of Chaotic Systems Using the Artificial Bee Colony Algorithm (ABC). Transactions on Machine Intelligence, 6(4), 31-40.
MLA
M. Khoshhal Rudposhti. "Design Of a New Optimal Controller for a Particular Class of Chaotic Systems Using the Artificial Bee Colony Algorithm (ABC)". Transactions on Machine Intelligence, 6, 4, 2023, 31-40.
HARVARD
Khoshhal Rudposhti, M. (2023). 'Design Of a New Optimal Controller for a Particular Class of Chaotic Systems Using the Artificial Bee Colony Algorithm (ABC)', Transactions on Machine Intelligence, 6(4), pp. 31-40.
VANCOUVER
Khoshhal Rudposhti, M. Design Of a New Optimal Controller for a Particular Class of Chaotic Systems Using the Artificial Bee Colony Algorithm (ABC). Transactions on Machine Intelligence, 2023; 6(4): 31-40.
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