RETRACTED: Artificial ecosystem-based optimization for optimal tuning of robust PID controllers in AVR systems with limited value of excitation voltage

Abstract

This paper presents an application of a novel optimization method called Artificial Ecosystem-Based Optimization (AEO) to determine the optimal design parameters of the proportional-integral-derivative (PID) controller for an automatic voltage regulator (AVR) system. Unlike the previous studies presented in the literature, the proposed method takes into account the excitation voltage limit and therefore formulates a new objective function for optimal PID parameters design. The practical aspect of the proposed constraint is significant since the generator field winding can be seriously damaged in case of the large excitation voltage. The performance of the proposed controller using the solution methodology proposed in this study and its contribution to the robustness of the control system are investigated. Further, the obtained PID parameters are used to simulate the AVR dynamics for a large step change in the generator’s voltage set-point. Besides, the obtained step responses have been compared with the corresponding responses of the AVR system whose PID parameters are determined by using well-known methods presented in the literature. Also, the proposed AEO-PID controller shows superior performances in the case of uncertainties in the AVR system’s parameters, as well as in the presence of the different disturbances in the system. The results obtained show that the obtained parameters provided a more secure and stable machine operation even with changes of the reference, generator, or excitation voltage signals compared with the performance of the controllers obtained by the previous works presented in the literature. Furthermore, AEO has proven its ability to get optimal solutions in a fast and efficient manner in terms of accuracy and time spent per iteration.

RETRACTED: Research on the countermeasures of college students’ mental health education under the background of the epidemic

“…This paper takes the opening of mental health education courses in several local universities as the research object, including undergraduate, specialized and independent institutions. 16 The results showed that the scores of anxiety and terror of college students were significantly higher than the national norm, and the number and proportion of students scoring more than two points in the three factors of anxiety, compulsion and terror ranked the top three. This indicates that during the outbreak of new coronary pneumonia, college students are prone to psychological distress such as anxiety, compulsion and terror, especially in anxiety and terror.…”

Fractional Order PID Controller Design for an AVR System Using Chaotic Yellow Saddle Goatfish Algorithm

“…In the previous table, KA, KE, KG, and KS stand for gains of an amplifier, exciter, generator, and sensor, respectively, while TA, TE, TG, and TS are time constants of the amplifier, exciter, generator, and sensor. Values that are considered in this paper are KA = 10, KE = 1, KG = 1, KS = 1, TA = 0.1, TE = 0.4, TG = 1, and TS = 0.01 [5][6][7][8][9][10][11][12][13][14][15][16][17][18][19][20][21][22]. It is important to mention that the gain of the generator KG depends on the load of the generator.…”

“…, and T S = 0.01 [5][6][7][8][9][10][11][12][13][14][15][16][17][18][19][20][21][22]. It is important to mention that the gain of the generator K G depends on the load of the generator.…”

“…In order to demonstrate the behavior of the system in the different cases of the load, simulations are conducted for different values of parameter K G (0.7, 0.8, 0.9, and 1). In the available literature [4][5][6][7][8][9][10][11][12][13][14][15][16][17][18][19][20][21][22], the components of the AVR (except the controller) are presented as the first-order transfer function, which is composed of gain and time constant. Table 1 gives a compact review of the transfer functions and the range of each parameter.…”

“…Also, it can be found that the authors used Chaotic Ant Swarm (CAS) [7], Multi-Objective Extremal Optimization (MOEO) [9], Cuckoo Search (CS) [10], and Salp Swarm Optimization (SSO) algorithm [12] to determine unknown parameters of the FOPID. Besides the FOPID, many existing studies deal with the optimization of the parameters of the classical PID controller for the AVR systems [13][14][15][16][17][18][19][20][21][22].…”