Tabu search algorithm based PID controller tuning for desired system specifications

Multi-objective optimal tuning of two degrees of freedom PID controllers using the ENNC method

“…In this sense, the multi-objective optimization of PID controllers remains an open research topic, even though it has been studied for several decades [5]- [7] and with multiple optimization methods, including bio-inspired techniques such as neural networks, fuzzy logic and genetic algorithms to solve the problem of the optimization [8], [9].…”

New Tuning Method for PI Controllers based on Pareto-Optimal Criterion with Robustness Constraint

“…En [7], un algoritmo de búsqueda Tabú se utiliza para sintonizar controladores PID en tiempo real, basándose en una conjunto de especificaciones de lazo cerrado y una función de costo que se optimiza. En [8] el problema de optimización multiobjetivo para controladores PID se resuelve utilizando la técnica de "colonia de hormigas", que trata de simular el comportamiento de las hormigas reales mientras buscan el camino más corto a un objetivo.…”

Design and performance analysis of PID controller for an automatic voltage regulator system using simplified particle swarm optimization

“…In recent years, many artificial intelligence algorithms are proposed to tune the controller parameters. These approaches include Simulated Annealing (SA) [2], Tabu Search Algorithm [3], Differential Evolution (DE) algorithm [4,5], evolutionary algorithms [6], Genetic Algorithm (GA) [7], fuzzy systems [8], Artificial Bee Colony (ABC) [9], Particle Swarm Optimization (PSO) [10] and multi-objective optimization [11,12]. Recently, to determine the PID parameters suitably, various tuning schemes have been reported by many researchers.…”