Skip to content
Open access

Optimal Design of PID Controller Parameters with Particle Swarm Optimization for Quadrotors

Aug 2026 · International Journal of Combinatorial Optimization Problems and Informatics · Vol 17, pp. 221-232 · 0 citations · 1 references
Computer Science

Abstract

This study presents a comprehensive comparative analysis of multiple Particle Swarm Optimization configurations for optimizing Proportional-Integral-Derivative controllers in quadrotor unmanned aerial vehicles. Traditional PID tuning methods such as Ziegler-Nichols often produce suboptimal performance for complex multi-variable systems. We investigate four distinct PSO configurations—Fast, Balanced, Quality, and Aggressive—evaluating their performance across five diverse flight scenarios including basic takeoff, attitude control, and transitional flight maneuvers. The optimization process focuses on twelve PID parameters controlling altitude, roll, pitch, and yaw dynamics. Experimental results demonstrate that PSO-based optimization significantly outperforms conventional Ziegler-Nichol’s tuning, with Root Mean Square Error improvements ranging from 45.2% to 51.7% across different configurations. Statistical analysis confirms the robustness and consistency of PSO-based approaches across varying operational conditions. Spanish-language metadata / Metadatos en españolTítulo en español:Diseño óptimo de los parámetros de controladores PID mediante optimización por enjambre de partículas para cuadricópteros Resumen:Este estudio presenta un análisis comparativo exhaustivo de múltiples configuraciones de optimización por enjambre de partículas (PSO) para optimizar controladores proporcional-integral-derivativo (PID) en vehículos aéreos no tripulados de tipo cuadricóptero. Los métodos tradicionales de ajuste PID, como el de Ziegler–Nichols, suelen producir un desempeño subóptimo en sistemas multivariables complejos. Se investigan cuatro configuraciones distintas de PSO —Fast, Balanced, Quality y Aggressive— y se evalúa su desempeño en cinco escenarios de vuelo diferentes, entre ellos el despegue básico, el control de actitud y las maniobras de vuelo transicional. El proceso de optimización se centra en doce parámetros PID que controlan la dinámica de altitud, alabeo, cabeceo y guiñada. Los resultados experimentales demuestran que la optimización basada en PSO supera significativamente al ajuste convencional de Ziegler–Nichols, con mejoras en la raíz del error cuadrático medio (RMSE) que oscilan entre el 45.2 % y el 51.7 % para las distintas configuraciones. El análisis estadístico confirma la robustez y la consistencia de los enfoques basados en PSO bajo diversas condiciones operativas. Palabras Claves:control de cuadricópteros; ajuste de controladores PID; optimización por enjambre de partículas; control multivariable; vehículo aéreo no tripulado; dinámica de vuelo; optimización evolutiva; minimización del RMSE; control de actitud; control de altitud; ajuste de Ziegler–Nichols; evaluación del desempeño del controlador. Smart citations: https://scite.ai/reports/10.61467/2007.1558.2026.v17i4.1347Dimensions.Open Alex.

Read PDF

Similar papers

Open access Sep 2026

Comparative Performance Analysis of Nature-Inspired Metaheuristic Algorithms for PID Controller Optimization

Tuning PID controllers for diverse dynamic systems remains a fundamental challenge in control engineering due to the conflicting requirements of fast transient response, robustness, and stability. This study presents a comprehensive comparative analysis of eight nature-inspired metaheuristic algorithms—Genetic Algorith...

Chong-Wen Huang, Hao-Xiang Lei, Cheng-Yi Li et al. · 0 citations
Open access Sep 2026

Precision enhancement in drone position control based on optimized PID: A comparative study

This paper presents a comparative study of quadrotor trajectory tracking performance using proportional integral derivative (PID) controllers optimized by two nature-inspired metaheuristic algorithms: the flower pollination algorithm (FPA) and particle swarm optimization (PSO). A nonlinear dynamic model of the quadroto...

Imam Barket Ghiloubi, Latifa Abdou · 0 citations
Open access Sep 2026

Hybrid metaheuristic NNHGS algorithm for PID controller tuning in UAVs

Controller tuning for unmanned aerial vehicles (UAVs) is a challenging task due to their nonlinear and coupled dynamics. This study validates the hybrid Neural-Network Hunger Games Search (NNHGS) algorithm, which integrates a Kohonen neural network with the Hunger Games Search (HGS) metaheuristic to dynamically adapt t...

N. Zúñiga-Peña, Salatiel Garcia-Nava, N. Hernández-Romero et al. · 0 citations
Conference Aug 2026

Optimization of Fuzzy PID Temperature Control Algorithm Based on Particle Swarm Optimization (PSO)

Fuzzy PID controllers are widely adopted in the field of industrial manufacturing. However, when applied to temperature control systems characterized by large inertia, significant time delay, and potentially time-varying delay, conventional fuzzy PID controllers still face considerable challenges in balancing dynamic r...

Jia-Jun Zheng · 0 citations
Open access Aug 2026

Metaheuristic-Based PI Controller Tuning Using a Multi-Error ITAE Objective Function for FOC-Controlled PMSM Drives in Electric Vehicle Applications

Permanent Magnet Synchronous Motors (PMSMs) are widely employed in electric vehicle (EV) propulsion systems because of their high efficiency, high power density, and superior dynamic performance. The performance of field-oriented control (FOC)-based PMSM drives strongly depends on accurate tuning of the proportional–in...

Ahmed Mashaly, M. Elgohary, R. El-Sehiemy · 1 citation

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.