Open AccessProceedings Article
Stabilization of inverted pendulum system using intelligent Linear Quadratic Regulator controller
Salawudeen Ahmed Tijani,M. B. Mua’zu +1 more
- pp 325-333
TLDR
Simulation results showed that the proposed method is efficient in determining the weighting matrices of LQR and minimizes time-to-solution in comparison with the conventional trial-&-error approach.Abstract:
One of the classical problem in dynamics and control theory, which has being widely used as a benchmark for testing control algorithms, such as Linear Quadratic Regulator (LQR) is the balancing of inverted pendulum. The performance of LQR depends largely on the design choice of state and control weighting matrices (Q & R). However, these matrices are usually selected by the designer through a trial and error iterative process which might not guarantee robustness and may increase computational time. To overcome this, we propose a new approach for the optimal determination of the LQR weighting matrices based on weighted artificial fish swarm algorithm (wAFSA). The designed controller is then used to obtain an optimal controller for a dynamic nonlinear Quadruple Inverted Pendulum (QIP). In this paper, we first introduce an approach called inertial weight into the standard Artificial Fish Swarm Algorithm (AFSA) to adaptively select its parameters (visual & step sizes) thereafter, the modified algorithm was used to determine the optimize values of LQR weighting matrices randomly. The optimized values of the weighting matrices were also determined using the standard AFSA and the standard Artificial Bee Colony (ABC) algorithm. This was then used to stabilize the QIP system. Simulation results showed that the proposed method is efficient in determining the weighting matrices of LQR and minimizes time-to-solution in comparison with the conventional trial-&-error approach.read more
Citations
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Proceedings ArticleDOI
Trajectory tracking control of ball on plate system using weighted Artificial Fish Swarm Algorithm based PID
TL;DR: The weighted Artificial Fish Swarm Algorithm is used to optimally tune the parameters of a PID controller applied to trajectory tracking control of a ball on plate system and its good control performance is verified by simulation examples.
Journal ArticleDOI
Optimal Design of PID Controller for Deep Space Antenna Positioning Using Weighted Cultural Artificial Fish Swarm Algorithm
TL;DR: This paper proposed a modification of the Artificial Fish Swarm Algorithm using adaptive behaviour base combination of normative and situational knowledge inherent in cultural algorithm to reduce the chance of falling into local minima by the standard AFSA.
Posted Content
Controlador LQR y SMC Aplicado a Plataformas Pendulares
Miguel F. Arevalo-Castiblanco,C. H. Rodríguez-Garavito,Alvaro A. Patiño-Forero,Jose F. Salazar-Caceres +3 more
TL;DR: In this paper, an optimal LQR controller and a Sliding Mode SMC controller were implemented on two commercial platforms, the Quanser rotary inverted pendulum (RotPen) and the Lego mobile inverted pendula (NxtWay).
Dissertation
Development of a smell agent optimization algorithm for combinatorial optimization problems
Journal ArticleDOI
Controlador LQR y SMC Aplicado a Plataformas Pendulares
Miguel F. Arevalo-Castiblanco,C. H. Rodríguez-Garavito,Alvaro A. Patiño-Forero,Jose F. Salazar-Caceres +3 more
TL;DR: El artículo presenta el comportamiento de los controladores diseñados sobre el modelo analítico comparado with su implementación real, atendiendo las respectivas restricciones de hardware and software en prototipos comerciales.
References
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Book ChapterDOI
Parameter Selection in Particle Swarm Optimization
Yuhui Shi,Russell C. Eberhart +1 more
TL;DR: This paper first analyzes the impact that inertia weight and maximum velocity have on the performance of the particle swarm optimizer, and then provides guidelines for selecting these two parameters.
Journal ArticleDOI
A modified Artificial Bee Colony algorithm for real-parameter optimization
Bahriye Akay,Dervis Karaboga +1 more
TL;DR: Modified versions of the Artificial Bee Colony algorithm are introduced and applied for efficiently solving real-parameter optimization problems.
Journal ArticleDOI
Distributed LQR Design for Identical Dynamically Decoupled Systems
TL;DR: The design procedure proposed in this paper illustrates how stability of the large-scale system is related to the robustness of local controllers and the spectrum of a matrix representing the desired sparsity pattern of the distributed controller design problem.
Journal ArticleDOI
Dynamic clustering with improved binary artificial bee colony algorithm
TL;DR: The obtained results indicate that the discrete artificial bee colony with the enhanced solution generator component is able to reach more valuable solutions than the other algorithms in dynamic clustering, which is strongly accepted as one of the most difficult NP-hard problem by researchers.
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