Document Type : Primary Research paper
Assistant Professor(Sr.Gr), Dept of I&CE, PSG College of Technology, Coimbatore.
Professor, Dept of EEE, PSG College of Technology, Coimbatore.
This work deals with servo control problem of a single inverted pendulum using Hybrid Particle Swarm Optimization (HPSO) tuned Linear Quadratic Regulator (LQR). It is important to select the state (Q) and control (R) weighting matrices of LQR in an optimal manner to get optimal results. As a general practice these weighting matrices are selected either through trial and error approach or through experience. This practice in particular makes the job of a control person more tedious and tiresome. To address this issue, a hybrid particle swarm optimization algorithm is proposed to obtain optimal weighting matrices. Moreover, the premature convergence of the particles leading to suboptimal results is accounted by introducing a local convergence monitor, which not only transforms the entire population at the occurrence of local convergence to a new search space but also introduces a disturbance factor in the velocity update equation. The proposed HPSO tuned LQR control strategy is applied to cart position tracking and pendulum angle regulatory control of a single inverted pendulum, which is a highly nonlinear open loop unstable system. Experimental results reveal that compared to PSO tuned LQR, HPSO tuned LQR has improved tracking response with smooth error convergence.