Özet:

The inverted pendulum is a standard benchmark control problem and numerous control algorithms have evolved over ages. LQR is an optimal control method which is used to control the system. One of the important challenges in the design of LQR in real time applications is the optimal choice of error and control weighting matrices (Q and R), which play a vital role in determining the performance and optimality of the controller. Commonly, trial and error approach are employed for selecting the weighting matrices, which not only burdens the design but also results in non-optimal response. Hence, to choose the elements of Q and R matrices optimally, optimization algorithms are used for selecting the most optimal Q and R matrices which also reduces the performance index of the system. However, stability is only a bare minimum requirement in the system design. Ensuring optimality guarantees the stability of the nonlinear system. The main objective of this project is to design a linear quadratic regulator (LQR) using various optimization algorithms like Artificial Bees Colony (ABC) and Particle Swarm Optimization (PSO) for the inverted pendulum system. The results show that Particle swarm optimization algorithm is efficient in tuning the parameters to give the optimum response.

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