Analysis of Improved Particle Swarm Optimization LQG Control of Vehicle Semi Active Suspension on Different Road Grades
This paper describes the problem that the weighting coefficient of LQG controller used in semi-active suspension depends on manual adjustment,and a LQG control method based on improved particle swarm optimization algorithm.The algorithm dynamically adjusts the inertia weight according to the fitness function value,and dynamically adjusts the learning factor through the tanh activation function,which improves its global search ability and convergence speed,and obtains the more adaptive LQG control matrix coefficient.The simulation verifies its effectiveness.
semi-active suspensiondifferent road levelsparticle swarm optimization algorithmLQG control
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