Optimal Control of Turbine Speed Control System Based on Improved Tunicate Swarm Algorithm

The turbine speed control system has the features of variable operating conditions, time-varying parameters and complex nonlinearity. The use of PID controller makes the system has long adjustment time, a large overshoot and low adjustment accuracy. To calibrate the parameters of this system, a revised algorithm is proposed. Firstly, Tent chaotic initialization is introduced on the basis of the original algorithm to make the tunicates more evenly distributed in the solution space. Secondly, a golden sine partition factor is introduced to generate new individuals before the position is updated, which increase the diversity of optimization particles and reduce the incidence of local optimal solutions. Finally, the nonlinear adaptive weight factor is introduced to adjust the development ability and discovery ability to achieve equalization. By adding frequency disturbance and load disturbance to the turbine speed regulation system, its dynamic characteristics are observed. And the results show that the PID control based on the revised TSA makes system have better dynamic stability characteristics.