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The hydraulic turbine governing system (HTGS) is a complex nonlinear system that regulates the rotational speed and power of a hydro-generator set. In this work, an incremental form of an HTGS nonlinear model was established and the Takagi–Sugeno (T-S) fuzzy linearization and mixed H2/H∞ robust control theory was applied to the design of an HTGS controller. A T-S fuzzy H2/H∞ controller for an HTGS based on modified hybrid particle swarm optimization and gravitational search algorithm integrated with chaotic maps (CPSOGSA) is proposed in this paper. The T-S fuzzy model of an HTGS that integrates multiple-state space equations was established by linearizing numerous equilibrium points. The linear matrix inequality (LMI) toolbox in MATLAB was used to solve the mixed H2/H∞ feedback coefficients using the CPSOGSA intelligent algorithm to optimize the weighting matrix in the process so that each mixed H2/H∞ feedback coefficients in the fuzzy control were optimized under the constraints to improve the performance of the controller. The simulation results show that this method allows the HTGS to perform well in suppressing system frequency deviations. In addition, the robustness of the method to system parameter variations is also verified.

The penetration of distributed generators (DGs)-based power electronic devices leads to low inertia and damping properties of the modern power grid. As a result, the system becomes more susceptible to disruption and instability, particularly when the power demand changes during critical loads or the system needs to switch from standalone to a grid-connected operation mode or vice versa. Developing a robust controller to deal with these transient cases is a real challenge. The inverter control method via the virtual synchronous generator (VSG) control method is a better way to supply the system’s inertia and damping features to boost system stability. Therefore, a nonlinear control strategy for VSG with uncertain disturbance is proposed in this paper to enhance the system stability in the islanded, grid-connected, and transition modes. Firstly, the mechanical equations for a VSG’s rotor, which include virtual inertia and damping coefficient, are presented, and the matching mathematical model is produced. Then, the nonlinear backstepping controller (BSC) method combined with the extended state observer (ESO) is constructed to compensate for the uncertainty. The Lyapunov criteria were used to prove the method’s stability. Considering the issue of uncertain items, a second-order ESO is built to estimate uncertainty and external disruption. Finally, the suggested control strategy is validated through three simulation experiments; the findings reveal that the proposed control method has an excellent performance with fast response and tracking under various operating situations.

The primary control goals of a wind turbine (WT) are structural load shedding, maximum wind energy capture in the underpowered situation, and consistent power production in the full power condition. A crucial component of the control problem for wind turbines with varying speeds is maximum power tracking control. Conventional maximum power tracking control tracks the ideal blade tip speed ratio to provide the most wind power at the specified wind speeds. However, because of the wind turbine’s great nonlinearity and the significant external disturbances it encounters, it is difficult to react quickly to variations in wind speed, and the tracking speed is sluggish, which lowers the amount of electricity produced annually. In light of this, this work develops a novel preset performance controller for a wind power system maximum power tracking control. With this technique, the convergence rate and tracking precision may be set. In particular, based on the concept of time-varying feedback, a time-varying function, known as the preset performance function, is first created to allow the convergence speed and accuracy to be predetermined; then this time-varying function is used to transform the actual specified time problem of the original system into a bounded time problem of the new system; finally, a direct robust controller design strategy with pre-defined performance is suggested based on the design concept of the backstepping technique. The plan may maximize the rotor power coefficient by altering the wind turbine speed, track the ideal blade tip speed ratio for a given tracking accuracy and speed, and get the most wind power to produce the most power with the strongest robustness. The simulation results show that the recommended control technique works.