In this paper, two robust controllers have been designed to automatically regulate the synchronous generator voltage for an extensive domain of the system parameters in a single-machine infinite bus (SMIB) framework. These two controllers are based on the fuzzy set, and the type-2 fuzzy logic plus the proportional–integral (PI) operation, respectively. The Fuzzy and Type-2 fuzzy logic decisions are independent of the system parameters which increase the system robustness against the uncertainties and disturbances, and the PI controller can eliminate the terminal voltage steady-state error. The performance of the controllers has been optimized by adjustment of the four coefficients of each controller through Artificial Bee Colony, Imperialistic Competitive Algorithm, and Particle Swarm Optimization (PSO). Five scenarios with four different patterns for reference input and disturbances have been considered to show the competency of the designed controllers. The simulations which have been done by PSO optimization results show the higher robustness of these controlling combination against the load fluctuations, the sequence of the input voltage, and changes in the system parameters, such as the gains and time constants of the amplifier, exciter, and generator in contrast to optimized PID with metaheuristic algorithms.

在本文中，设计了两个鲁棒控制器，用于在单机无限总线 (SMIB) 框架中为广泛的系统参数域自动调节同步发电机电压。这两个控制器分别基于模糊集和类型 2 模糊逻辑加上比例积分 (PI) 操作。Fuzzy和Type-2模糊逻辑决策独立于系统参数，增加了系统对不确定性和干扰的鲁棒性，PI控制器可以消除端电压稳态误差。通过人工蜂群、帝国竞争算法和粒子群优化 (PSO) 调整每个控制器的四个系数，优化了控制器的性能。已经考虑了具有四种不同模式的参考输入和干扰的五种场景，以显示所设计控制器的能力。通过 PSO 优化结果进行的仿真表明，这些控制组合对负载波动、输入电压序列以及系统参数的变化（例如放大器、励磁机的增益和时间常数）具有更高的鲁棒性，和生成器与使用元启发式算法优化的 PID 形成对比。