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In this article, a novel fuzzy proportional integral derivative (PID) controller with filtered derivative action and fractional order integrator (fuzzy PIλDF controller) is proposed to solve automatic generation control (AGC) problem in power system. The optimization task for fine-tuning parameters of the proposed controller structure is accomplished by cuckoo optimization algorithm (COA). To appraise the usefulness and practicability of proposed COA optimized fuzzy PIλDF controller, four extensively used interconnected test systems, that is, two-area non-reheat thermal, two-area multi-source, three-area thermal and three-area hydro-thermal power plants, are considered. Different nonlinearity such as generation rate constraint (GRC) and governor dead band (GDB) as a source of physical constraints are taken into account in the model of the three-area power systems to examine the ability of the proposed technique to handle practical challenges. The acceptability and novelty of COA-based fuzzy PIλDF controller to solve aforesaid test systems are evaluated in comparison with some recently reported approaches. The consequences of time domain simulation reveal that designed secondary controllers provide a desirable level of performance and stability compared with other existing strategies. Additionally, to explore the robustness of the proposed technique, sensitivity analysis is conducted by varying the operating loading conditions and system parameters within a specific tolerable range.

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This paper proposes a new modified model predictive control to compensate for voltage and frequency deviations with higher bandwidth for an AC shipboard microgrid. The shipboard power system (SPS) and islanded microgrids (MGs) have a reasonable analogy regarding supplying loads with local generations. However, a great number of vital imposing pulse loads and highly dynamic large propulsion loads in the SPS make the frequency and voltage regulation a complicated issue. Conventional linear control methods suffer from high sensitivity to parameter variations and slow transient response, which make big oscillations in the frequency and voltage of the SPS. This paper addresses the problem by proposing a novel finite control set model predictive control to compensate for primary frequency and voltage deviations with higher bandwidth and order of magnitude faster than state of the art. Furthermore, a single input interval type-2 fuzzy logic controller (SI-IT2-FLC) is applied in secondary level to damp the steady-state deviations with higher bandwidth. Finally, hardware-in-the-loop (HiL) experimental results prove the applicability of the proposed control structure.

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The negative impedance characteristic of the constant power loads (CPLs) causes instability in DC/DC converters in the DC microgrids. To improve the stability of the DC/DC converter feeding CPLs, a robust and fast controller is required. This paper presents a robust pulse-width modulationbased type-II fuzzy controller for a DC/DC boost converter feeding the CPL in a DC microgrid. Theoretical analysis and real-time simulation are presented to demonstrate the effectiveness of the proposed non-integer intelligent controller. Finally, the experimental results demonstrate that the proposed intelligent controller for the DC/DC converter has a faster and more robust response in comparison to the previously suggested control techniques.