Power converters (PCs) with their control techniques help regulate voltages of nodes in microgrids with different types of loads such as resistive, inductive, nonlinear, constant power, or critical loads. However, constant power loads (CPLs) affect the stability of the voltage in the output of PCs and are usually difficult to regulate with traditional control techniques. The sliding-mode control (SMC) with the washout filter technique has been recently proposed to address this issue, but studies that consider the phenomenon and parameters present in real systems are required. Therefore, this paper focuses on evaluating the dynamic behavior of an SMC based on a washout filter using three different loads: A constant impedance load (CIL), a nonlinear CPL, and a combination of CIL and CPL. The CIL considered a resistance connected to the circuit, whereas the nonlinear CPL was designed by using a buck converter with zero average dynamics and fixed-point induction control techniques (ZAD-FPIC). The tests consisted of creating some variations in the reference signals to identify the output voltage and the error that the control brings according to the different loads. Besides, this study focuses on representing the dynamic behavior of signals when loads change, considering quantization effects, system discretization, delay effects, and parasitic resistors. Additionally, bifurcation diagrams are created by changing the control parameter k and plotting the regulated voltage and the error produced in the output signals. To illustrate the advantages of the SMC with the washout filter technique, a comparison was made with other techniques such as the proportional–integral–derivative (PID) and conventional SMC by varying the load. The results showed that SMC with the washout filter technique was superior to the PID and the conventional SMC because it stabilizes the signal faster and has a low steady-state error. Additionally, the control system regulates well the output voltage with the three types of load and the system remains stable when changing the parameter k for values greater than 1, with a low error in the steady-state operation.

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