at least a time-delay margin of $0.25$ seconds. From Figure \[figure:bode\], one can see that the cases $(\gamma,\kappa,\eta)=(100, 5, 0)$, $(\gamma,\kappa,\eta)=(100, 50, 10)$, and $(\gamma,\kappa,\eta)=(1000, 50, 0)$ achieves approximately the same rejection of low-frequency disturbances. However, it should be noted that the case $(\gamma,\kappa,\eta)=(1000, 50, 0)$ amplifies measurement noise excessively in comparison to the cases $(\gamma,\kappa,\eta)=(100, 5, 0)$ and $(\gamma,\kappa,\eta)=(100, 50, 10)$. In addition, it should be also noted that the case $(\gamma,\kappa,\eta)=(100, 5, 0)$ has the poorest time-delay margin of $0.1$ seconds, whereas the cases $(\gamma,\kappa,\eta)=(100, 50, 10)$ and $(\gamma,\kappa,\eta)=(1000, 50, 0)$ have time-delay margins of $0.25$ and $0.14$ seconds, respectively. Therefore, one can conclude that the case $(\gamma,\kappa,\eta)=(100, 50, 10)$ achieves good rejection of low-frequency disturbances like the other two cases, has the maximum time-delay margin, and does not inject measurement noise as compared to the case $(\gamma,\kappa,\eta)=(1000, 50, 0)$. This shows the significance of having additional design parameters $\eta$ and $\kappa$ in the control design process. Moreover, the effect of increasing $\kappa$ alone can be depicted from the cases $(\gamma,\kappa,\eta)=(100, 5, 0)$ and $(\gamma,\kappa,\eta)=(100, 50, 0)$. Specifically, it deteriorates the rejection properties of low-frequency disturbances. That is the reason why we increased the adaptation gain $\gamma$ in 