Grid-forming inverters (GFMIs) are anticipated to play a leading role in future power systems. In contrast to their counterpart grid-following inverters, which employ phase-locked loops for synchronization with the grid voltage and rely on stable grid connections, GFMIs primarily employ the power-based synchronization concept to form the voltage. Hence, they can not only stably operate in regions of the grid characterized by low strength but also provide critical ancillary services to power systems, including voltage, frequency and inertia support. Several control strategies have been employed for GFMIs, making it crucial to comprehend their stability characteristics for the analysis of small-signal stability and low-frequency oscillations. This article examines the performance of GFMIs when equipped with four different control strategies, namely: droopbased GFMI, virtual synchronous generator (VSG)-based GFMI, compensated generalized VSG (CGVSG)based GFMI, and adaptive VSG (AVSG)-based GFMI. The comparative analysis assesses the performance and robustness of these four control strategies across various operational scenarios in frequency and time domains. Initially, the impedance-based stability analysis method is employed to evaluate these control strategies across different case studies in terms of grid strengths, grid impedance ratios, the dynamics with/without virtual impedance and inner voltage and current loops, and variations in the inverter's operating points. Subsequently, time domain verification using the electromagnetic transient models are conducted for these case studies as well as to assess the power tracking capability of these control strategies in response to changes in power references. Finally, the robustness of these four controllers is explored against external grid disturbances, including grid frequency deviations, phase jumps, and voltage sags, considering varying levels of disturbance magnitudes in both weak and strong grid connections. In conclusion, the evaluation of these control techniques in various operational scenarios reveals their strengths and weaknesses, offering valuable guidance for the selection of the most appropriate control technique to suit desired practical applications.