## 2 Methodology
### Proposed Tracking Strategy
Although the proposed algorithm does not manage time per se, the parameter is necessary for estimating the useful life of the components, so recording time and associating the actions performed in the decision-making process is essential to determine comprehensive strategies for reducing the wear of the tracking systems. The findings highlight a 53.33% reduction in the movements required for tracking and a 60.77% reduction in operation time, which translates into a 6.8-fold increase in the lifetime of the solar tracking system under the experimental conditions applied. In addition, the tracking strategy and the real-time data recording will allow effective identification of failure modes to determine critical states during the operation of the tracking system. The collected, filtered, and saved data can be processed in a cloud system to anticipate malfunctions, failures, and maintenance of the tracking systems. On the other hand, control strategies can increase tracker performance; however, even with the most precise control method, the fatigue limits of the robot's structural and mechanical components cannot be exceeded, considering torque, current, and temperature \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Algorithm** & \(|\mathbf{N_{m}}|_{avg}\) **[RPM]** & \(|\mathbf{T_{m}}|_{avg}\) **[Nm]** & \(\mathbf{L_{h}}\) **[hours]** \\ \hline \(DMA\) & 0.1067 & 1.8178 & \(22.77\times 10^{6}\) \\ \hline \(CA\) & 0.1067 & 3.2337 & \(3.34\times 10^{6}\) \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Summary of the experimental results of service life analysis. \begin{table}
\begin{tabular}{c c c c c c} \hline \hline \multirow{2}{*}{**Step**} & \multirow{2}{*}{**Solar Time**} & \multicolumn{2}{c}{**CA**} & \multicolumn{2}{c}{**DMA**} \\ \cline{3-6}  & & \(\mathbf{q_{2}}\) [\({}^{\circ}\)] & \(\mathbf{T_{m}}\) **[Nm]** & \(\mathbf{q_{2}}\) [\({}^{\circ}\)] & \(\mathbf{T_{m}}\) **[Nm]** \\ \hline
0 & 11:30 & 75.22 & - & 75.22 & - \\ \hline
1 & 11:34 & 81.25 & 0.4878 & 80.13 & 0.5496 \\ \hline
2 & 11:38 & 82.19 & 0.4357 & - & - \\ \hline
3 & 11:42 & 83.13 & 0.3835 & - & - \\ \hline
4 & 11:46 & 84.08 & 0.3307 & - & - \\ \hline
5 & 11:50 & 85.02 & 0.2783 & - & - \\ \hline
6 & 11:54 & 85.96 & 0.2259 & - & - \\ \hline
7 & 11:58 & 86.90 & 0.1734 & - & - \\ \hline
8 & 12:02 & 87.84 & 0.1208 & - & - \\ \hline
9 & 12:06 & 88.78 & 0.0683 & - & - \\ \hline
10 & 12:10 & 89.73 & 0.0151 & 91.43 & 0.0862 \\ \hline
11 & 12:14 & 90.67 & 0.0375 & 92.37 & 0.1326 \\ \hline
12 & 12:18 & 91.61 & 0.0901 & 93.31 & 0.1851 \\ \hline
13 & 12:22 & 92.55 & 0.1427 & 94.25 & 0.2376 \\ \hline
14 & 12:26 & 93.50 & 0.1957 & 95.19 & 0.2912 \\ \hline
15 & 12:30 & 94.44 & 0.2482 & 96.14 & 0.3429 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Angular position and torque and data for the CA and DMA strategies. limits. Hence, if the operation time and the tracking action aggressiveness are reduced, as a consequence, the lifetime of the tracking systems can be improved considerably. Although life estimation of the tracker's lifetime is complex due to the variability in the weather conditions, the health of the PV system, and the wear or failure of the tracker components, the proposal presents an approach with promising results that require future research to develop more complex models based on the present strategy that allow defining with greater precision and in a comprehensive manner the improvement of the useful life of the trackers, considering the speed and acceleration profiles, wind loads, temperature, and control action, among others. In addition, a more extensive comparison can be made with state-of-the-art algorithms that allow the development of new strategies that improve the performance of tracking systems and increase their useful life simultaneously.