This chapter presents the implementation of advanced control strategies for a portable chemical reactor, integrating classical and intelligent control approaches to enhance process performance. The work independently develops and compares a Tyreus-Luyben controller, a Fuzzy PD controller, and a Genetic Algorithm (GA)-based PID tuning method for regulating temperature and level variables. For the thermal subsystem, the Fuzzy PD controller maintained a temperature within 40–60  \(^\circ \) C with a steady-state error of 0.18  \(^\circ \) C, a rise time of 580 s, and an overshoot of 13.03%. In contrast, the GA-optimized PID controller achieved a lower steady-state error of 0.09  \(^\circ \) C, with a rise time of 2040.65 s and an overshoot of 4.95%. In the level control subsystem, the Fuzzy PD controller regulated the liquid between 2 cm and 10 cm with a steady-state error of 0.01 cm, a rise time of 14.23 s, and an overshoot of 4.43%, while the GA-tuned PID attained a steady-state error of 0.039 cm, a faster rise time of 6.65 s, and a minimal overshoot of 0.004%. Real-time experimental validation using LabVIEW demonstrated the robustness of all control strategies and confirmed the effectiveness of Genetic Algorithm optimization in improving system stability, energy efficiency, and product quality in chemical processes.