This study evaluates control strategies for a single-degree-of-freedom lower-limb exoskeleton designed for aquatic rehabilitation, integrating hydrotherapy with robotic systems. The objective is to enhance motion precision and stability using Proportional-Integral (PI), Fuzzy Logic Control (FLC), and a hybrid Fuzzy-PI controller, optimized via the Quantum Approximate Optimization Algorithm (QAOA). The prototype, modeled as a simple pendulum and tested in a simulated aquarium environment, simplifies aquatic dynamics by neglecting hydrodynamic forces and fluid-structure interactions. The hybrid controller combines FLC’s smooth initial response with PI’s precise stabilization, achieving error rates below 4% for angles between 17° and 50°. QAOA simulations in Qiskit, using a single-layer circuit with COBYLA, optimized PI gains (e.g., Kp = 0.08, Ki = 6.0), demonstrating near-optimal performance. Results indicate improved smoothness and stability compared to standalone PI or FLC controllers. However, the study’s reliance on simulations limits real-world applicability. Future work should include physical prototype testing and incorporate detailed modeling of hydrodynamic forces, fluid-structure interactions, and actuator limitations to enhance clinical relevance. Extending to multi-degree-of-freedom systems and benchmarking QAOA against classical optimization methods will further advance aquatic exoskeleton technology for personalized rehabilitation.