This paper presents a low-cost virtual platform for evaluating dual-axis photovoltaic solar trackers, assisted by control algorithms, using a partial Hardware-in-the-Loop (signal-in-the-loop) approach. A computer-aided design-derived mechanical model is built in SolidWorks® and executed in Matlab-Simulink®/Simscape Multibody, while an Arduino® interface provides real-time interaction and controlled disturbance injection. The mechanical tracker is simulated in Simulink/Simscape, while the only physical hardware is the Arduino® interface, which is used for real-time disturbance induction and signal acquisition. Four tests were performed using a 15 h astronomical trajectory (54 000 s): undisturbed tracking, disturbed tracking without control, and disturbed tracking with PI control (including a zoomed window). Disturbance magnitudes are reported as the equivalent angular deviations observed between the setpoint and the measured tracker angles. Without control, perturbations produced sustained deviation and an unusable trajectory. With PI control, the platform quantified disturbance rejection using standard tracking metrics. Maximum transient errors were |e_max| ≈ 27° (elevation) and |e_max|≈ 33° (azimuth); root mean square errors were 15.46° and 17.51°, respectively, with residual errors on the order of 10^− 3 degrees and settling times (±1° band) of 4.98 s and 5.06 s. The results show that the proposed PHIL virtual environment supports repeatable, disturbance-oriented controller tuning and early-stage design decisions aligned with renewable energy efficiency improvements. Future work will focus on automating disturbance profiles, mapping tracking errors to harvested energy, and extending the platform toward a Digital Twin with synchronized data and real-time parameter updates.

Fiber optics sensors based on multimodal interference (MMI) have proven effective for refractometry of liquid samples. Here, we extend these capabilities to demonstrate that aqueous solutions with a similar refractive index (RI), which at room temperature are indistinguishable at the same concentration, can be discriminated against based on their thermo-optical response. We used an MMI sensor with the standard singlemode–multimode–singlemode architecture, where a section of no-core multimode fiber provides environmental sensitivity to the fiber surroundings. The proposed idea has been tested on aqueous solutions of tris and fructose, whose RI has a similar dependence on concentration. Indeed, we verified that they produce indistinguishable wavelength shifts as a function of concentration, measuring 0.2179 nm/% for tris and 0.2264 nm/% for fructose. Then, by varying the temperature in a controlled manner, from 25 °C to 45 °C in 2.5 °C increments, the distinct thermo-optic response can be unveiled for the two samples, which now permits differentiating them. Thermal sensitivities of 0.14433 nm/°C for tris and 0.1852 nm/°C for fructose were observed. This optical sensor requires no specific preparation or specialized equipment because the temperature range needed to achieve thermo-optical discrimination is accessible. Therefore, the measurement protocol can be incorporated into commercial refractometers equipped with temperature control.