This article presents a control strategy that combines a super-twisting sliding-mode reaching law with a fuzzy inference system to regulate the liquid level in the third tank of a three-tank non-interacting process. This type of plant is widely used in contemporary industrial process automa-tion, particularly in applications such as petroleum refining, distillation operations, and pulp manufacturing. To obtain the target liquid level, a slid-ing-mode controller employing the super-twisting algorithm is formulated to guarantee finite-time convergence of the tank level to the reference value, thereby improving robustness and tracking precision while inherently mitigating chattering. The fuzzy system is incorporated to estimate the parameters of the super-twisting reaching law adaptively. System stability under the proposed control scheme is demonstrated through Lya-punov analysis with explicit gain conditions. MATLAB/Simulink simulations are carried out and benchmarked against a conventional fuzzy logic controller, a Proportional-Integral-Derivative (PID) fuzzy logic controller, a PID controller using the Amigo tuning rule, and a neural network-based predictive controller. Compared with the selected benchmark controllers, the proposed method achieves faster transient response, zero overshoot, zero steady-state error, and a significantly reduced integral time absolute error (ITAE), while maintaining a competitive integral abso-lute error (IAE). The rise time is 1.6385 s, the settling time is 3.0398 s, and the IAE and ITAE values are 12.37 and 19.58, respectively.
T. Pham, L. Huynh· Acta Mechanica et Automatica· 0 citations
Reliable communication infrastructure is a fundamental component of Intelligent Transport Systems (ITSs), particularly in scenarios involving maritime corridors and emergency traffic management. In locations where optical fiber deployment is geographically constrained, unmanned aerial vehicle (UAV)-assisted free-space optical (FSO) relay links provide a flexible and rapidly deployable alternative. However, atmospheric attenuation, turbulence-induced fading, and wind-induced UAV misalignment can severely degrade link reliability and disrupt real-time transport data streams. This study proposes a payload-efficient multiple-input multiple-output free-space optical (MIMO-FSO) relay architecture based on a multi-output/single-input (MOSI) uplink and a single-output/multi-input (SOMI) downlink. Here, MOSI denotes multiple ground-based transmit apertures directed toward a single UAV receiving aperture, whereas SOMI denotes one UAV transmitting aperture serving multiple ground-based receiving apertures. Unlike conventional symmetric UAV-assisted MIMO-FSO relays that may duplicate diversity hardware on the aerial node, the proposed design shifts the parallel optical branches to the ground stations and keeps only one optical receiver and one optical transmitter on board the UAV. Under the adopted 4 × 4 comparison assumption, this reduces the UAV-side optical branch count from eight to two, corresponding to a 75% branch-count reduction proxy. System performance is evaluated over a 1.54 km relay link. The analytical framework describes Beer–Lambert attenuation, log-normal/gamma–gamma turbulence, and statistical pointing errors; in the OptiSystem implementation, their combined effects are represented by equivalent aggregate losses of 25 dB/km for atmospheric absorption/scattering and 25.5 dB/km for turbulence- and pointing-related degradation. Comparative simulations for SISO, 2 × 2, and 4 × 4 configurations show that the proposed 4 × 4 architecture increases the Q-factor from 8.38 to 18.25 and changes the OptiSystem-reported minimum BER from 2.73 × 10−17 to 9.95 × 10−75. Because a finite simulation cannot statistically validate error probabilities of this magnitude through raw error counting, values far below 10−12 are interpreted primarily as comparative indicators of receiver decision margin. The findings provide simulation-based evidence that the proposed architecture is a scalable candidate for resilient optical wireless backhaul in smart transport corridors under adverse propagation conditions.
H. V. Cuu, L. Huynh, Ž. Koboević· Automation· 0 citations