Temperature control in a continuous stirred tank reactor (CSTR) poses significant challenges due to the process’s inherent nonlinearities and uncertain parameters. This study proposes an innovative solution by developing an adaptive nonlinear proportional–integral–derivative (NPID) controller. The nonlinear gain that dynamically scales the error fed to the integrator is enhanced for optimized performance. The network’s ability to approximate nonlinear functions and its online learning capabilities are leveraged by effectively integrating an NPID control scheme with a radial basis function neural network (RBFNN). This synergistic approach provides a more robust and reliable control strategy for CSTRs. To assess the proposed method’s feasibility, a set of simulations was conducted for tracking, disturbance rejection, and parameter variations. These results were compared with those of an adaptive RBFNN-based PID (APID) controller under identical conditions. The simulations indicated that the proposed method achieved reductions in maximum overshoot of 33.7% and settling time of 54.2% for upward and downward setpoint changes and 27.2% and 5.3% for downward and upward setpoint changes compared to the APID controller. For disturbance changes, the proposed method reduced the peak magnitude (M_peak) by 4.9%, recovery time (t_rcy) by 23.6%, and integral absolute error by 16.2%. Similarly, for parameter changes, the reductions were 3.0% (M_peak), 26.4% (t_rcy), and 24.4% (IAE).

This study investigated the hydraulic characteristics of a self-rotating flood barrier (SRFB) by performing laboratory experiments. The SRFB is proposed as a secure solution to withstand both waves and sudden water level rise, thereby protecting the coastal area behind it. The SRFB is designed to rotate and rise automatically by buoyancy when the water level exceeds a certain threshold or waves start to overtop the crest level of the caisson, where the barrier is enclosed. The barrier begins to rise when the chamber is filled with enough water for the buoyancy force to exceed its own weight. The performance of the structure was tested under various regular wave conditions at different water depths. Pressure transducers were placed along the front face of the barrier to measure the wave pressures acting on it. The barrier’s angular displacement was also identified using synchronized video footage during the measurements. The results showed that the overall magnitude of the measured pressures increased with water depth due to the larger volume of water inflow from overtopping waves. During the rise in the barrier, the pressure profiles dynamically varied with the rotation angle as the pattern of water flow into the chamber changed depending on the test cases. Analysis results showed how the pressures are distributed along the barrier at the moment of peak wave force. These findings would provide fundamental information for estimating design wave forces on the structure.

Ground fault detection in DC-links of high-voltage AC drives is challenging because faults may not produce large currents, while neutral-point voltage monitoring can lose sensitivity under nearly balanced pole-to-ground conductances. This paper develops a physics-based mathematical model and a multipath detection framework for the 5 kV DC-link of the GE MV7306 drive. A closed-form expression for the neutral-point voltage $V_{DC0}$ is derived using Kirchhoff’s current law in terms of equivalent pole-to-ground conductances. A normalized conductance asymmetry index characterizes near-balanced conditions, and logarithmic resistance sensitivity identifies the characteristic transition, $G_{fault}=G_{ref}$, beyond which the neutral-point voltage approaches saturation. The analytical model is also used to relate the fixed voltage threshold to the corresponding fault conductance and fault resistance boundaries. A multipath architecture combining fixed-threshold and robust adaptive-threshold paths is then developed. Circuit-model-based simulations consider degradation–recovery, variable-resistance surface leakage, and near-symmetric conductance oscillation scenarios. The proposed method detects all three scenarios with delays of 1.213, 0.031, and 0.141 s, respectively. For the two scenarios detected by both the proposed method and the fixed-threshold baseline, the mean detection delay decreased from 0.822 to 0.622 s, a 24.3% reduction. The results establish a direct link between the conductance model, nonlinear sensitivity characteristics, and multipath ground fault detection.