# Nonlinear Tank-Level Control Using Dahlin Algorithm Design and PID Control  
[PERSON]  
1 Faculty of Maritime Studies Kotor, University of Montenegro, Put I Bokeljske Brigade 44, 885330 Kotor, Montenegro; [EMAIL_ADDRESS] (T.D. ); [EMAIL_ADDRESS] (N.M.)1 Faculty of Technical Sciences Cacak, University of Kragujuvac, Svetog Save 65, 32102 Cacak, Serbia; [EMAIL_ADDRESS] Faculty of Electrical Engineering, University of Montenegro, Dzordza Vasingtona bb, 81000 Podgorica, Montenegro; [EMAIL_ADDRESS]. Maritime transport plays an essential role in the overseas transportation of goods. The effectiveness of the transportation process is related to various factors, with ship stability as an essential one. It impacts crucial safety of any seagoing ship. An insufficient ship stability will result in dangerous conditions, such as not favorable listing, strong heel, or even capsizing [9]. Depending on the type of the ship, a large impact on the ship stability is made by the geometry of the tanks and their position onboard the vessels, which are planned and experimentally tested prior to the ship building. Environmental protection awareness has been significantly increased in the last decades due to the rapid social and economic development in the shipping industry [10]. Nowadays, we have new standards for limiting the ship emissions. These have been especially restricted by the MARPOL convention and additionally by some national legislations in order to reduce pollution of the global seas and oceans, as well as the air. This has resulted in the change in practice for the use of heavy fuel oil as the most important energy source in maritime industry. It is to be replaced by alternatives, such as LNG, biofuels, etc., as well as by the latest technologies, such as pure electric propulsion, which is currently in use only with small vessels and is still in the phase of testing. Once again, tank level calculations and proper planning play an important role in the ship's regular operations and safe navigation. With the implementation of exhaust gas purification systems (scrubbers) on the ships, which are still run-on heavy fuel oil due to economic reasons, a large amount of additional harmful chemicals are stored onboard ships in special tanks and under special conditions. Regardless of the continuous improvement in the control technology, the PID controllers are still the most commonly used in industrial applications due to their simple structure, robustness, simplicity, and easy comprehension [11; 12; 13; 14; 15; 16; 17]. Furthermore, PID controller and PI controller are frequently used for tank-level control as described in [18; 19; 20; 21; 22; 23; 24; 25; 26]. Considering the PID controllers, there are several possible applications for liquid-level control:  
* A traditional approach, which includes the implementation of conventional methods, such as Ziegler-Nichols (ZN) in the case of continuous PID controller design, shown in [19], and virtual instrument-based liquid-level control system using conventional PID, as presented in [3];
* The fuzzy logic and neural network approach is represented by the implementation of the fuzzy-PID controller to the liquid-level system using LabVIEW in [20], whereas four control strategies are designed and compared, including classical PID, gain scheduling (GS), internal model control (IMC), and fuzzy logic (FL) principle in [8]. Hybrid PI-neural network (hybrid PI-NN) controllers are presented in [21]. Parameters of PID in [22] were tuned by an artificially intelligent algorithm, such as a fuzzy, neural network, genetic algorithm, BAT algorithm, neuro-fuzzy, IT2 FNNC. An example of the integrated fuzzy logic-based intelligent control of three tank systems is shown in [23]:
* The use of optimization tourniquets, which include fractional order PI and PD controllers, is implemented in [24].