One significant benefit of the Maclaurin symmetric mean (MSM) is that it is a generalization of many extend operators and can consider the interrelationships among the multi-input arguments, such as multi-attributes or multi-experts in the multi-attribute group decision making (MAGDM). In the information fusion process, the Schweizer-Sklar T-norm (TN) and T-conorm (TCN), an important class of the TN and TCN, have more flexibility. We define SS operational rules of SFNs and extend SSTN, SSTCN to Spherical fuzzy values (SFVs) in order to fully utilize the advantages of SSTN, SSTCN, and MSM. Next, by combining the MSM with SS operational rules, we propose the spherical fuzzy Schweizer-Sklar weighted Maclaurin symmetric mean (SFSSWMSM) and spherical fuzzy Schweizer-Sklar Maclaurin symmetric mean (SFSSMSM) operators. This research examines their advantages and creates a novel approach based on these operators for particular MAGDM issues. Then, by comparing the suggested technique with current approaches in practical settings, its benefits and viability are demonstrated. Lastly, a few real-world examples are provided to demonstrate the applicability and benefits of the suggested approach in comparison to a few other approaches already in use.
Unmanned Aerial Vehicles (UAVs), have recently sparked attention due to its versatility in a wide range of real-life uses. They require to be controlled so as to conduct different operations and widen their typical roles. This study proposes an optimal robust deadbeat controller for the roll angle motion of tail-sitter vertically take-off and land vehicles, taking into consideration the systems’ intrinsic sensitivity to outside influences and fluctuation of their dynamics. Primarily, several assumptions are used to develop an appropriate transfer function that reflects the system physical attributes. The suggested controller is then formed in two sections: the first section addresses the nominal system’s unstable dynamics, and the second element imposes the desired deadbeat performance and robustness. The control system variables are optimized using the creative and efficient Incomprehensible but Time-Intelligible Logics optimization technique, ensuring that the specified robustness demand is satisfied correctly. Finally, simulation is used to evaluate the developed controller effectiveness, revealing beneficial stability and performance indicators for both nominal and uncertain regulated system featuring uniform, bounded, and feasible closed-loop outputs. The control unit performs well, with a rising time of 0.0965 seconds, a settling time of 0.1134 seconds, and an overshoot of 0.167%.
The quality of state estimation in uncertain systems exerts a significant impact on the performance of control systems. Within these uncertain systems, set-valued mappings introduce output uncertainties, complicating the design of observers. This study maps the output error of uncertain systems to the nonlinear terms of a framer , thereby extending the Luenberger framer. An interval observer design method for uncertain systems is proposed, leveraging monotone system theory to analyze the coherence of the error system. The effectiveness of the algorithm is validated through simulation examples.
In the era of low-carbon travel, maglev cars emerge as a high-speed, environmentally sustainable solution, leveraging their frictionless, smooth operation. This study introduces a nonlinear dynamic model for the longitudinal dynamics of maglev cars, constructed via a data-driven approach. A nonlinear model predictive control (NMPC) strategy, incorporating rotational speed constraints, is developed to address the inherent instability of the open-loop system. The dynamic relationship between the driving force and the rotational speeds of magnetic wheels was quantified using the least squares method (LSM) based on tests conducted across varied rotational speeds. A single-degree-of-freedom model, integrating stiffness and damping characteristics, was subsequently formulated to describe the longitudinal motion of the maglev car. The model’s validity was confirmed through comparison with experimental outputs under varying conditions. Further, the stiffness and damping coefficients were derived from experimental data, enhancing the model’s precision. Control simulations and real-world experiments under diverse operational conditions demonstrated the efficacy of the NMPC in ensuring robust longitudinal tracking. This investigation substantiates the NMPC approach as an effective control strategy for enhancing the stability and performance of maglev transportation systems.
In the pursuit of optimizing automotive suspension systems, a semi-active suspension system (SASS) utilizing continuous skyhook control has been developed to enhance vehicle ride comfort and handling. This system is specifically engineered to mitigate vibrations stemming from high-frequency road excitations. Central to this advancement is the introduction of an electrohydraulic (EH) damper, which is uniquely characterized by solenoid valves capable of adjusting the orifice size to modify damping characteristics. By tuning the damping ratio, the system effectively minimizes the positional oscillations of the sprung mass in response to road irregularities. The dynamic behavior of this damper is comprehensively modeled through a boundary model approach, ensuring precise simulation and prediction of performance. A full-scale quarter-car test platform was constructed to evaluate the dynamic response and the efficacy of various control strategies implemented within the SASS. The performance assessments were conducted using MATLAB Simulink to simulate the behavior of the system under skyhook control algorithms, which aim to maintain the chassis’s vertical stability during disturbances. Comparative tests involving a single EH damper have demonstrated a high level of correlation with the simulated models, achieving a 95% agreement level. These findings underscore the capability of the SASS to surpass traditional hydraulic dampers in terms of performance, cost-efficiency, and versatility in testing applications. The insights garnered from this study not only validate the functionality of the proposed system but also contribute significantly to the body of knowledge in vehicle dynamics and control. This research provides a foundational framework for future exploration and potential implementation of advanced damping systems in the automotive industry.
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