In biomedical applications, the regulation of biological systems that contain Genetic Regulatory Networks (GRNs), protein formation, and pancreas structure is crucial for maintaining health. Any significant deviations...
详细信息
In biomedical applications, the regulation of biological systems that contain Genetic Regulatory Networks (GRNs), protein formation, and pancreas structure is crucial for maintaining health. Any significant deviations from the set values of these systems can lead to serious diseases and potentially death. Hence, there's a pressing need for effective controlsystems to manage and regulate these biological processes. Therefore, a novel control approach called Normalized Versatile Fuzzy Fractional-Order Proportional-Integral-Derivative (NV-FFOPID) based controller is suggested to address the challenges of regulating parameters within organic systems. This is designed to control the variables of biological systems like nutrient synthesis, pancreatic function, and GRNs within a Linear-Time Invariant (LTI) model. The stability of the proposed controlsystem is analyzed using appropriate stability theories to ensure its robustness and reliability. To implement and validate the proposed approach, a nonlinear dynamic model of the organic system is developed using Simulink / MATLAB. The efficacy of the NV-FFOPID controller is evaluated by comparing it with numerous advanced control methods commonly taken in biomedical applications. Performance metrics such as convergence time, settling time, overshoot, rise time, and overall system error are used for comparison. The results indicate that the projected controller achieves steady-state conditions with minimal error of 1.2725% in the system. Additionally, it exhibits a lower settling time of 3.7 s, an overshoot having 0.5, a convergence time of 10 s, and a rise time of 1.985 s compared to alternative methods. These findings suggest that the developed NV-FFOPID controller effectively regulates parameter variations in biological systems, thereby offering significant advantages in addressing complex biomedical problems. The proposed approach holds promise for improving the management and control of crucial biological processes, con
The hydrogen energy storage system(HESS)integrated with renewable energy power generation exhibits low reliability and flexibility under source-load *** address the above issues,a two-stage optimal scheduling model co...
详细信息
The hydrogen energy storage system(HESS)integrated with renewable energy power generation exhibits low reliability and flexibility under source-load *** address the above issues,a two-stage optimal scheduling model considering the operation sequences of HESSs is proposed for commercial community integrated energy systems(CIESs)with power to hydrogen and heat(P2HH)*** aims to optimize the energy flow of HESS and improve the flexibility of hydrogen production and the reliability of energy supply for ***,the refined operation model of HESS is established,and its operation model is linearized according to the operation domain of HESS,which simplifies the difficulty in solving the optimization problem under the premise of maintaining high approximate ***,considering the flexible start-stop of alkaline electrolyzer(AEL)and the avoidance of multiple energy conversions,the operation sequences of HESS are ***,a two-stage optimal scheduling model combining day-ahead economic optimization and intra-day rolling optimization is established,and the model is simulated and verified using the source-load prediction data of typical days in each *** simulation results show that the two-stage optimal scheduling reduces the total load offset by about 14%while maintaining similar operating cost to the day-ahead economic optimal ***,by formulating the operation sequences of HESS,the operating cost of CIES is reduced by up to about 4.4%.
Traffic surveillance systems are essential for ensuring public safety and optimizing urban traffic flow by accurately detecting, classifying, and monitoring traffic law violations such as illegal parking and jaywalkin...
详细信息
In recent years, the need for surface life-saving is gradually increasing as a response to accidents such as ship collisions in the marine environment. To solve this problem, there were approaches that launched life-s...
详细信息
Researchers worldwide are exploring renewable hybrid energy systems that integrate battery energy storage systems and hydrogen production technology to combat climate change. The study presents a novel hydrogen produc...
详细信息
This research estimates the power loss in photovoltaic (PV) systems through a Random Forest model by using 15-min interval data for two years (2021-2023) of operation from a university campus located in Delhi, India. ...
详细信息
In the process industries, it's hard to control a non-linear process. Nonlinear behavior is frequently seen in real processes. The challenging problem of controlling a spherical tank is result of its nonlinearity ...
详细信息
This study investigates the controllability of a general heterogeneous networked sampled-data system(HNSS) consisting of nonidentical node systems, where the inner coupling between any pair of nodes can be described b...
详细信息
This study investigates the controllability of a general heterogeneous networked sampled-data system(HNSS) consisting of nonidentical node systems, where the inner coupling between any pair of nodes can be described by a unique *** signals on control and transmission channels are sampled and held by zero-order holders, and the control sampling period of each node can be different. Necessary and sufficient controllability conditions are developed for the general HNSS, using the Smith normal form and matrix equations, respectively. The HNSS in specific topology or dynamic settings is discussed subsequently with easier-to-verify conditions derived. These heterogeneous factors have been determined to independently or jointly affect the controllability of networked sampled-data systems. Notably, heterogeneous sampling periods have the potential to enhance the overall controllability, but not for systems with some special dynamics. When the node dynamics are heterogeneous,the overall system can be controllable even if it is topologically uncontrollable. In addition, in several typical heterogeneous sampled-data multi-agent systems, pathological sampling of single-node systems will necessarily cause overall uncontrollability.
This paper proposes an event-triggered stochastic model predictive control for discrete-time linear time-invariant(LTI) systems under additive stochastic disturbances. It first constructs a probabilistic invariant set...
详细信息
This paper proposes an event-triggered stochastic model predictive control for discrete-time linear time-invariant(LTI) systems under additive stochastic disturbances. It first constructs a probabilistic invariant set and a probabilistic reachable set based on the priori knowledge of system *** with enhanced robust tubes, the chance constraints are then formulated into a deterministic form. To alleviate the online computational burden, a novel event-triggered stochastic model predictive control is developed, where the triggering condition is designed based on the past and future optimal trajectory tracking errors in order to achieve a good trade-off between system resource utilization and control performance. Two triggering parameters σ and γ are used to adjust the frequency of solving the optimization problem. The probabilistic feasibility and stability of the system under the event-triggered mechanism are also examined. Finally, numerical studies on the control of a heating, ventilation, and air conditioning(HVAC) system confirm the efficacy of the proposed control.
Incorrect autonomous driving decisions on highways can lead to traffic congestion and accidents. Therefore, accurate decision-making in highways is essential. However, decision-making in highways is a challenging task...
详细信息
暂无评论