the control schemes that are related to visual servoing systems are often done through trial and error. Based on the classical control concept, it is necessary to have a mathematical model of the plant before designin...
the control schemes that are related to visual servoing systems are often done through trial and error. Based on the classical control concept, it is necessary to have a mathematical model of the plant before designing the controller. therefore, this research focuses on producing a mathematical model of the pan-tilt system. We propose the combination of the computer vision method withthe classic system identification method, namely N4SID to obtain the dynamics model of a pan-tilt system. In this research, the system identification procedure was successful in producing a state-space model of a visual servoing system using a pan-tilt system and a single camera. this study merged traditional system identification techniques with computer vision to create a discrete-time linear state-space model. When the system order value equals three, the approximation withthe minimum MSE value is obtained.
the Internet of things (IoT) has brought significant changes in the way we interact with technology in our homes. Smart homes equipped with IoT devices offer a comfortable and convenient lifestyle. However, managing t...
the Internet of things (IoT) has brought significant changes in the way we interact with technology in our homes. Smart homes equipped with IoT devices offer a comfortable and convenient lifestyle. However, managing these devices and their operations can be challenging, especially for individuals with limited technical expertise. the integration of artificial intelligence (AI) in IoT-based smart homes can potentially overcome these challenges by automating device management and enabling proactive responses to users’ needs. this paper investigates the potential of AI-based automation for IoT-enabled smart homes. We review the literature on AI-based automation and IoT-based smart homes, highlighting their benefits, challenges, and existing solutions. the research methodology used in this study is through deep learning approach. the results indicates that AI-based automation can improve user experience and enhance the efficiency and effectiveness of IoT-based smart homes. However, some technical and ethical challenges, such as privacy and security concerns, need to be addressed.
Face Mask Detection is currently a hot topic that has piqued the interest of researchers all over the world. Today, the entire world is dealing withthe COVID-19 pandemic. To controlthe spread of the Coronavirus the ...
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Although the usage of roundabouts has been widely implemented as an alternative to signalised intersections as a version of traffic control, it is still reported that major traffic congestions commonly occur at rounda...
Although the usage of roundabouts has been widely implemented as an alternative to signalised intersections as a version of traffic control, it is still reported that major traffic congestions commonly occur at roundabouts in urban areas. However, studies show that one of the most promising methods to overcome this issue is through the implementation of an evolutionary algorithm as a method to controlthe phase timings of the traffic light system at roundabouts. As such, this project aims to evaluate the effectiveness of implementing particle swarm optimisation (PSO) as the traffic light control for a signalised roundabout. Hence the performance of the PSO-controlled signalised roundabout is compared withthat of a fixed-time signalised roundabout and also the unsignalised roundabout under different traffic conditions. this project presents a case study inspired by a real-world roundabout, namely the Persiaran Anggerik Mokara Roundabout in Kota Kemuning, Shah Alam, Malaysia. From the study, we can conclude that the usage of a Particle Swarm optimisation (PSO) algorithm is suitable in finding more effective green traffic light phase timings compared to fixed-time traffic lights for all test cases. However, the implementation of the PSO-controlled signalised roundabout is less effective compared to unsignalised roundabouts due the minimal delay incurred from an unsignalised round design. As such, it was concluded that when designing a roundabout systemthat is of similar characteristics as the modelled roundabout for this project, an unsignalised approach to the roundabout system greatly outperforms any traffic light systemthat only has traffic signals at the entrances of the roundabout.
this study is concerned withthe security of networked systems with random sampling intervals and deception attacks using non-fragile sampled-data control. We first establish a discrete-time stochastic model framework...
this study is concerned withthe security of networked systems with random sampling intervals and deception attacks using non-fragile sampled-data control. We first establish a discrete-time stochastic model framework for the networked system with random sampling intervals and deception attacks. Subsequently, by the vectorization and Kronecker product operation, a non-fragile controller is designed such that the exponential mean-square stability of resulting discrete-time stochastic system is guaranteed. Finally, a numerical example is presented to show the effectiveness of the designed algorithm.
this paper aims to deal withthe delay compensation problem for linear systems in the presence of three distributed input delays. A fresh state variable is instituted so as to design the state-based feedback controlle...
this paper aims to deal withthe delay compensation problem for linear systems in the presence of three distributed input delays. A fresh state variable is instituted so as to design the state-based feedback controllers. Whereafter, truncated predictor feedback (TPF) approaches are built to make up for the three distributed input delays. It is displayed that the original system possessing three distributed input delays can be stabilized via the TPF controller. Additionally to demonstrating the efficacy of the built controller via an example.
For a class of nonlinear cascade systems, a novel method is used to acquire the event-triggered control law. Different from the traditional backstepping method, by the recursive design approach of “ascending order an...
For a class of nonlinear cascade systems, a novel method is used to acquire the event-triggered control law. Different from the traditional backstepping method, by the recursive design approach of “ascending order and descending dimension”, the cascade systems are transformed into the high-order fully actuated (HOFA) model. By the HOFA system method, the control law is further obtained. the adaptive controller is designed along withthe event-triggered mechanism (ETM) to save the workload and the energy in signal transmission. We prove that for the closed-loop system, all the signals are uniformly bounded at last. A simulation example is presented, which shows the effectiveness of the adaptive event-triggered controller.
At present, in high-voltage DC transmission systems, when the AC system on the inverter side malfunctions, if the DC controlsystem responds improperly, it will lead to inverter commutation failure. Studying from the ...
At present, in high-voltage DC transmission systems, when the AC system on the inverter side malfunctions, if the DC controlsystem responds improperly, it will lead to inverter commutation failure. Studying from the principle of extinguishing angle control, the advantages and disadvantages of measurement based and calculation based extinguishing angle control methods were compared. A composite control strategy in DC transmission engineering is proposed, and a corresponding control protection model is established in PSCAD/EMTDC, and the feasibility of the optimization strategy is verified. this strategy can effectively avoid the continuous commutation failure of the converter station caused by ground faults in the system, and improve the stable operation efficiency of the DC system.
Photovoltaic power generation system is susceptible to temperature and light conditions, and its P-V curve shows multiple peaks, which reduces the effectiveness of the traditional maximum power point tracking method. ...
Photovoltaic power generation system is susceptible to temperature and light conditions, and its P-V curve shows multiple peaks, which reduces the effectiveness of the traditional maximum power point tracking method. Aiming at this problem, the eagle perching optimization algorithm (EPO) is introduced into maximum power-point-tracking (MPPT) control, and its scaling factor and incremental formula are improved, which effectively improves the convergence speed and reduces the number and amplitude of shocks. In Matlab/Simulink simulation, three test environments are set up: no shadow condition, static shadow condition and abrupt shadow condition. It is verified that the improved eagle perching optimization algorithm can track the maximum output power point of photovoltaic array quickly and stably, and improve the working efficiency of photovoltaic power generation system.
For a class of second-order nonlinear leader-following multi-agent systems with actuator faults and integral quadratic constraints (IQCs) of followers, a fully distributed adaptive consensus control algorithm based on...
For a class of second-order nonlinear leader-following multi-agent systems with actuator faults and integral quadratic constraints (IQCs) of followers, a fully distributed adaptive consensus control algorithm based on improved PID sliding mode is designed. the algorithm only requires local topology information but no global information. According to Lyapunov stability theory, it is demonstrated that multi-agent systems can converge to the vicinity near equilibrium points within a finite time. Finally, the feasibility of the control algorithm proposed in this paper is verified by numerical simulation of multi-agent systems.
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