In the modern world, automobile suspension holds crucial importance in uplifting a cars ride comfort and handling ability. Active suspension can doubtless enhance the driving quality and traveler comfort at the same t...
In the modern world, automobile suspension holds crucial importance in uplifting a cars ride comfort and handling ability. Active suspension can doubtless enhance the driving quality and traveler comfort at the same time. Its a fourth-order advanced system that requires a highly accurate and precise robust control technique. This work presents a highly robust $H_{\infty}$ controller proposed for a quarter car active suspension system and a comparison of it with the prevailing LQR controller design. Also, the design criteria to enhance the transient performance of the system consist of the concept of regional pole placement. Controller behavior is examined through simulation setup using MATLAB/Simulink. Simulation results are shown to explain the efficacy of the developed design.
At present, ad hoc networks are getting a lot of attention, because they have many features that differ from the rest of the networks and because they are technically advanced. In routing protocols, the Vehicular Ad-h...
At present, ad hoc networks are getting a lot of attention, because they have many features that differ from the rest of the networks and because they are technically advanced. In routing protocols, the Vehicular Ad-hoc network (VANET) differ in performance because each protocol has different variables, such as variable density, speed, and traffic scenarios. In this work, we proposed topology-based routing namely Ad hoc On Demand Distance Vector (AODV) protocol. The AODV protocol has been simulated in case of the movement of vehicles at a fixed velocity at 60km/h, and in case of randomly changing the vehicle's locations in the network. There are three parameters used to investigate the performance of the proposed AODV protocol which are packet delivery ratio, and overheads. The Simulation results show a significant decrease from 0.55 to 0.82 in the packet delivery ratio. On the other hand, the performance of the AODV protocol demonstrates effective communication for the VANETs.
In this paper, machine learning-based techniques are used to solve and analyze the modulation format recognition problem. The combination of intelligent software and high-performance hardware provides a large scope fo...
详细信息
Adiabatic quantum-flux-parametron (AQFP) logic is a promising technology for future energy-efficient, high-performance information processing systems. It has significantly low power consumption thanks to the adiabatic...
详细信息
This paper examine the challenges posed by conventional sliding mode design in the presence of matching/nonmatching disturbances. Previously designed approaches have proven inadequate in offering an efficient and stra...
This paper examine the challenges posed by conventional sliding mode design in the presence of matching/nonmatching disturbances. Previously designed approaches have proven inadequate in offering an efficient and straightforward solution to non-matching disturbances. To overcome this, a novel sliding mode control strategy centered on a non-smooth integral sliding manifold is introduced. The newly proposed sliding manifold possesses two crucial characteristics. Firstly, it functions transform to a reduced-order disturbance observer by autonomously estimating the mismatched disturbances, eliminating the need for an additional observer design. Secondly, the system consistently initiates its operation from the sliding surface, eliminating any reaching phase dynamics. As a result, the system trajectory remains resilient to disturbances right from the outset. To validate the effectiveness of the proposed method, it is simulated for a coupled tank system.
Unmanned Aerial Vehicles(UAVs)provide a reliable and energyefficient solution for data collection from the Narrowband Internet of Things(NB-IoT)***,the UAV’s deployment optimization,including locations of the UAV’s ...
详细信息
Unmanned Aerial Vehicles(UAVs)provide a reliable and energyefficient solution for data collection from the Narrowband Internet of Things(NB-IoT)***,the UAV’s deployment optimization,including locations of the UAV’s stop points,is a necessity to minimize the energy consumption of the UAV and the NB-IoT devices and also to conduct the data collection *** this regard,this paper proposes GainingSharing Knowledge(GSK)algorithm for optimizing the UAV’s *** GSK,the number of UAV’s stop points in the three-dimensional space is encapsulated into a single individual with a fixed length representing an entire *** superiority of using GSK in the tackled problem is verified by simulation in seven *** provides significant results in all seven scenarios compared with other four optimization algorithms used before with the same ***,the NB-IoT is proposed as the wireless communication technology between the UAV and IoT devices.
This paper is concerned with control design methods via a new Lyapunov function for fuzzy descriptor systems. Takagi-Sugeno fuzzy descriptor model, that can represent nonlinear systems, are divided into two families: ...
This paper is concerned with control design methods via a new Lyapunov function for fuzzy descriptor systems. Takagi-Sugeno fuzzy descriptor model, that can represent nonlinear systems, are divided into two families: one with same membership functions in both sides of fuzzy systems and another with different membership functions in right and left side of fuzzy systems. Although many papers propose control designs for the above two systems that are derived from Lyapunov stability theory, they are very conservative because they use a Lyapunov function including a single Lyapunov matrix. In this paper, to design less conservative conditions, we propose new Lyapunov functions with all Lyapunov matrices that are multiple. Finally, numerical examples are given to show the effectiveness of our methods.
Despite the potential benefits that the integration of distributed energy resources (DERs) can bring to the system, it may cause problems related to power quality constraints, such $as$ reverse power flow in substat...
Despite the potential benefits that the integration of distributed energy resources (DERs) can bring to the system, it may cause problems related to power quality constraints, such $as$ reverse power flow in substation and overvoltages. An effective approach to address these problems involves the adoption of reactive and active power control in grid-tie inverters associated with DER. Therefore, this paper assesses the impacts of grid-tie inverter control modes, including both Volt-Var and Volt-Watt strategies, on the DER hosting capacity. In order to improve the overall system operation, modifications in the Volt-Var and Volt-Watt curves were proposed. It is noteworthy that these control strategies can have adverse effects on certain distribution system performance indicators, such $as$ voltage deviation and power losses; for this reason, these indicators are also evaluated in this study. A stochastic approach was adopted to deal with the uncertainties associated with DERs and loads. Finally, from tests conducted in the IEEE 33-bus test system, it was concluded that the proper adjustment of the Volt-Var and Volt-Watt control curves significantly influences DER hosting capacity, $as$ well $as$ voltage deviation and power losses.
Recent advancements in brain-computer interface (BCI) technology for steady-state visual evoked potential (SSVEP)-based target identification have shifted from traditional linear algebra (LA) techniques to more sophis...
详细信息
ISBN:
(数字)9798350330991
ISBN:
(纸本)9798350331004
Recent advancements in brain-computer interface (BCI) technology for steady-state visual evoked potential (SSVEP)-based target identification have shifted from traditional linear algebra (LA) techniques to more sophisticated neural network (NN) approaches, driven by their increased accuracy and consistent performance across different subjects. However, adopting NN-based algorithms has introduced complexities in wearable BCI systems, mainly due to their extensive parameter sets that demand significant memory capacity. Moreover, the computational intensity of these models requires reevaluating hardware architectures. Additionally, the advent of Transformer-based models has further advanced the state of the art, providing even higher accuracy and reduced variability in cross-subject performance, placing greater demands on hardware resources. This paper provides an overview of recent algorithmic progress in SSVEP-based target identification. Also, it proposes considerations for the hardware architecture needed to efficiently support the computation of cutting-edge Transformer-based models in wearable BCIs from the perspective of algorithm-hardware co-design.
Modern reinforcement learning (RL) often faces an enormous state-action space. Existing analytical results are typically for settings with a small number of state-actions, or simple models such as linearly modeled Q-f...
详细信息
暂无评论