46 AI MAGAZINE With the advance of automation and infotainment systems in vehicles, driving can be perceived as a comprehensive interactive activity occurring among human drivers and their vehicles. Classically, these users were considered the supervisors of the automated systems running in the cars. In the last decade, we have seen progress toward more autonomous driving automation, including ...

With the benefits of Internet Vehicles (IoV) paradigm, come along unprecedented security challenges. Among many applications inter-connected systems, vehicular networks and smart cars are examples that already rolled out. Smart vehicles not only have connecting their internal components e.g. via Controller Area Network (CAN) bus, but also connected to outside world through road side units other...

this study proposes a combination of a fuzzy sliding mode controller (fsmc) with integral-proportion-derivative switching surface based superconducting magnetic energy storage (smes) and pid tuned by a multi-objective optimization algorithm to solve the load frequency control in power systems. the goal of design is to improve the dynamic response of power systems after load demand changes. in t...

In this study, we reproduce the results from an existing paper on PID tuning using extremum seeking (ES) methods. In addition to analyzing performance with respect to existing tuning methods, we investigate the ES algorithm parameters and how their values impact stability and convergence speed. To demonstrate the efficacy of ES on tuning classical controllers, we apply the algorithm to a simple...

Two different control algorithms, sliding mode and MPC (Model Predictive Control) are employed to analyse the performance of a linear vehicle model equipped with an ACC (Adaptive Cruise Control) system. Both controllers are analysed under critical TM (Transitional Maneuvers) to investigate their suitability for the ACC system. The simulation results, for the same scenario, from both controllers...

 An adaptive input-output linearization method for general nonlinear systems is developed without using states of the system. Another key feature of this structure is the fact that, it does not need model of the system. In this scheme, neurolinearizer has few weights, so it is practical in adaptive situations.  Online training of neuroline...

Car driving could induce fatigue and an altered sensorimotor control of foot muscles. Also, the use of a cruise controller (CC) or an adaptive cruise controller (ACC) could delay the brake reaction time when an emergency braking response is needed. The literature brings very few information on fatigue of the leg muscles during prolonged car driving and no data was found on any lengthened brake ...

Data-based Predictive Control is an emerging control method that stems from Model Predictive Control (MPC). MPC computes current control action based on a prediction of the system output a number of time steps into the future and is generally derived from a known model of the system. Data-based predictive control has the advantage of deriving predictive models and controller gains from inputout...

This paper deals with the design of resilient Cooperative Adaptive Cruise Control (CACC) for homogeneous vehicle platoons in which communication is vulnerable to Denial-of-Service (DOS) attacks. We consider DOS attacks as consecutive packet dropouts. present a controller tuning procedure based on linear matrix inequalities (LMI) that maximizes resiliency attacks, while guaranteeing performance ...

In this paper an adaptive PID controller for Wind Energy Conversion Systems (WECS) has been developed. Theadaptation technique applied to this controller is based on Reinforcement Learning (RL) theory. Nonlinearcharacteristics of wind variations as plant input, wind turbine structure and generator operational behaviordemand for high quality adaptive controller to ensure both robust stability an...