Development and testing of braking and acceleration features for vehicle advanced driver assistance system

<span lang="EN-US">Traffic congestion is a constant problem for cities worldwide. The human driving inefficiency and poor urban planning and development contribute to traffic buildup and travel discomfort. An example of human inefficiency is the phantom traffic jam, which is caused by unnecessary braking, causing traffic to slow down, and eventually coming to a stop. In this study, a brake and acceleration feature (BAF) for the advanced driver assistance system (ADAS) is proposed to mitigate the effects of the phantom traffic phenomenon. In its initial stage, the BAF provides a heads-up display that gives information on how much braking and acceleration input is needed to maintain smooth driving conditions, i.e., without sudden acceleration or deceleration, while observing a safe distance from the vehicle in front. BAF employs a fuzzy logic controller that takes distance information from a light detection and ranging (LIDAR) sensor and the vehicle’s instantaneous speed from the engine control unit (ECU). It then calculates the corresponding percentage value of needed acceleration and braking in order to maintain travel objectives of smooth and safe-distance travel. Empirical results show that the system suggests acceleration and braking values slightly higher than the driver’s actual inputs and can achieve 90% accuracy overall.</span>

Seismic Collapse Probability and Life Cycle Cost Assessment of Isolated Structures Subjected to Pounding With Smart Hybrid Isolation System Using a Modified Fuzzy Based Controller

The possibility of pounding on isolated structures with surrounding moat walls is one of the concerns in the design of isolation systems, especially in pulse-type near-field earthquakes. This paper puts forward the seismic probability assessment of structures equipped with passive and smart hybrid isolation systems by considering pounding possibilities. This investigation is performed on isolated structures equipped with a high damper rubber bearing (HDRB) considering stiff moat walls around the structure. In the Hybrid isolation system, magnetorheological dampers (MR) are considered an adaptive dissipation energy device along with isolators using an optimized novel interval Type-2 fuzzy logic controller with adaptive red-zone function (IT2FS+RZF) to reduce pounding possibilities. The fragility curves of the building for various cases are determined using IDA analysis, and possible damage costs are evaluated by using exceedance probability in each damage level. This study concludes that the collapse probability of the isolated structures with restrains at the code-based distance is over the acceptable limit of ASCE 7-22. The smart additional damping system with the proposed controller reduces the possible damage cost of the building by about 64% compared to the uncontrolled system and puts the collapse probability of the structure in the acceptable range.

24 Sectors DTC Control with Fuzzy Hysteresis Comparators for DFIM Fed by the Three-level NPC Inverter

This article presents 24 sectors direct torque control (DTC) with fuzzy hysteresis comparators for the doubly-fed induction motor (DFIM) using a three-level neutral point clamped (NPC) inverter. The designed DTC technique of the DFIM combines the advantages of the DTC strategy and fuzzy logic controller. The reaching conditions, stability, and robustness of the DFIM with the designed DTC technique are guaranteed. The designed DTC technique is insensitive to uncertainties, including parameter variations and external disturbances in the whole control process. Finally, the designed DTC technique with fuzzy hysteresis comparators is used to regulate the electromagnetic torque and the flux of the DFIM fed by the three-level NPC inverter and confirms the validity of the designed DTC technique. Results of simulations containing tests of robustness and tracking tests are presented.

Frequency regulation of a RES integrated power system with AC/DC parallel link employing a fuzzy tuned fractional order controller

This paper demonstrates the operational efficacy of a newly proposed fuzzy tuned fractional order controller to offer an improved frequency regulation of a multi area renewable energy source (RES) integrated nonlinear power system. The effect of governor dead band nonlinearity and generation rate constraint of hydro and thermal power plants are considered in the system. Moreover, a proposed appropriate High voltage direct current (HVDC) tie line model is incorporated in this work, to verify the frequency deviation. Different test cases are applied to verify the robustness of the controllers on frequency response. The superiority of the proposed controller upon Proportional integral and derivative (PID), fuzzy logic controller and fuzzy PID controller in minimizing frequency deviation has been verified through MATLAB SIMULINK environment.

Fuzzy Logic Controller for Automating Electrical Conductivity and pH in Hydroponic Cultivation

This study proposes a fuzzy logic controller for adjusting the electrical conductivity (EC) and pH of the nutrient solution in a hydroponic system. The proposed control system detects the EC and pH of the solution through sensors and adjusts the working time of the solution pump through the fuzzy controller. Specifically, the EC and pH of the nutrient solution are maintained at specific values. A Raspberry Pi3 development board is used in the proposed control system to realize and solve the problem of adjusting the EC and pH of the solution. In the fuzzy controller, the inputs are EC and pH sensors, and the output is the operating time of the pump. Experimental results indicate that the proposed control system can effectively reduce the measurement burden and complex calculations of producers by adjusting nutrient solutions.

Real-Time High Performance of Induction Motor Drive Using Hybrid Fuzzy-Sliding Mode Controllers

Obtaining the required performance, stability, and robustness in real-time control of induction motors usually requires the use of complex controllers, however through multiple experimentations, many challenges have arisen from such methods. The complex structure of control methods in real-time applications is usually computationally challenging and energy consuming, hence the need for a simple control strategy to overcome these challenges, in this paper, we focus on designing an advanced hybrid control strategy with a simple design applied to an induction motor. Mainly, the hybrid controller used in this study has the benefits of joining the best performance of both fuzzy logic controller and sliding mode controller, specifically designed to handle each phase separately, the transition phase and the steady phase. A fuzzy controller intervenes as a supervisor in our control structure, more specifically it manages the switch from one type of control to the other taking into account the intervention phase of each type of controller by commanding the rate of both controllers. Control performance analysis was carried out in a real experimental setup to validate the efficiency and robustness of the proposed hybrid controller and confirm its effectiveness in handling the compromise between overshoot and response time.