Rafael C. B. Sampaio

A New Control Architecture for Robust Controllers in Rear Electric Traction Passenger HEVs

It is well known that control systems are the core of electronic differential systems (EDSs) in electric vehicles (EVs)/hybrid HEVs (HEVs). However, conventional closed-loop control architectures do not completely match the needed ability to reject noises/disturbances, especially regarding the input acceleration signal incoming from the drivers commands, which makes the EDS (in this case) ineffective. Due to this, in this paper, a novel EDS control architecture is proposed to offer a new approach for the traction system that can be used with a great variety of controllers (e.g., classic, artificial intelligence (AI)-based, and modern/robust theory). In addition to this, a modified proportional-integral derivative (PID) controller, an AI-based neuro-fuzzy controller, and a robust optimal H∞ controller were designed and evaluated to observe and evaluate the versatility of the novel architecture. Kinematic and dynamic models of the vehicle are briefly introduced. Then, simulated and experimental results were presented and discussed. A Hybrid Electric Vehicle in Low Scale (HELVIS)-Sim simulation environment was employed to the preliminary analysis of the proposed EDS architecture. Later, the EDS itself was embedded in a dSpace 1103 high-performance interface board so that real-time control of the rear wheels of the HELVIS platform was successfully achieved.

FVMS: A novel SiL approach on the evaluation of controllers for autonomous MAV

The originality of this work is to propose a novel SiL (Software-in-the-Loop) platform using Microsoft Flight Simulator (MSFS) to assist control design regarding the stabilization problem found in ©AscTec Pelican platform. Aerial Robots Team (USP/EESC/LabRoM/ART) has developed a custom C++/C# software named FVMS (Flight Variables Management System) that interfaces the communication between the virtual Pelican and the control algorithms allowing the control designer to perform fast full closed loop real time algorithms. Emulation of embedded sensors as well as the possibility to integrate OpenCV Optical Flow algorithms to a virtual downward camera makes the SiL even more reliable. More than a strictly numeric analysis, the proposed SiL platform offers an unique experience, simultaneously offering both dynamic and graphical responses. Performance of SiL algorithms is presented and discussed.

Robust control in 4×4 hybrid-converted touring vehicles during urban speed steering maneuvers

The present work is focused on the synthesis and the analysis of robust control techniques for rear electric traction control in 4×4 hybrid-converted CVs (Conventional Vehicles) at urban speed limits (lower than 60 Km/h). This set represents a practicable alternative for the automotive industry, improving vehicular performance and reducing considerably fossil fuel air pollution. Our goal is to design an electromechanical controlled system that can replace the conventional rear wheels in touring cars with a pair of electric wheels with a minimal level of adaptation, preserving the original combustion engine. We consider the synthesis of an H∞ robust controller and also the neurofuzzy approach. An optimized PID controller was also designed for the final analysis and evaluation. Based on Ackerman Geometry and the reading of the steering front angles, it was possible to estimate the maneuver radius from turning center. Thus, all three proposed control approaches must adjust the rear wheels individual angular speeds by means of the current control of the two electrical motors linked to them, so that the car presents an appropriate behavior during all possible maneuvers. Finally, computation models were run in order to compare the three controllers.

Novel SiL evaluation of an optimal H ∞ controller on the stability of a MAV in flight simulator

This paper introduces a novel methodology to assist the evaluation of control algorithms for MAVs (Micro Aerial Vehicles) using Software-in-the-Loop (SiL) based flight simulation. The originality of this paper is to use ©Microsoft Flight Simulator (MSFS) as the environment to embed both the dynamic and graphic models of ©Ascending Technologies Pelican MAV flying robot. The resulting is a reliable model of the Pelican quadrotor. The full duplex communication between the virtual aircraft and the control algorithm is achieved by a custom C++/C software named FVMS (Flight Variables Management System), developed by Aerial Robots Team (ART), which is able to reach (read/write) a great number of flight variables from MSFS. To illustrate the effectiveness of such method, we first completely present FVMS architecture and main features. Later, the synthesis and then the application of the optimal H∞ robust control algorithm and its operation into the FVMS SiL context are explained. Regarding MAVs control evaluation, SiL simulation considerably contributes to save battery time, to ease control synthesis and prototyping and to prevent accidents during tests with the real robot. The final goal is to evaluate the stability of the Pelican platform in hovering tasks in flight simulation focusing on the efficiency of FVMS to properly run the optimal H∞ robust control algorithm. The SiL control of the MAV has proven FVMS capabilities, which may be extended to assist the design of other classes of controllers.

Optimal H ∞ controller on the stability of MAVs in a novel Software-in-the-Loop control platform

This paper presents a novel Software-in-the-Loop (SiL) evaluation of an optimal H∞ robust controller on the stability problem of MAVs (Micro Aerial Vehicles) in the quadrotor configuration, whose originality is to employ ©Ascending Technologies Pelican MAV. The synthesis of the robust controller is grounded by the γ-iteration algorithm, which results in a MIMO optimal controller bounded by an attenuation level. The core of SiL platform, a customized C++/C# software named FVMS (Flight Variables Management System), developed by ART (Aerial Robots Team) at USP/EESC, is able to deal with full duplex communication to ©Microsoft Flight Simulator (MSFS). In turn, MSFS acts as the virtual environment through which a complete dynamic and graphic model of the Pelican MAV can be configured and emulated. Since FVMS can fully reach every variable related to the simulated MAV, the optimal H∞ control algorithm can be implemented for evaluation in SiL simulation. Hence, the stability of the Pelican MAV can be observed. Regarding MAVs control evaluation, SiL simulation potentially contributes to save battery time, to ease control synthesis and prototyping and to prevent accidents during tests with the real robot. Results of Pelican stabilization in SiL simulation in hovering mode are presented and discussed.

HELVIS: A mini platform in the research of HEVs

The HELVIS (Hybrid Electric Vehicle In Low Scale) mini-HEV has shown to be a very efficient (and attractive) platform on the research of HEVs (Hybrid Electric Vehicles) at our institution. It represents a powerful mean to introduce engineering students to the peculiarities that surrounds the HEVs subject. In this work the mini-HEV platform is presented, as well as some of its important elements, such as the drive train architecture, the EDS control module, the steering system, the IC-engine and the energy generation system. Such a platform can head students and enthusiasts not only to the HEVs technical aspects but, from a more philosophical point of view, it can be an important tool on spreading the new paradigm of a less aggressive transportation system, promoting the idea of reducing the carbon emissions. Furthermore, it is important to look forward to the increasing demand of manpower resources in the automotive industry regarding the specialization on EVs/HEVs. Thus, the University figures as a very appropriate environment to achieve these goals.

Optimal H ∞ controller with a novel control architecture in the HELVIS mini-HEV EDS

HELVIS (Hybrid Electric Vehicle In Low Scale) has shown to be a very efficient platform in the research of HEVs (Hybrid Electric Vehicles) at our institution, as a mean to introduce students of all degrees to the technical universe that surrounds the HEV subject. In this work, a novel approach on the design of controllers to the EDS (Electronic Differential System) problem is presented. The synthesis of a reliable optimal H∞ robust controller to the EDS of HELVIS autonomous mini-HEV using the γ-iteration algorithm is outlined. A new control architecture to fully meet the H∞ controller high ability to reject noises is also proposed. Furthermore, the proposed architecture is a result of an well defined and distributed blocks of functionalities which makes the system suitable for low scale embedded applications. Main aspects, as robustness to noises and performance at a vast range of frequencies are illustrated. At the end, experimental results are evaluated, after embedding the entire HELVIS ED system in a dSpace™ 1103 interface board.

Novel hybrid electric motor glider-quadrotor MAV for in-flight/V-STOL launching

This work presents a novel lightweight electric UAV that features fixed-wing motor glider aircraft and quadrotor helicopter capabilities. This paper presents the hybrid concept, design, evaluation and operation of a MAV (Mini Aerial Vehicle) named Sharky, fully designed and crafted by ART (Aerial Robots Team), which may be a versatile flying robot to broaden the scope of a great number of autonomous/tele-operated missions. To illustrate, Sharky may be potentially useful on precise positioning of sensors/equipment at any point in water/ground/air areas. The MAV may aid atmospheric sensing, water sample collecting, precise positioning of sensor for agriculture, surveillance of restricted/non-structured areas, such as post-disaster sites. The aircraft is morphologically and aerodynamically shaped to perform well defined and specific features, e.g., in-flight stable launching from a carrier, gliding ability, powered flight (motor-glider), transition between glider and quadrotor (and vice versa) and base level launching either as a quadrotor or a motor glider. Sharky transition (glider/quadrotor/glider) may be achieved at anytime during the mission. The aircraft center of mass is slightly shifted to offer gliding/motor gliding stability. Because it is a quadrotor, Sharky may either work as an inverted pendulum problem. Thus, translations and rotations are easily achieved using part of the potential energy from center of mass unbalance. Still, Sharky is easily able to return back to glider/motor glider configuration by using the same principle. That helps minimizing brushless motors usage and, therefore, battery consumption. Dynamic models are presented and analyzed. Sharky stability and controllability are first evaluated in VLM/Panels software. Secondly, wind tunnel analysis are run.

GISA: A Brazilian platform for autonomous cars trials

According to WHO, traffic safety is one of the major concerns of this decade. Due to this, researchers worldwide aim to reduce the large number of fatalities in traffic accidents. This paper presents GISA as a contribution to this scenario. It consists of a platform for testing autonomous car algorithms. Firstly, some requisites to build an autonomous vehicle are presented, followed by sensors, their placement and ROS middleware. Some tests are presented to check the platform performance, including localization issues and obstacle detection. Results show that GISA is a consistent platform for implementation of autonomous car algorithms.

Fuzzy Control Strategy Applied to Adjustment of Front Steering Angle of a 4WSD Agricultural Mobile Robot

This paper presents the preliminary studies of the control strategy based in fuzzy logic, projected for the steering system of AGRIBOT project that consist of a wheeled autonomous mobile robotic in real scale endowed with four independent steering and driven wheels (4WSD). In this work we present a preliminary fuzzy controller design applied to front steering angle, using a multivariable plant which incorporates simplified linear model of lateral dynamics of a vehicle whose input are linear combination of rear and front steering angles. The fuzzy control strategy was decided because provides flexible way to deploy with embedded systems. Simulations are used to illustrate the designed controller performance. We use Ackerman geometry to trace front steering angle that allows the vehicle to perform correctly a given maneuver preserving a minimum level of stability and maneuverability. The goal is to establish a relationship between steering input commands and the control commands to the actuators so that it is possible to adjust the attitude of the actuators over the movement axis, as the trajectory change.