Design and Development of Magneto-Rheological Actuators with Application in Mobile Robotics

In recent years, Magneto-Rheological (MR) fluids devices are widely studied and used for various purposes. Among these MR fluids devices, the MR actuator has attracted increasing attention for last two decades. An MR actuator is usually made of an active component (motor) and MR clutches. Compared with the regular actuators, the MR actuator features compliance due to the existence of MR fluids, which is commonly consider as benefits at the aspect of safety. On the other hand, the MR actuator has advantages on controllable bandwidth, torque-mass and torque-inertia ratios compared with the other compliant actuators. In this study, a new closed-loop, Field-Programable-Gate-Array (FPGA) based control scheme to linearize an MR clutch\u27s input-output relationship is presented. The feedback signal used in this control scheme is the magnetic field acquired from hall sensors within the MR clutch. The FPGA board uses this feedback signal to compensate for the nonlinear behavior of the MR clutch using an estimated model of the clutch magnetic field. The local use of an FPGA board will dramatically simplify the use of MR clutches for torque actuation. The effectiveness of the proposed technique is validated using an experimental platform that includes an MR clutch as part of a compliant actuation mechanism. The results clearly demonstrate that the use of the FPGA based closed-loop control scheme can effectively eliminate hysteretic behaviors of the MR clutch, allowing to have linear actuators with predictable behaviors. Moreover, a novel optimization design of MR clutches is proposed. Based on the optimization, the characteristics of MR clutches in three common configurations are discussed and compared. People can select suitable configuration of MR clutch before design. Lastly, a lightweight mobile robot is developed by using MR actuators. This mobile robot also has large driving force and can stop at any positions without running the motor

Neurofuzzy controller based full vehicle nonlinear active suspension systems

To design a robust controller for active suspension systems is very important for guaranteeing the riding comfort for passengers and road handling quality for a vehicle. In this thesis, the mathematical model of full vehicle nonlinear active suspension systems with hydraulic actuators is derived to take into account all the motions of the vehicle and the nonlinearity behaviours of the active suspension system and hydraulic actuators. Four robust control types are designed and the comparisons among the robustness of those controllers against different disturbance types are investigated to select the best controller among them. The MATLAB SIMULINK toolboxes are used to simulate the proposed controllers with the controlled model and to display the responses of the controlled model under different types of disturbance. The results show that the neurofuzzy controller is more effective and robust than the other controller types. The implementation of the neurofuzzy controller using FPGA boards has been investigated in this work. The Xilinx ISE program is employed to synthesis the VHDL codes that describe the operation of the neurofuzzy controller and to generate the configuration file used to program the FPGA. The ModelSim program is used to simulate the operation of the VHDL codes and to obtain the expected output data of the FPGA boards. To confirm that FPGA the board used as the neurofuzzy controller system operated as expected, a MATLAB script file is used to compare the set of data obtained from the ModelSim program and the set of data obtained from the MATLAB SIMULINK model. The results show that the FPGA board is effective to be used as a neurofuzzy controller for full vehicle nonlinear active suspension systems. The active suspension system has a great performance for vibration isolation. However the main drawback of the active suspension is that it is high energy consumptive. Therefore, to use this suspension system in the proposed model, this drawback should be solved. Electromagnetic actuators are used to convert the vibration energy that arises from the rough road to useful electrical energy to reduce the energy consumption by the active suspension systems. The results show that the electromagnetic devices act as a power generator, i.e. the vibration energy excited by the rough road surface has been converted to a useful electrical energy supply for the actuators. Furthermore, when the nonlinear damper models are replaced by the electromagnetic actuators, riding comfort and the road handling quality are improved. As a result, two targets have been achieved by using hydraulic actuators with electromagnetic suspension systems: increasing fuel economy and improving the vehicle performance

DEVELOPMENT OF HARDWARE-IN-THE-LOOP SIMULATION SYSTEM FOR ELECTRIC POWER STEERING CONTROLLER TESTING

The Electronic Control Unit (ECU) of an Electric Power Steering (EPS) system is a core device to decide how much assistance an electric motor applies on steering wheel. EPS ECUs play an important role in EPS systems. The effectiveness of EPS ECUs needs to be thoroughly tested before mass production. Hardware-in-the-loop (HIL) simulation provides an efficient way for the development and testing of embedded controllers. This report focuses on the development of HIL system for testing EPS controllers. The hardware of the HIL system employs a dSPACE HIL simulator. The EPS plant model is an integrated model consisting of Vehicle Dynamics model of the dSPACE Automotive Simulation Model (ASM) and the Nexteer model. The report presents the design of EPS HIL system, the simulation of sensors and actuators, the functions of ASM Vehicle Dynamics model, and the integration method of ASM Vehicle Dynamics model with Nexteer model. The offline simulation of the integrated model is performed and the results for different driving maneuvers are presented. The real-time HIL testing will be conducted in the future to examine the performance of an entire HIL system

Integrated tilt and active lateral secondary suspension control in high speed railway vehicles

The use of tilting bodies on railway vehicles is increasingly widespread with a number of well-established services using tilt technology already existing around the world. The motivation for tilting railway vehicles is that they give a cost-effective means of achieving a substantial reduction in journey time by increasing the vehicle speed during curves, without the need of building new high speed railtrack infrastructure. A tilting railway vehicle is a dynamically complex structure. Many of the dynamic modes of the system are coupled and the coupling in certain situations, i.e. coupling between the vehicle lateral and roll modes, is very significant which unavoidably causes difficulties in control system design, especially for the local vehicle control strategies. Meanwhile, the high speed results in the worse ride quality on straight track, and an effective solution is to use the active secondary suspension. This research investigated control strategies for the integration of tilt and active lateral secondary suspension. The simulation results showed the efficiency of this research on enhancing local tilting control performance both on straight and curved track. Furthermore, Multi-input and Multi-output system configuration, control and optimization, as well as model-based estimation are also investigated for this tilt and lateral actuators control system aiming to further improve the control system robustness and performance. Finally, a FPGA-based Hardware-In-the-Loop simulation system is set up with the considersion of the controller practical implementation.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Hardware-in-the-loop Testing of On-Off Controllers in Semi-Active Suspension Systems

International audienceThis paper presents an experimental validation of a proposed Frequency Estimation-Based (FEB) controller for semi-active suspensions by using a Hardware-in-the-Loop (HiL) platform of a Quarter of Vehicle (QoV) model. The FEB approach is compared with three commercial On-Off controllers that have shown good results in comfort and road holding: Sky-Hook (SH), Groud-Hook (GH) and Mix-1-sensor (M1S). The comparison was done under the same experimental tests; the standards ISO-2631 and BS-6841 are used to evaluate the comfort and the Root Mean Square (RMS) index to quantify the road holding. The QoV model belongs to a front-left corner of a pick-up truck; the used experimental Magneto-Rheological (MR) damper is not symmetric and only hast 2 manipulation states. Experimental results show that the FEB controller has the best comfort performance at low frequencies (outperforms the benchmark controllers at 11.2%); while, for road holding, the improvement is slight; however, FEB controller works better for both goals simultaneously. By analyzing the suspension deflection, the FEB controller reduces up to 32.8% of motion respect to the GH controller. Additionally, the manipulation of the SH and GH controllers have several changes of actuation that do not allow the stabilization of the force in its desirable value; while FEB controller has a soft actuation defined on bandwidths

Integrated tilt and active lateral secondary suspension control in high speed railway vehicles

The use of tilting bodies on railway vehicles is increasingly widespread with a number of well-established services using tilt technology already existing around the world. The motivation for tilting railway vehicles is that they give a cost-effective means of achieving a substantial reduction in journey time by increasing the vehicle speed during curves, without the need of building new high speed railtrack infrastructure. A tilting railway vehicle is a dynamically complex structure. Many of the dynamic modes of the system are coupled and the coupling in certain situations, i.e. coupling between the vehicle lateral and roll modes, is very significant which unavoidably causes difficulties in control system design, especially for the local vehicle control strategies. Meanwhile, the high speed results in the worse ride quality on straight track, and an effective solution is to use the active secondary suspension. This research investigated control strategies for the integration of tilt and active lateral secondary suspension. The simulation results showed the efficiency of this research on enhancing local tilting control performance both on straight and curved track. Furthermore, Multi-input and Multi-output system configuration, control and optimization, as well as model-based estimation are also investigated for this tilt and lateral actuators control system aiming to further improve the control system robustness and performance. Finally, a FPGA-based Hardware-In-the-Loop simulation system is set up with the considersion of the controller practical implementation.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

High performance control of a multiple-DOF motion platform for driver seat vibration test in laboratory

Dynamic testing plays an important part in the vehicle seat suspension study. However, a large amount of research work on vibration control of vehicle seat suspension to date has been limited to simulations because the use of a full-size vehicle to test the device is an expensive and dangerous task. In order to decrease the product development time and cost as well as to improve the design quality, in this research, a vibration generation platform is developed for simulating the road induced vehicle vibration in laboratory. Different from existing driving simulation platforms, this research focuses on the vehicle chassis vibration simulation and the control of motion platform to make sure the platform can more accurately generate the actual vehicle vibration movement. A seven degree-of-freedom (DOF) full-vehicle model with varying road inputs is used to simulate the real vehicle vibration. Moreover, because the output vibration data of the vehicle model is all about the absolute heave, pitch and roll velocities of the sprung mass, in order to simulate the vibration in all dimensions, a Stewart multiple-DOF motion platform is designed to generate the required vibration. As a result, the whole vibration simulator becomes a hardware-in-the-loop (HIL) system. The hardware consists of a computer used to calculate the required vibration signals, a Stewart platform used to generate the real movement, and a controller used to control the movement of the platform and implemented by a National Instruments (NI) CompactRIO board. The data, which is from the vehicle model, can be converted into the length of the six legs of the Stewart platform. Therefore, the platform can transfer into the same posture as the real vehicle chassis at that moment. The success of the developed platform is demonstrated by HIL experiments of actuators. As there are six actuators installed in the motion platform, the signals from six encoders are used as the feedback signals for the control of the length of the actuators, and advanced control strategies are developed to control the movement of the platform to make sure the platform can accurately generate the required motion even in heavy load situations. Theoretical study is conducted on how to generate the reasonable vibration signals suitable for vehicle seat vibration tests in different situations and how to develop advanced control strategies for accurate control of the motion platform. Both simulation and experimental studies are conducted to validate the proposed approaches

Implementation in Embedded Systems of State Observers Based on Multibody Dynamics

Programa Oficial de Doutoramento en Enxeñaría Naval e Industrial . 5015V01[Abstract] Simulation has become an important tool in the industry that minimizes either the cost and time of new products development and testing. In the automotive industry, the use of simulation is being extended to virtual sensing. Through an accurate model of the vehicle combined with a state estimator, variables that are difficult or costly to measure can be estimated. The virtual sensing approach is limited by the low computational power of invehicle hardware due to the strictest timing, reliability and safety requirements imposed by automotive standards. With the new generation hardware, the computational power of embedded platforms has increased. They are based on heterogeneous processors, where the main processor is combined with a co-processor, such as Field Programmable Gate Arrays (FPGAs). This thesis explores the implementation of a state estimator based on a multibody model of a vehicle in new generation embedded hardware. Different implementation strategies are tested in order to explore the advantages that an FPGA can provide. A new state-parameter-input observer is developed, providing accurate estimations. The proposed observer is combined with an efficient multibody model of a vehicle, achieving real-time execution.[Resumen] La simulación se ha convertido en una importante herramienta para la industria que permite minimizar tanto costes como tiempo de desarrollo y test de nuevos productos. En automoción, el uso de la simulación se extiende al desarrollo de sensores virtuales. Mediante un modelo preciso de un vehículo combinado con un observador de estados, variables que son caras o imposibles de medir pueden ser estimadas. La principal limitación para utilizar sensores virtuales en los vehículos es la baja potencia computacional de los procesadores instalados a bordo, debido a los estrictos requisitos impuestos por los standards de automoción. Con el hardware de nueva generación, el poder de cálculo de las plataformas empotradas se ha visto incrementado. Estos nuevos procesadores son del tipo heterogéneo, donde el procesador principal se complementa con un co-procesador, como una Field Programmable Gate Array (FPGA). Esta tesis explora la implementación de un observador de estados basado en un modelo multicuerpo de un vehículo en hardware empotrado de nueva generación. Se han probado diferentes implementaciones para evaluar las ventajas de disponer de una FPGA en el procesador. Se ha desarrollado un nuevo observador de estados, parámetros y entradas que permite obtener estimaciones de gran precisión. Combinando dicho observador con un eficiente modelo multicuerpo de un vehículo, se consigue rendimiento en tiempo real.[Resumo] A simulación estase a converter nunha importante ferramenta na industria que permite minimizar custes e tempo tanto de desenvolvemento coma de test de novos productos. En automoción, o uso da simulación esténdese á implementación de sensores virtuais. Mediante un modelo preciso dun vehículo combinado cun observador de estados, pódense estimar variables que son caras ou imposíbeis de medir. A principal limitación para utilizar sensores virtuais nos vehículos é a baixa potencia computacional dos procesadores instalados a bordo, debido aos estritos requisitos impostos polos estándares de automoción. Co hardware de nova xeración, o poder de cálculo das plataformas empotradas vese incrementado. Estos novos procesadores son de tipo heteroxéneo, onde o procesador principal compleméntase cun co-procesador, coma unha Field Programmable Gate Array (FPGA). Esta tese explora a implementación dun observador de estados basado nun modelo multicorpo dun vehículo en hardware empotrado de nova xeración. Diferentes implementacións foron probadas para avaliar as vantaxes de dispoñer dunha FPGA no procesador. Un novo observador de estados, parámetros e entradas deseñado nesta tese permite obter estimacións de gran precisión. Combinando dito observador cun eficiente modelo multicorpo dun vehículo, conséguese rendemento de tempo real

Real-time multi-domain optimization controller for multi-motor electric vehicles using automotive-suitable methods and heterogeneous embedded platforms

Los capítulos 2,3 y 7 están sujetos a confidencialidad por el autor. 145 p.In this Thesis, an elaborate control solution combining Machine Learning and Soft Computing techniques has been developed, targeting a chal lenging vehicle dynamics application aiming to optimize the torque distribution across the wheels with four independent electric motors.The technological context that has motivated this research brings together potential -and challenges- from multiple dom ains: new automotive powertrain topologies with increased degrees of freedom and controllability, which can be approached with innovative Machine Learning algorithm concepts, being implementable by exploiting the computational capacity of modern heterogeneous embedded platforms and automated toolchains. The complex relations among these three domains that enable the potential for great enhancements, do contrast with the fourth domain in this context: challenging constraints brought by industrial aspects and safe ty regulations. The innovative control architecture that has been conce ived combines Neural Networks as Virtual Sensor for unmeasurable forces , with a multi-objective optimization function driven by Fuzzy Logic , which defines priorities basing on the real -time driving situation. The fundamental principle is to enhance vehicle dynamics by implementing a Torque Vectoring controller that prevents wheel slip using the inputs provided by the Neural Network. Complementary optimization objectives are effici ency, thermal stress and smoothness. Safety -critical concerns are addressed through architectural and functional measures.Two main phases can be identified across the activities and milestones achieved in this work. In a first phase, a baseline Torque Vectoring controller was implemented on an embedded platform and -benefiting from a seamless transition using Hardware-in -the -Loop - it was integrated into a real Motor -in -Wheel vehicle for race track tests. Having validated the concept, framework, methodology and models, a second simulation-based phase proceeds to develop the more sophisticated controller, targeting a more capable vehicle, leading to the final solution of this work. Besides, this concept was further evolved to support a joint research work which lead to outstanding FPGA and GPU based embedded implementations of Neural Networks. Ultimately, the different building blocks that compose this work have shown results that have met or exceeded the expectations, both on technical and conceptual level. The highly non-linear multi-variable (and multi-objective) control problem was tackled. Neural Network estimations are accurate, performance metrics in general -and vehicle dynamics and efficiency in particular- are clearly improved, Fuzzy Logic and optimization behave as expected, and efficient embedded implementation is shown to be viable. Consequently, the proposed control concept -and the surrounding solutions and enablers- have proven their qualities in what respects to functionality, performance, implementability and industry suitability.The most relevant contributions to be highlighted are firstly each of the algorithms and functions that are implemented in the controller solutions and , ultimately, the whole control concept itself with the architectural approaches it involves. Besides multiple enablers which are exploitable for future work have been provided, as well as an illustrative insight into the intricacies of a vivid technological context, showcasing how they can be harmonized. Furthermore, multiple international activities in both academic and professional contexts -which have provided enrichment as well as acknowledgement, for this work-, have led to several publications, two high-impact journal papers and collateral work products of diverse nature