Optimised configuration of sensors for fault tolerant control of an electro-magnetic suspension system

For any given system the number and location of sensors can affect the closed-loop performance as well as the reliability of the system. Hence, one problem in control system design is the selection of the sensors in some optimum sense that considers both the system performance and reliability. Although some methods have been proposed that deal with some of the aforementioned aspects, in this work, a design framework dealing with both control and reliability aspects is presented. The proposed framework is able to identify the best sensor set for which optimum performance is achieved even under single or multiple sensor failures with minimum sensor redundancy. The proposed systematic framework combines linear quadratic Gaussian control, fault tolerant control and multiobjective optimisation. The efficacy of the proposed framework is shown via appropriate simulations on an electro-magnetic suspension system

Optimised configuration of sensors for fault tolerant control of an electro-magnetic suspension system

For any given system the number and location of sensors can affect the closed-loop performance as well as the reliability of the system. Hence, one problem in control system design is the selection of the sensors in some optimum sense that considers both the system performance and reliability. Although some methods have been proposed that deal with some of the aforementioned aspects, in this work, a design framework dealing with both control and reliability aspects is presented. The proposed framework is able to identify the best sensor set for which optimum performance is achieved even under single or multiple sensor failures with minimum sensor redundancy. The proposed systematic framework combines linear quadratic Gaussian control, fault tolerant control and multiobjective optimisation. The efficacy of the proposed framework is shown via appropriate simulations on an electro-magnetic suspension system

Optimised configuration of sensing elements for control and fault tolerance applied to an electro-magnetic suspension system

New technological advances and the requirements to increasingly abide by new safety laws in engineering design projects highly affects industrial products in areas such as automotive, aerospace and railway industries. The necessity arises to design reduced-cost hi-tech products with minimal complexity, optimal performance, effective parameter robustness properties, and high reliability with fault tolerance. In this context the control system design plays an important role and the impact is crucial relative to the level of cost efficiency of a product. Measurement of required information for the operation of the design control system in any product is a vital issue, and in such cases a number of sensors can be available to select from in order to achieve the desired system properties. However, for a complex engineering system a manual procedure to select the best sensor set subject to the desired system properties can be very complicated, time consuming or even impossible to achieve. This is more evident in the case of large number of sensors and the requirement to comply with optimum performance. The thesis describes a comprehensive study of sensor selection for control and fault tolerance with the particular application of an ElectroMagnetic Levitation system (being an unstable, nonlinear, safety-critical system with non-trivial control performance requirements). The particular aim of the presented work is to identify effective sensor selection frameworks subject to given system properties for controlling (with a level of fault tolerance) the MagLev suspension system. A particular objective of the work is to identify the minimum possible sensors that can be used to cover multiple sensor faults, while maintaining optimum performance with the remaining sensors. The tools employed combine modern control strategies and multiobjective constraint optimisation (for tuning purposes) methods. An important part of the work is the design and construction of a 25kg MagLev suspension to be used for experimental verification of the proposed sensor selection frameworks

Facilitating autonomous systems with AI-based fault tolerance and computational resource economy

Proposed is the facilitation of fault-tolerant capability in autonomous systems with particular consideration of low computational complexity and system interface devices (sensor/actuator) performance. Traditionally model-based fault-tolerant/detection units for multiple sensor faults in automation require a bank of estimators, normally Kalman-based ones. An AI-based control framework enabling low computational power fault tolerance is presented. Contrary to the bank-of-estimators approach, the proposed framework exhibits a single unit for multiple actuator/sensor fault detection. The efficacy of the proposed scheme is shown via rigorous analysis for several sensor fault scenarios for an electro-magnetic suspension testbed

Active suspension control of electric vehicle with in-wheel motors

In-wheel motor (IWM) technology has attracted increasing research interests in recent years due to the numerous advantages it offers. However, the direct attachment of IWMs to the wheels can result in an increase in the vehicle unsprung mass and a significant drop in the suspension ride comfort performance and road holding stability. Other issues such as motor bearing wear motor vibration, air-gap eccentricity and residual unbalanced radial force can adversely influence the motor vibration, passenger comfort and vehicle rollover stability. Active suspension and optimized passive suspension are possible methods deployed to improve the ride comfort and safety of electric vehicles equipped with inwheel motor. The trade-off between ride comfort and handling stability is a major challenge in active suspension design. This thesis investigates the development of novel active suspension systems for successful implementation of IWM technology in electric cars. Towards such aim, several active suspension methods based on robust H∞ control methods are developed to achieve enhanced suspension performance by overcoming the conflicting requirement between ride comfort, suspension deflection and road holding. A novel fault-tolerant H∞ controller based on friction compensation is in the presence of system parameter uncertainties, actuator faults, as well as actuator time delay and system friction is proposed. A friction observer-based Takagi-Sugeno (T-S) fuzzy H∞ controller is developed for active suspension with sprung mass variation and system friction. This method is validated experimentally on a quarter car test rig. The experimental results demonstrate the effectiveness of proposed control methods in improving vehicle ride performance and road holding capability under different road profiles. Quarter car suspension model with suspended shaft-less direct-drive motors has the potential to improve the road holding capability and ride performance. Based on the quarter car suspension with dynamic vibration absorber (DVA) model, a multi-objective parameter optimization for active suspension of IWM mounted electric vehicle based on genetic algorithm (GA) is proposed to suppress the sprung mass vibration, motor vibration, motor bearing wear as well as improving ride comfort, suspension deflection and road holding stability. Then a fault-tolerant fuzzy H∞ control design approach for active suspension of IWM driven electric vehicles in the presence of sprung mass variation, actuator faults and control input constraints is proposed. The T-S fuzzy suspension model is used to cope with the possible sprung mass variation. The output feedback control problem for active suspension system of IWM driven electric vehicles with actuator faults and time delay is further investigated. The suspended motor parameters and vehicle suspension parameters are optimized based on the particle swarm optimization. A robust output feedback H∞ controller is designed to guarantee the system’s asymptotic stability and simultaneously satisfying the performance constraints. The proposed output feedback controller reveals much better performance than previous work when different actuator thrust losses and time delay occurs. The road surface roughness is coupled with in-wheel switched reluctance motor air-gap eccentricity and the unbalanced residual vertical force. Coupling effects between road excitation and in wheel switched reluctance motor (SRM) on electric vehicle ride comfort are also analysed in this thesis. A hybrid control method including output feedback controller and SRM controller are designed to suppress SRM vibration and to prolong the SRM lifespan, while at the same time improving vehicle ride comfort. Then a state feedback H∞ controller combined with SRM controller is designed for in-wheel SRM driven electric vehicle with DVA structure to enhance vehicle and SRM performance. Simulation results demonstrate the effectiveness of DVA structure based active suspension system with proposed control method its ability to significantly improve the road holding capability and ride performance, as well as motor performance

AI-based actuator/sensor fault detection with low computational cost for industrial applications

A low computational cost method is proposed for detecting actuator/sensor faults. Typical model-based fault detection units for multiple sensor faults, require a bank of estimators (i.e., conventional Kalman estimators or artificial intelligence based ones). The proposed fault detection scheme uses an artificial intelligence approach for developing of a low computational power fault detection unit abbreviated as ‘iFD’. In contrast to the bank-of-estimators approach, the proposed iFD unit employs a single estimator for multiple actuator/sensor fault detection. The efficacy of the proposed fault detection scheme is illustrated through a rigorous analysis of the results for a number of sensor fault scenarios on an electromagnetic suspension system

Engineering assessment of current and future vehicle technologies: FMVSS no. 105 hydraulic and electric brake systems, FMVSS no. 135 passenger car brake systems; final report

This report provides a technical assessment of Federal Motor Vehicle Safety Standards (FMVSS) 105, Hydraulic and electric brake systems, and FMVSS 135, Passenger car brake systems. The review of these standards is part of a NHTSA’s Regulatory Review Plan to systematically examine all of the FMVSS. The primary thrust of the document is to address two questions: Do the current standards impede emerging technologies in passenger car and light/medium truck braking systems? Do the current standards require modification to adequately regulate emerging technologies? Emerging technologies are reviewed. Estimates of the extent and timing of their influence are made. It is concluded that the standards will not impede emerging technologies in the foreseeable future but could do so in the long term. The view is expressed that the approach of the current standards to ensuring adequate performance under partial-failure conditions may become ineffective as more, and more complex, automatic functions are added to automotive brake systems. A new approach may be required. Seventy-eight references are included in an annotated bibliography.National Highway Traffic Safety Administrationhttp://deepblue.lib.umich.edu/bitstream/2027.42/55414/1/99826.pd

Fault management via dynamic reconfiguration for integrated modular avionics

The purpose of this research is to investigate fault management methodologies within Integrated Modular Avionics (IMA) systems, and develop techniques by which the use of dynamic reconfiguration can be implemented to restore higher levels of systems redundancy in the event of a systems fault. A proposed concept of dynamic configuration has been implemented on a test facility that allows controlled injection of common faults to a representative IMA system. This facility allows not only the observation of the response of the system management activities to manage the fault, but also analysis of real time data across the network to ensure distributed control activities are maintained. IMS technologies have evolved as a feasible direction for the next generation of avionic systems. Although federated systems are logical to design, certify and implement, they have some inherent limitations that are not cost beneficial to the customer over long life-cycles of complex systems, and hence the fundamental modular design, i.e. common processors running modular software functions, provides a flexibility in terms of configuration, implementation and upgradability that cannot be matched by well-established federated avionic system architectures. For example, rapid advances of computing technology means that dedicated hardware can become outmoded by component obsolescence which almost inevitably makes replacements unavailable during normal life-cycles of most avionic systems. To replace the obsolete part with a newer design involves a costly re-design and re-certification of any relevant or interacting functions with this unit. As such, aircraft are often known to go through expensive mid-life updates to upgrade all avionics systems. In contrast, a higher frequency of small capability upgrades would maximise the product performance, including cost of development and procurement, in constantly changing platform deployment environments. IMA is by no means a new concept and work has been carried out globally in order to mature the capability. There are even examples where this technology has been implemented as subsystems on service aircraft. However, IMA flexible configuration properties are yet to be exploited to their full extent; it is feasible that identification of faults or failures within the system would lead to the exploitation of these properties in order to dynamically reconfigure and maintain high levels of redundancy in the event of component failure. It is also conceivable to install redundant components such that an IMS can go through a process of graceful degradation, whereby the system accommodates a number of active failures, but can still maintain appropriate levels of reliability and service. This property extends the average maintenance-free operating period, ensuring that the platform has considerably less unscheduled down time and therefore increased availability. The content of this research work involved a number of key activities in order to investigate the feasibility of the issues outlined above. The first was the creation of a representative IMA system and the development of a systems management capability that performs the required configuration controls. The second aspect was the development of hardware test rig in order to facilitate a tangible demonstration of the IMA capability. A representative IMA was created using LabVIEW Embedded Tool Suit (ETS) real time operating system for minimal PC systems. Although this required further code written to perform IMS middleware functions and does not match up to the stringent air safety requirements, it provided a suitable test bed to demonstrate systems management capabilities. The overall IMA was demonstrated with a 100kg scale Maglev vehicle as a test subject. This platform provides a challenging real-time control problem, analogous to an aircraft flight control system, requiring the calculation of parallel control loops at a high sampling rate in order to maintain magnetic suspension. Although the dynamic properties of the test rig are not as complex as a modern aircraft, it has much less stringent operating requirements and therefore substantially less risk associated with failure to provide service. The main research contributions for the PhD are: 1.A solution for the dynamic reconfiguration problem for assigning required systems functions (namely a distributed, real-time control function with redundant processing channels) to available computing resources whilst protecting the functional concurrency and time critical needs of the control actions. 2.A systems management strategy that utilises the dynamic reconfiguration properties of an IMA System to restore high levels of redundancy in the presence of failures. The conclusion summarises the level of success of the implemented system in terms of an appropriate dynamic reconfiguration to the response of a fault signal. In addition, it highlights the issues with using an IMA to as a solution to operational goals of the target hardware, in terms of design and build complexity, overhead and resources

High performance, direct drive machines for aerospace applications

For aerospace related electric systems, torque/force density, reliability and fault tolerance are of the utmost importance. A method by which high figures of reliability can be achieved is by eliminating any mechanical gearing or interconnection elements between the electrical machine and its mechanical load. This means that direct drive, electrical machines must be employed. However, to implement such solutions (without any mechanical advantages), electrical machines with excellent torque density (for rotational machines) and force density (for linear machines) performances are required. In this work, the main aim is to propose and investigate possible methods for extending and improving the torque/force density capabilities of high performance, state of the art, electrical machines (both rotational and linear). This is done in order to be able to meet the performance requirements while lacking the mechanical advantages synonymous with gearing and/or mechanical interconnections. Novel electro-magnetic and thermal management structures, detailed design and optimisation procedures for electrical machines are presented in this thesis. As vehicles to investigate these novel concepts, a tubular linear, permanent magnet motor and a rotational, synchronous permanent magnet motor are designed, built and experimentally tested. These machines which are both for aerospace related applications serve to show and validate the worthiness of the proposed, performance enhancement measures

Volume 3 – Conference

We are pleased to present the conference proceedings for the 12th edition of the International Fluid Power Conference (IFK). The IFK is one of the world’s most significant scientific conferences on fluid power control technology and systems. It offers a common platform for the presentation and discussion of trends and innovations to manufacturers, users and scientists. The Chair of Fluid-Mechatronic Systems at the TU Dresden is organizing and hosting the IFK for the sixth time. Supporting hosts are the Fluid Power Association of the German Engineering Federation (VDMA), Dresdner Verein zur Förderung der Fluidtechnik e. V. (DVF) and GWT-TUD GmbH. The organization and the conference location alternates every two years between the Chair of Fluid-Mechatronic Systems in Dresden and the Institute for Fluid Power Drives and Systems in Aachen. The symposium on the first day is dedicated to presentations focused on methodology and fundamental research. The two following conference days offer a wide variety of application and technology orientated papers about the latest state of the art in fluid power. It is this combination that makes the IFK a unique and excellent forum for the exchange of academic research and industrial application experience. A simultaneously ongoing exhibition offers the possibility to get product information and to have individual talks with manufacturers. The theme of the 12th IFK is “Fluid Power – Future Technology”, covering topics that enable the development of 5G-ready, cost-efficient and demand-driven structures, as well as individual decentralized drives. Another topic is the real-time data exchange that allows the application of numerous predictive maintenance strategies, which will significantly increase the availability of fluid power systems and their elements and ensure their improved lifetime performance. We create an atmosphere for casual exchange by offering a vast frame and cultural program. This includes a get-together, a conference banquet, laboratory festivities and some physical activities such as jogging in Dresden’s old town.:Group 8: Pneumatics Group 9 | 11: Mobile applications Group 10: Special domains Group 12: Novel system architectures Group 13 | 15: Actuators & sensors Group 14: Safety & reliabilit