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

Research on optimal control, stabilization and computational algorithms for aerospace applications

The research carried out in the areas of optimal control and estimation theory and its applications under this grant is reviewed. A listing of the 257 publications that document the research results is presented

Distributed infinite-horizon optimal control of continuous-time linear systems over network

This article deals with the distributed infinite-horizon linear-quadratic-Gaussian optimal control problem for continuous-time systems over networks. In particular, the feedback controller is composed of local control stations, which receive some measurement data from the plant process and regulates a portion of the input signal. We provide a solution when the nodes have information on the structural data of the whole network but takes local actions, and also when only local information on the network are available to the nodes. The proposed solution is arbitrarily close to the optimal centralized one (in terms of cost index) when a design parameter is set sufficiently large. Numerical simulation validate the theoretical results

Comprehensive review on controller for leader-follower robotic system

985-1007This paper presents a comprehensive review of the leader-follower robotics system. The aim of this paper is to find and elaborate on the current trends in the swarm robotic system, leader-follower, and multi-agent system. Another part of this review will focus on finding the trend of controller utilized by previous researchers in the leader-follower system. The controller that is commonly applied by the researchers is mostly adaptive and non-linear controllers. The paper also explores the subject of study or system used during the research which normally employs multi-robot, multi-agent, space flying, reconfigurable system, multi-legs system or unmanned system. Another aspect of this paper concentrates on the topology employed by the researchers when they conducted simulation or experimental studies

An adaptive type-2 fuzzy sliding mode tracking controller for a robotic manipulator

With the wide application of intelligent manufacturing and the development of diversified functions of industrial manipulator, the requirements for the control accuracy and stability of the manipulator servo system are also increasing. The control of industrial manipulator is a time-varying system with nonlinear and strong coupling, which is often affected by uncertain factors, including parameter changing, environmental interference, joint friction and so on. Aiming at the problem of the poor control accuracy of the manipulator. Under the complex disturbance environment, control accuracy of the manipulator will be greatly affected, so this paper proposes an adaptive type-2 fuzzy sliding mode control (AT2FSMC) method applied to the servo control of the industrial manipulator, which realizes the adaptive adjustment of the boundary layer thickness to suppress the trajectory error caused by the external disturbance and weakens the chattering problem of the sliding mode control. The simulation results on a two-axis manipulator indicate that, with the presence of external disturbances, the proposed control method can help the manipulator maintain control signal stability and improve tracking accuracy. It also suppressed chattering produced by sliding mode control (SMC) and strengthening the robustness of the system. Compared with other conventional trajectory tracking control methods, the effectiveness of the proposed method can be reflected. Finally, the proposed method is tested in an actual manipulator to complete a practical trajectory to prove its feasibility

Interval Sliding Mode Observer based Fault Accommodation for Non-minimum Phase LPV Systems with Online Control Allocation

This paper proposes an interval sliding mode observer (ISMO) based sliding mode actuator fault accommodation (FA) framework for non-minimum phase linear-parameter-varying (LPV) systems involving online control allocation (CA) problem. Firstly, a specifically designed coordinate transformation is introduced to deal with the non-minimum phase issue. Then, for the transformed system, an ISMO is proposed to estimate the set of admissible values for the states of the faulty LPV systems. It is constructed based on the designed interval bounds for the scheduling-parameter-related uncertainties and fault-related items. The observer is designed by combining the interval observer and the sliding mode observer techniques. A fault-tolerant control (FTC) law with an online CA scheme is subsequently designed by stabilizing the proposed ISMO instead of the original faulty LPV system, which guarantees that the unmeasurable states of the original LPV system converge to zero asymptotically, the measurable outputs converge to zero in finite time, and further, the actual control efforts are allocated to all actuators optimally and satisfy prescribed performance. Finally, a simulation based on the inverter used in China Railway High-speed (CRH) is presented to illustrate the effectiveness of the proposed framework

Advanced Mathematics and Computational Applications in Control Systems Engineering

Control system engineering is a multidisciplinary discipline that applies automatic control theory to design systems with desired behaviors in control environments. Automatic control theory has played a vital role in the advancement of engineering and science. It has become an essential and integral part of modern industrial and manufacturing processes. Today, the requirements for control precision have increased, and real systems have become more complex. In control engineering and all other engineering disciplines, the impact of advanced mathematical and computational methods is rapidly increasing. Advanced mathematical methods are needed because real-world control systems need to comply with several conditions related to product quality and safety constraints that have to be taken into account in the problem formulation. Conversely, the increment in mathematical complexity has an impact on the computational aspects related to numerical simulation and practical implementation of the algorithms, where a balance must also be maintained between implementation costs and the performance of the control system. This book is a comprehensive set of articles reflecting recent advances in developing and applying advanced mathematics and computational applications in control system engineering

Fault tolerant strategy for actively controlled railway wheelset

Traditionally, solid axle railway wheelsets are stabilised by using passive suspensions on a conventional rail vehicle, but such additional stiffness affects the pure rolling action of the wheelset around the curve. It has been theoretically proven that this design conflict between stability and curving performance can be solved by applying active control instead of conventional passive components, resulting in the reduction of the wear of the wheels and track by minimising the track shifting forces. In the active approach, the use of actuators, sensors and data processors to replace the traditional passive suspension raises the issue of the system safety in the event of a failure of the active control, which could result in the loss of stability and in more severe cases, derailment. Further on, in active control systems for railway vehicles the actuators tend to be significantly more expensive and require more additional space than sensors, and an electronic control unit. Therefore, developing an analytical redundancy-based fault tolerance technique for an actively controlled wheelset that minimises the number of actuators will clearly be more beneficial. Thus the emphasis of this research is to develop a fault-tolerant system of active control for a railway vehicle in the event of actuator malfunction in order to guarantee stability and good curving performance without using additional actuators. The key achievements of this research can be summarised as follows: •The research considers three of the most common types of actuator failure for the electro-mechanical actuators: fail-hard (FH), short circuit (SC) and open circuit (OC). The fail-hard is a failure condition when the motor shaft of the actuator becomes immovable, whereas the short circuit and open circuit are failures that occur in the electrical parts of the actuator which correspond to zero voltage and zero current in the motor respectively.•The research investigates and develops a thorough understanding of the effect of actuator faults and failure modes on the vehicle behaviour that provides the necessary foundation for the development of the proposed fault-tolerant strategy.•An effective fault detection and isolation methods for actuator faults through two different approaches is developed; the vehicle model-based approach and the actuator model-based approach. Additionally, the research takes into account the reliability and robustness of the FDI schemes in the presence of sensor failures and parameter uncertainties in the system. •The research develops the control re-configuration in order to cope with the identified failure mode of the actuator in order to maintain the vehicle stability and desired curving performance

Passive attack detection for a class of stealthy intermittent integrity attacks

This paper proposes a passive methodology for detecting a class of stealthy intermittent integrity attacks in cyber-physical systems subject to process disturbances and measurement noise. A stealthy intermittent integrity attack strategy is first proposed by modifying a zero-dynamics attack model. The stealthiness of the generated attacks is rigorously investigated under the condition that the adversary does not know precisely the system state values. In order to help detect such attacks, a backward-in-time detection residual is proposed based on an equivalent quantity of the system state change, due to the attack, at a time prior to the attack occurrence time. A key characteristic of this residual is that its magnitude increases every time a new attack occurs. To estimate this unknown residual, an optimal fixed-point smoother is proposed by minimizing a piece-wise linear quadratic cost function with a set of specifically designed weighting matrices. The smoother design guarantees robustness with respect to process disturbances and measurement noise, and is also able to maintain sensitivity as time progresses to intermittent integrity attack by resetting the covariance matrix based on the weighting matrices. The adaptive threshold is designed based on the estimated backward-in-time residual, and the attack detectability analysis is rigorously investigated to characterize quantitatively the class of attacks that can be detected by the proposed methodology. Finally, a simulation example is used to demonstrate the effectiveness of the developed methodology