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The High Redundancy Actuator project deals with the construction of an actuator using many redundant actuation elements. Whilst this promises a high degree of fault tolerance, the high number of components poses a unique challenge from a control perspective, especially when actuation elements are used in series.\ud This paper describes how an adaptive control scheme can be used to deal with faults in a High Redundancy Actuator. This is based on previous results leading to a simplified model of the HRA with serial elements. In case of the fault, the parameters change, but the otherwise the deviation from the simplified model is minimal.\ud This approach has two benefits. For one, it can restore the original system dynamics even after a fault has occurred. The parameter estimate can also be used for health monitoring purposes, because it reflects the number of effective faults in the HRA.

The High Redundancy Actuator (HRA) project deals with the construction of an actuator using many redundant actuation elements. If one element fails, this changes the behaviour slightly, but the system still remains operation. A key challenge in this project is to design a passive fault tolerant controller that maintains the required performance in the presence of faults. This paper shows how to achieve this with structurally simple controllers, by optimising the parameters using a genetic algorithm.

The aim of this paper is to summarise on-going research into a new method of providing fault tolerant actuators for high-integrity and/or safety-critical applications. The High Redundancy Actuator (HRA) project aims to exploit a large number of very small actuation elements to make up a single large actuator. This is in contrast to current technology where a relatively low level of functional redundancy is used. The HRA elements are configured and controlled in such a way that faults in individual elements are inherently accommodated without resulting in a failure of the complete actuation system. The HRA project research challenges are outlined and progress to-date is discussed.

A high redundancy actuator (HRA) is composed of a high number of actuation elements, increasing both the travel and the force over the power of an individual element. This provides inherent fault tolerance, because when an element fails, the capabilities of the actuator may be reduced, but it does not become dysfunctional. This paper analyses the likelihood of different reductions in capabilities, based on the reliability of the actuation elements used. The result is a probability distribution that quantifies the capability of the high redundancy actuator. Together with the required capabilities, this determines the fault tolerance of the actuator.

This paper discusses a systematic approach for selecting the minimum number of sensors for an Electromagnetic levitation system that satisfies both deterministic and stochastic performance objectives. The controller tuning is based upon the utilisation of a recently developed genetic algorithm, namely NSGAII. Two controller structures are discussed, an inner loop classical solution for illustrating the efficacy of the NSGAII tuning and a Linear quadratic gaussian structure particularly on sensor optimization.

This paper presents the modelling of a moving coil actuator for use as an element in a High Redundancy Actuator (HRA). A single element model is derived from first principles and verified using experimental data. This model is subsequently used to describe an approach to deriving models of multi-element HRAs and determine the effect of a variety of faults, chosen to be appropriate for the electro-magnetic technology, on the behaviour of multi-element assemblies.

Input-Output selection/placement for control systems has been an attractive research topic in particular under fault-free conditions. In this paper we present a methodology of output selection in a closed-loop framework with a view of fault tolerance capability. The principles with regards to the selection of sensors are reduced hardware redundancy, reduced costs and easier implementation, and acceptable degraded performance when faults occur. The selection of sensors is based upon both closed-loop control and fault tolerance objectives by solving an H1 optimization problem for each group of sensors sets via Linear Matrix Inequalities (LMIs). The proposed scheme is applied to a practical example of ride quality improvement of a high speed rail vehicle.

This paper present work on modern control approaches in titling railway vehicles. The design of the Linear Quadratic Gaussian with integral action controller provides the required tilt compensation, while the addition of the fuzzy mechanism to the controller improves the system performance both for the deterministic and stochastic track. Moreover, the use of multiobjective GA as a tuning method seeks an optimum value based on the imposed constraints in the objective functions.

The paper discusses on the use of an optimal LQG control design to improve the vehicle curving performance at increased running speed, employing only local (rail vehicle-based) signal measurements. It addresses the fundamental problem related with straightforward feedback control, and introduces the commercially-used command-driven with precedence scheme. A combination of simulation results and, a recently proposed, tilt control system assessment method are utilised for assessing the overall performance of the tilt controller.