Optimal Control Prediction Method for Control Allocation

This paper proposes a novel prediction method for online optimal control allocation that extends the volume of moments achievable with the Moore-Penrose generalized inverse to the entire Attainable Moment Set. This method formulates the control allocation problem using selected basis vectors and associated gains which reduces the optimization problem dimensions and provides physical insight into the resulting optimal solutions. The proposed algorithm finds the entire family of unique optimal control solutions along the desired moment vector from the origin to the boundary of the Attainable Moment Set. Numerical results for the Moore-Penrose prediction method show that the unique minimal controls obtained yield the desired moment with near machine precision accuracy while maintaining control effectors within specified position limits. This method has been fully validated against the unique solution obtained on the boundary of the Attainable Moment Set using the Durham Direct Allocation method. Minimal control solutions obtained for moments in the interior of the Attainable Moment Set, similarly yield the desired moment to near machine precision while providing control solutions that are smaller (i.e. 2-norm) than solutions found with traditional control allocation algorithms (e.g. interior point methods) applied to the minimal control problem. Numerical simulations using a Matlab autocoded executable (MEX) for the representative real world problem of 3-moments with 20 individual control effectors and prescribed control position limits show a mean computation speed of approximately 125 Hz which is sufficient to enable real-time flight allocation

Power loss minimization in electric cars by wheel force allocation

The need for lowering the emission levels has never been greater than now. In the vehicle industry, electrification seems to be an irreversible way ahead but user-related challenges such as limited range delay electricity as the primary energy source for personal transportation. Other control-related challenges are also introduced as electric cars are over-actuated, i.e. several actuators can be used for the same purpose. Over-actuation introduces the possibility to choose more freely which actuator to use when. Can this freedom of choice be used to improve energy efficiency of electric cars by e.g. minimizing power losses? In this thesis, two wheel force distribution algorithms have been developed with a method called control allocation. The algorithms minimize power losses in the electric drivetrain, transmission and tires. They were tested in a simulated city cycle in a Volvo V60 configuration with four electric motors, each connected to a wheel through a single speed transmission and coupling respectively. It was found that by using developed algorithms, up to 3.9% energy could be saved. In a next step, the transmission ratio on the front motors and rear motors were optimized in combination with one of the algorithms. By using a larger transmission ratio in the front than in the rear, the energy consumption reduced even further. With these development steps, up to 7.9% energy could be saved compared to the original vehicle

High-Efficiency Thrust Vector Control Allocation

A generalized approach to the allocation of redundant thrust vector slew commands for multi-actuated launch vehicles is presented, where deflection constraints are expressed as omniaxial or elliptical deflection limits in gimbal axes. More importantly than in the aircraft control allocation problem, linear allocators (pseudoinverses) are preferred for large booster applications to facilitate accurate prediction of the control-structure interaction resulting from thrust vectoring effects. However, strictly linear transformations for the allocation of redundant controls cannot, in general, access all of the attainable moments for which there is a set of control effector positions thatsatisfles the constraints. In this paper, the control allocation efficiency ora certain class of linear allocators subject to multiple quadratic constraints is analyzed, and a novel single-pass control allocation scheme is proposed that augments the pseudolnverse near the boundary of the attainable set. The controls are determined over a substantial volume of lhe attainable set using only a linear transformation; as such, the algorithm maintains compatibility with frequencydomain approaches to the analysis of the vehicle closed-loop elastic stability. Numerical results using a model of a winged reusable booster system illustrate the proposed technique\u27s ability to access a larger Fraction of the attainable set than a pseudoinverse alone

Optimal fault-tolerant flight control for aircraft with actuation impairments

Current trends towards greater complexity and automation are leaving modern technological systems increasingly vulnerable to faults. Without proper action, a minor error may lead to devastating consequences. In flight control, where the controllability and dynamic stability of the aircraft primarily rely on the control surfaces and engine thrust, faults in these effectors result in a higher extent of risk for these aspects. Moreover, the operation of automatic flight control would be suddenly disturbed. To address this problem, different methodologies of designing optimal flight controllers are presented in this thesis. For multiple-input multiple-output (MIMO) systems, the feedback optimal control is a prominent technique that solves a multi-objective cost function, which includes, for instance, tracking requirements and control energy minimisation. The first proposed method is based on a linear quadratic regulator (LQR) control law augmented with a fault-compensation scheme. This fault-tolerant system handles the situation in an adaptive way by solving the optimisation cost function and considering fault information, while assuming an effective fault detection system is available. The developed scheme was tested in a six-degrees-of-freedom nonlinear environment to validate the linear-based controller. Results showed that this fault tolerant control (FTC) strategy managed to handle high magnitudes of the actuator’s loss of effciency faults. Although the rise time of aircraft response became slower, overshoot and settling errors were minimised, and the stability of the aircraft was maintained. Another FTC approach has been developed utilising the features of controller robustness against the system parametric uncertainties, without the need for reconfiguration or adaptation. Two types of control laws were established under this scheme, the H∞ and µ-synthesis controllers. Both were tested in a nonlinear environment for three points in the flight envelope: ascending, cruising, and descending. The H∞ controller maintained the requirements in the intact case; while in fault, it yielded non-robust high-frequency control surface deflections. The µ-synthesis, on the other hand, managed to handle the constraints of the system and accommodate faults reaching 30% loss of effciency in actuation. The final approach is based on the control allocation technique. It considers the tracking requirements and the constraints of the actuators in the design process. To accommodate lock-in-place faults, a new control effort redistribution scheme was proposed using the fuzzy logic technique, assuming faults are provided by a fault detection system. The results of simulation testing on a Boeing 747 multi-effector model showed that the system managed to handle these faults and maintain good tracking and stability performance, with some acceptable degradation in particular fault scenarios. The limitations of the controller to handle a high degree of faults were also presented

Control of an over-actuated nanopositioning system by means of control allocation

This Master’s Thesis is devoted to the analysis and design of a control structure for the nanopositioning system LAU based on the dynamic control allocation technique. The objective is to control the vertical displacement with nanometer precision under a control effort distribution criterion among the actuator set. In this case, the pneumatic actuator is used as a passive gravity compensator while the voice coil motor generates the transient forces. The analysis of the system characteristics allows defining the design criterion for the control allocation. In this direction, the proposed dynamic control allocation stage considers a frequency distribution of the control effort. The lower frequency components are assigned to the pneumatic actuator while the higher frequencies are handled by the voice coil drive. The significant actuator dynamics are compensated through a Kalman filter approach. The position controller is based on a feedback linearization framework with a disturbance observer for enhanced robustness. The experimental validation demonstrates the feasibility of the proposed technique.Diese Masterarbeit widmet sich der Analyse und dem Entwurf einer Regelungsstruktur für das Nanopositioniersystem LAU. Dabei werden Methoden untersucht, welche das notwendige Stellsignal auf zwei Aktoren aufteilen. Ziel ist es, die vertikale Verschiebung des LAU mit Nanometerpräzision zu regeln. In diesem Fall wird der pneumatische Aktor als passiver Schwerkraftkompensator verwendet, während die elktromagnetische Tauchspule die transienten Kräfte erzeugt. Die Analyse der Eigenschaften des LAUSystems ermöglicht die Definition der Entwurfskriterien zur Aufteilung der Stellgröße. In dieser Richtung berücksichtigt die vorgeschlagene dynamische Methode eine Aufteilung der Stellgröße bezüglich der Frequenzanteile. Die niederfrequenten Komponenten werden dem pneumatischen Aktor zugeordnet. Dem elektromagnetische Aktor werden die verbliebenen hochfrequenten Anteile zugeordnet. Die signifikanten Effekte der Aktordynamik in Bezug auf die Bewegungsdynamik werden durch einen Kalman- Filteransatz kompensiert. Nichtlineare Streckenanteile werden basierend auf dem Modell und einem Störbeobachter kompensiert, sodass der verbleibende Anteil des Positionsreglers mit linearen Methoden entworfen werden kann. Die experimentelle Validierung zeigt die Effektivität des untersuchten Konzeptes.Tesi

Parallel Load Balancing Strategies for Ensembles of Stochastic Biochemical Simulations

The evolution of biochemical systems where some chemical species are present with only a small number of molecules, is strongly influenced by discrete and stochastic effects that cannot be accurately captured by continuous and deterministic models. The budding yeast cell cycle provides an excellent example of the need to account for stochastic effects in biochemical reactions. To obtain statistics of the cell cycle progression, a stochastic simulation algorithm must be run thousands of times with different initial conditions and parameter values. In order to manage the computational expense involved, the large ensemble of runs needs to be executed in parallel. The CPU time for each individual task is unknown before execution, so a simple strategy of assigning an equal number of tasks per processor can lead to considerable work imbalances and loss of parallel efficiency. Moreover, deterministic analysis approaches are ill suited for assessing the effectiveness of load balancing algorithms in this context. Biological models often require stochastic simulation. Since generating an ensemble of simulation results is computationally intensive, it is important to make efficient use of computer resources. This paper presents a new probabilistic framework to analyze the performance of dynamic load balancing algorithms when applied to large ensembles of stochastic biochemical simulations. Two particular load balancing strategies (point-to-point and all-redistribution) are discussed in detail. Simulation results with a stochastic budding yeast cell cycle model confirm the theoretical analysis. While this work is motivated by cell cycle modeling, the proposed analysis framework is general and can be directly applied to any ensemble simulation of biological systems where many tasks are mapped onto each processor, and where the individual compute times vary considerably among tasks

Health-aware and fault-tolerant control of an octorotor UAV system based on actuator reliability

A major goal in modern flight control systems is the need for improving reliability. This work presents a health-aware and fault-tolerant control approach for an octorotor UAV that allows distributing the control effort among the available actuators based on their health information. However, it is worth mentioning that, in the case of actuator fault occurrence, a reliability improvement can come into conflict with UAV controllability. Therefore, system reliability sensitivity is redefined and modified to prevent uncontrollable situations during the UAV’s mission. The priority given to each actuator is related to its importance in system reliability. Moreover, the proposed approach can reconfigure the controller to compensate actuator faults and improve the overall system reliability or delay maintenance tasks.Peer ReviewedPostprint (published version

Robust fault tolerant control allocation for a modern over‐actuated commercial aircraft

This is the final version. Available on open access from Wiley via the DOI in this recordThis paper presents a novel form of control allocation, designed within a sliding mode framework, for the fault tolerant control of over-actuated systems. The control allocation is designed in such a way as to allow a subset of the actuators to remain inactive under nominal fault-free conditions. In the event that the active set of actuators becomes unable to provide the desired performance, an adaption process takes place which allows the inactive actuators to compensate. A computationally light gradient descent algorithm is proposed to govern the adaption which guarantees that, if possible, actuator saturation is avoided and system performance is maintained - even in the event of severe actuator faults and failures. Rigorous conditions are derived, in terms of the faults/failures, uncertainties in fault reconstruction information and the adaptive process, which ensures sliding occurs in a finite time and that the resulting motion is stable. To demonstrate the effectiveness of the control scheme, a highfidelity blended wing body aircraft model is also proposed in this paper; this particular configuration of aircraft is nominally unstable, with poor control authority and a large amount of redundancy - making it a suitable candidate for testing reconfigurable fault tolerant control laws in the presence of input constraints.University of Exete