Johannes Tjønnås

Stabilization of Automotive Vehicles Using Active Steering and Adaptive Brake Control Allocation

In this work a dynamic control allocation approach is presented for an automotive vehicle yaw stabilization scheme. The stabilization strategy consists of a high level module that deals with the vehicle motion control objective (yaw rate reference generation and tracking), a low level module that handles the braking control for each wheel (longitudinal slip control and maximal tire-road friction parameter estimation), and an intermediate level dynamic control allocation module that generates the longitudinal slip reference for the low level brake control module and commands front wheel steering angle corrections. The control allocation design is such that the actual torque about the yaw axis tends to the desired torque calculated form the high level module, with desirable distribution of control forces satisfying actuator constraints and minimal control effort objectives. Conditions for uniform asymptotic stability are given for the case when the control allocation includes adaptation of the tire-road maximal friction coefficients, and the scheme has been implemented in a realistic non linear multi body vehicle simulation environment. The simulation cases show that the yaw control allocation strategy stabilizes the vehicle in extreme maneuvers where the non linear vehicle yaw dynamics otherwise (without active braking or active steering) becomes unstable in the sense of over- or under steering. The control allocation implementation is efficient and suitable for low cost automotive electronic control units.

Adaptive control allocation

In this work we address the control allocation problem for a nonlinear over-actuated time-varying system where parameters affine in the effector model may be assumed unknown. Instead of optimizing the control allocation at each time instant, a dynamic approach is considered by constructing update-laws that represent asymptotically optimal allocation search and adaptation. Using Lyapunov analysis for cascaded set-stable systems, uniform global/local asymptotic stability is guaranteed for the sets described by the system, the optimal allocation update-law and the adaptive update-law.

Optimizing adaptive control allocation with actuator dynamics

In this work we address the optimizing control allocation problem for an over-actuated nonlinear time-varying system with actuator dynamic where parameters affine in the actuator and effector model may be assumed unknown. Instead of optimizing the control allocation at each time instant, a dynamic approach is considered by constructing actuator reference update-laws that represent an asymptotically optimal allocation search. By using Lyapunov analysis for cascaded set- stable systems, uniform global/local asymptotic stability is guaranteed for the optimal equilibrium sets described by the system, the control allocation update-law and the adaptive update-law, if some persistence of exitation condition holds. Simulations of a scaled-model ship, manoeuvred at low-speed, demonstrate the performance of the proposed allocation scheme.

ON OPTIMIZING NONLINEAR ADAPTIVE CONTROL ALLOCATION WITH ACTUATOR DYNAMICS

Abstract In this work we address the optimizing control allocation problem for a nonlinear over-actuated time-varying system where parameters affine in the dynamic actuator and effector model may be assumed unknown. In-stead of finding the optimal control allocation at each time instant, a dynamic approach is considered by constructing update-laws that represent asymptotically optimal allocation search and adaptation. Using Lyapunov analysis for cascaded set-stable systems, uniform global/local asymptotic stability is guaranteed for the optimal set described by the system, the optimal allocation update-law and the adaptive update-law. Simulations of a scaled-model ship, manoeuvred at low-speed, demonstrate the performance of the proposed allocation scheme.

Integration of vehicle yaw stabilisation and rollover prevention through nonlinear hierarchical control allocation

This work presents an approach to rollover prevention that takes advantage of the modular structure and optimisation properties of the control allocation paradigm. It eliminates the need for a stabilising roll controller by introducing rollover prevention as a constraint on the control allocation problem. The major advantage of this approach is the control authority margin that remains with a high-level controller even during interventions for rollover prevention. In this work, the high-level control is assigned to a yaw stabilising controller. It could be replaced by any other controller. The constraint for rollover prevention could be replaced by or extended to different control objectives. This work uses differential braking for actuation. The use of additional or different actuators is possible. The developed control algorithm is computationally efficient and suitable for low-cost automotive electronic control units. The predictive design of the rollover prevention constraint does not require any sensor equipment in addition to the yaw controller. The method is validated using an industrial multi-body vehicle simulation environment.

OPTIMIZING NONLINEAR ADAPTIVE CONTROL ALLOCATION

Abstract A control-Lyapunov approach is used to develop an adaptive optimizing control allocation algorithm for over-actuated mechanical systems where the actuator model is affine in the uncertain parameters. Uniform global (asymptotic) stability is guaranteed by the control allocation defined by the dynamic update laws in combination with an exponentially stable controller.

Well Testing by Sinusoidal Stimulation

A new approach to testing of oil and gas wells by means of sinusoidal oscillations in flow and pressure instead of the traditional buildup test is proposed in this article. This approach allows faster testing and simultaneous testing of several wells, with no need for a dedicated test header; it can also be adjusted to strike an appropriate compromise between measurement precision and production loss. This study details various operating issues such as generation of input signals, choice of test frequencies, applicability, and interpretation of results. To demonstrate the method, both a synthetic test and several field tests are presented.

Cascade lemma for set-stable systems

A previous result about uniform global asymptotic stability (UGAS) of the equilibrium of a cascaded time-varying systems, is here also shown to hold for closed (not necessarily compact) sets composed by set-stable subsystems of a cascade. In view of this result an optimal control allocation approach is discussed

Automatic Classification of Sub-Techniques in Classical Cross-Country Skiing Using a Machine Learning Algorithm on Micro-Sensor Data

The automatic classification of sub-techniques in classical cross-country skiing provides unique possibilities for analyzing the biomechanical aspects of outdoor skiing. This is currently possible due to the miniaturization and flexibility of wearable inertial measurement units (IMUs) that allow researchers to bring the laboratory to the field. In this study, we aimed to optimize the accuracy of the automatic classification of classical cross-country skiing sub-techniques by using two IMUs attached to the skier’s arm and chest together with a machine learning algorithm. The novelty of our approach is the reliable detection of individual cycles using a gyroscope on the skier’s arm, while a neural network machine learning algorithm robustly classifies each cycle to a sub-technique using sensor data from an accelerometer on the chest. In this study, 24 datasets from 10 different participants were separated into the categories training-, validation- and test-data. Overall, we achieved a classification accuracy of 93.9% on the test-data. Furthermore, we illustrate how an accurate classification of sub-techniques can be combined with data from standard sports equipment including position, altitude, speed and heart rate measuring systems. Combining this information has the potential to provide novel insight into physiological and biomechanical aspects valuable to coaches, athletes and researchers.

Control Structure of a Micro Combined Heat and Power Fuel-Cell System for Lifetime Maximisation

The aim of this work is how to analyse controllability and design a suitable control structure for a commercial stationary micro combined heat and power system (\mchp) where the focus is to optimise the life time of the fuel cell, which is the central component in the system and the most critical with respect to durability. A three-layered control approach is proposed, building on the pre-existing low-level regulatory layer. A middle-level controller handles reversible degradation phenomena before they cause lasting damage, inducing temporary deviations from the steady state to recover from e.g. catalyst contamination or electrode flooding. A high-level optimising controller sets the nominal operating conditions to maximise a specific objective function, based on prognostics and health management, in which the lifetime of the stack is of pivotal importance.