One-shot data-driven design of fractional-order PID controller considering closed-loop stability: fictitious reference signal approach

A one-shot data-driven tuning method for a fractional-order proportional-integral-derivative (FOPID) controller is proposed. The proposed method tunes the FOPID controller in the model-reference control formulation. A loss function is defined to evaluate the match between a given reference model and the closed-loop response while explicitly considering the closed-loop stability. A loss function value is based on the fictitious reference signal computed using the input/output data. Model matching is achieved via loss function minimization. The proposed method is simple and practical: it needs only one-shot input/output data of a plant (no plant model required), considers the bounded-input bounded-output stability of the closed-loop system, and automatically determines the appropriate parameter value via optimization. Numerical simulations show that the proposed approach facilitates good control performance, and destabilization can be avoided even if perfect model matching is unachievable

Optimized state feedback regulation of 3DOF helicopter system via extremum seeking

In this paper, an optimized state feedback regulation of a 3 degree of freedom (DOF) helicopter is designed via extremum seeking (ES) technique. Multi-parameter ES is applied to optimize the tracking performance via tuning State Vector Feedback with Integration of the Control Error (SVFBICE). Discrete multivariable version of ES is developed to minimize a cost function that measures the performance of the controller. The cost function is a function of the error between the actual and desired axis positions. The controller parameters are updated online as the optimization takes place. This method significantly decreases the time in obtaining optimal controller parameters. Simulations were conducted for the online optimization under both fixed and varying operating conditions. The results demonstrate the usefulness of using ES for preserving the maximum attainable performance

Optimization of System Identification for Multi-Rail DC-DC Power Converters

Ph. D. Thesis.There have been many recursive algorithms investigated and introduced in real time parameter estimation of Switch Mode Power Converters (SMPCs) to improve estimation performance in terms of faster convergence speed, lower computational cost and higher estimation accuracy. These algorithms, including Dichotomous Coordinate Descent (DCD) - Recursive Least Square (RLS), Kalman Filter (KF) and Fast Affine Projection (FAP), etc., are commonly applied for performance comparison of system identification of single-rail power converters. When they need to be used in multi-rail architectures with a single centralized controller, the computational burden on the processor becomes significant. Typically, the computational effort is directly proportional to the number of converters/rails. This thesis presents an iterative decimation approach to significantly alleviate the computational burden of centralized controllers applying real-time recursive system identification algorithms in multirail power converters. The proposed approach uses a flexible and adjustable update rate rather than a fixed rate, as opposed to conventional adaptive filters. In addition, the step size/forgetting factors are varied, as well, corresponding to different iteration stages. As a result, reduced computational burden and faster model update can be achieved. Recursive algorithms, such as Recursive Least Square (RLS), Affine Projection (AP) and Kalman Filter (KF), contain two important updates per iteration cycle. Covariance Matrix Approximation (CMA) update and the Gradient Vector (GV) update. Usually, the computational effort of updating Covariance Matrix Approximation (CMA) requires greater computational effort than that of updating Gradient Vector (GV). Therefore, in circumstances where the sampled data in the regressor does not experience significant fluctuations, re-using the Covariance Matrix Approximation (CMA), calculated from the last iteration cycle for the current update can result in computational cost savings for real- time system identification. In this thesis, both iteration rate adjustment and Covariance Matrix Approximation (CMA) re-cycling are combined and applied to simultaneously identify the power converter model in a three-rail power conversion architecture. Besides, in multi-rail architectures, due to the high likelihood of the at-the-same-time need for real time system identification of more than one rail, it is necessary to prioritize each rail to guarantee rails with higher priority being identified first and avoid jam. In the thesis, a workflow, which comprises sequencing rails and allocating system identification task into selected rails, was proposed. The multi-respect workflow, featured of being dynamic, selectively pre-emptive, cost saving, is able to flexibly change ranks of each rail based on the application importance of rails and the severity of abrupt changes that rails are suffering to optimize waiting time and make-span of rails with higher priorities

Design and fabrication of a system for the additive manufacturing of transparent glass

Despite glass\u27 prevalence in the scientific and engineering community, very little research has been conducted attempting to additively manufacture (AM) glass. Even less research has been done on optically transparent glass. Glass’ material properties make it ineligible for most AM processes if the end result is to be transparent. Even small gas inclusions can cause large amounts of scattering. Additively manufacturing transparent glass brings the advantages found in other AM processes with the added benefit of having optical properties better than those found in polymers. Additively manufacturing glass also allows the optical properties of transparent parts to vary arbitrarily. This thesis presents the design, manufacture, and control of a system to AM transparent glass. The system feeds glass wires, which are opaque in the near infrared, into a melt pool maintained by a CO₂ laser (10.6μm). The laser beam and melt pool remained fixed as the AM part is moved using a motion stage as the glass is deposited layer-by-layer. The stages are controlled using a PID controller, and the wire feeders are controlled using a PD controller. A spring damper model is also presented to model the deposition process along the feed direction, and perpendicular to the feed direction for control purposes. The Glass AM process is able to create morphologically accurate glass pieces more efficiently, and with fewer filament breakages than the prototype system. The glass produced with this system has optical properties as good as cast glass. The Glass AM system is also expandable and interchangeable so that more subsystems can be added and changed with minimal redesign --Abstract, page iii

Advanced control for floating offshore wind turbines.

El contenido de los capítulos 3, 4 y 5 está sujeto a confidencialidad. 117 p.os aerogeneradores flotantes presentan diversos retos tecnológicos, entre los cuales, las atenuaciones de la dinámica producida por el empuje del viento y la inducida por el oleaje, debido a la baja rigidez hidrodinámica de la plataforma, son vitales. Estas dinámicas no solo influyen en el funcionamiento normal del aerogenerador, sino que además, incrementan las cargas mecánicas de algunos componentes, como la torre y palas del aerogenerador. Por ello, el objetivo de esta tesis es minimizar las dinámicas de los aerogeneradores flotantes, mejorando el funcionamiento a la vez que se reducen las cargas mecánicas producidas en la torre y palas mediante técnicas de control avanzadas, y así, aumentar la eficiencia del aerogenerador y prolongar la vida útil de dichos componentes.La descripción del trabajo incluye el modelado de plataformas flotantes y el desarrollo de dos lazos de control, que respectivamente realimentan la velocidad de la góndola y los momentos flectores en las raíces de las palas, para la contribución en la regulación del ángulo de pitch de las palas del aerogenerador. Además, se estudia la relación de las dimensiones de las plataformas flotantes y el desempeño del controlador diseñado con el fin de reducir las dimensiones de la plataforma manteniendo las propiedades del funcionamiento del aerogenerador. Se proponen dos métodos innovadores para la linealización de los modelos no lineales de aerogeneradores flotantes y la optimización de los lazos de control diseñados en esta tesis. Los resultados mostrados demuestran la eficacia del controlador diseñado en la consecución de los objetivos propuestos

Hybrid modeling and control of mechatronic systems using a piecewise affine dynamics approach

This thesis investigates the topic of modeling and control of PWA systems based on two experimental cases of an electrical and hydraulic nature with varying complexity that were also built, instrumented and evaluated. A full-order model has been created for both systems, including all dominant system dynamics and non-linearities. The unknown parameters and characteristics have been identi ed via an extensive parameter identi cation. In the following, the non-linear characteristics are linearized at several points, resulting in PWA models for each respective setup. Regarding the closed loop control of the generated models and corresponding experimental setups, a linear control structure comprised of integral error, feed-forward and state-feedback control has been used. Additionally, the hydraulic setup has been controlled in an autonomous hybrid position/force control mode, resulting in a switched system with each mode's dynamics being de ned by the previously derived PWA-based model in combination with the control structure and respective mode-dependent controller gains. The autonomous switch between control modes has been de ned by a switching event capable of consistently switching between modes in a deterministic manner despite the noise-a icted measurements. Several methods were used to obtain suitable controller gains, including optimization routines and pole placement. Validation of the system's fast and accurate response was obtained through simulations and experimental evaluation. The controlled system's local stability was proven for regions in state-space associated with operational points by using pole-zero analysis. The stability of the hybrid control approach was proven by using multiple Lyapunov functions for the investigated test scenarios.publishedVersio

A Design Method of Model Error Compensator for Systems with Polytopic-type Uncertainty and Disturbances

Control systems achieve the desired performance with the model-based controller if the dynamical model of the actual plant is given with sufficient accuracy. However, if there exists a difference between the actual plant and its model dynamics, the model-based controller does not work well and does not achieve the intended desired performance. A model error compensator (MEC) is proposed for overcoming the model error in our previous study. Attaching the compensator for the model error to the actual plant, the output trajectory of the actual plant is made close to that of its model. Then, from the controller, the apparent difference in the dynamics can be smaller, and performance degradation is drastically reduced. MEC is useful for various control systems such as non-linear systems and the control systems with delay, and so on. In this paper, we propose an original design method of the filter parameters in MEC for systems with polytopic-type uncertainty and disturbances. First, we show an analysis method about the robust performance of MEC for the system with the polytopic type uncertainty based on an linear matrix inequality problem. The gain parameters in MEC is designed using particle swarm optimization and the presented analysis method. The effectiveness of the design method for the system with polytopic-type uncertainty and disturbance is evaluated using numerical examples

Advances in Condition Monitoring, Optimization and Control for Complex Industrial Processes

The book documents 25 papers collected from the Special Issue “Advances in Condition Monitoring, Optimization and Control for Complex Industrial Processes”, highlighting recent research trends in complex industrial processes. The book aims to stimulate the research field and be of benefit to readers from both academic institutes and industrial sectors