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Use of feedforward can alleviate feedback and adaptive actions. Feedforward signals can be generated from reference models and the same models can also be used as reference models in adaptive control. A method for designing the reference models is presented in the paper. By exploiting the structure of the equations describing air vehicles it is possible to find reference models that scale to the p
The development of a predictive control algorithm for glycaemia regulation in diabetic subjects requires patient-specific models of the glucose metabolism which are physiologically relevant, parsimonious, yet able to accurately forecast blood glucose. Given the measured data: total plasma insulin [mIU/L]; plasma glucose [mg/dL]; plasma glucose rate of appearance after intestinal absorption [mg/kg
A previous paper introduced an online gradient method to iteratively update local controllers for improved performance. In this paper we modify that method to get an offline method for distributed control synthesis. The complexity of the method is linear in the number of neighbors to each agent. Since the controllers are constructed to be distributed and the method is an iterative scheme, the con
This paper introduces a new Open Source Java library suited for the simulation of embedded control systems. The library is based on the ideas and architecture of TrueTime, a toolbox of Matlab devoted to this topic, and allows Java programmers to simulate the performance of control processes which run in a real time environment. Such simulations can improve considerably the learning and design of m
Wind turbines operating in wind farms are coupled by the wind flow. This coupling results in increased turbulence levels for downwind turbines, and consequently higher maintenance costs. In this paper, we consider a scenario where a wind farm is asked to produce less than maximum power. The objective is to minimize fatigue loads on the turbines, while maintaining the desired power production. We s
Numerous auto-scaling strategies have been proposed in the past few years for improving various Quality of Service (QoS) indicators of cloud applications, for example, response time and throughput, by adapting the amount of resources assigned to the application to meet the workload demand. However, the evaluation of a proposed auto-scaler is usually achieved through experiments under specific cond
This work concerns efficient and reliable numerical simulations of the dynamic behaviour of a moving-boundary model for tubulin-driven axonal growth. The model is nonlinear and consists of a coupled set of a partial differential equation (PDE) and two ordinary differential equations. The PDE is defined on a computational domain with a moving boundary, which is part of the solution. Numerical simul
Many popular first order algorithms for convex optimization, such as forward-backward splitting, Douglas-Rachford splitting, and the alternating direction method of multipliers (ADMM), can be formulated as averaged iteration of a nonexpansive mapping. In this paper we propose a line search for averaged iteration that preserves the theoretical convergence guarantee, while often accelerating practic
Nonlinear Model Predictive Control (NMPC) is a control strategy based on repeatedly solving an optimal control problem. In this paper we present a new MPC framework for the JModelica.org platform, developed specifically for use in NMPC schemes. The new framework utilizes the fact that the optimal control problem to be solved does not change between solutions, thus decreasing the computation time n
This paper presents a hierarchical approach to feedback-based trajectory generation for improved vehicle autonomy. Hierarchical vehicle-control structures have been used before—for example, in electronic stability control systems, where a low-level control loop tracks high-level references. Here, the control structure includes a nonlinear vehicle model already at the high level to generate optimiz
As automatic sensing and Information and Communication Technology (ICT) get cheaper, building monitoring data is easier to obtain. The abundance of data leads to new opportunities in the context of energy efficiency in buildings. This paper describes ongoing developments and first results of data-driven grey-box modelling for buildings. A Python toolbox is developed based on a Modelica library wit
Dynamic optimization problems involving differential-algebraic equation (DAE) systems are traditionally solved while retaining the semi-explicit or implicit form of the DAE. We instead consider symbolically transforming the DAE into an ordinary differential equation (ODE) before solving the optimization problem using a collocation method. We present a method for achieving this, which handles DAE-c
The solution of generic dynamic optimization problems described by Modelica, and its extension Optimica, code using direct collocation methods is discussed. We start by providing a description of dynamic optimization problems in general and how to solve them by means of direct collocation. Next, an existing implementation of a collocation algorithm in JModelica.org, using CasADi and IPOPT, is pres
Dynamic optimization problems involving parametric sensitivities, such as optimal experimental design, are typically solved using shooting-based methods, while leveraging numerical integrators with sensitivity computation capabilities. In this paper we present how simultaneous discretization can be employed to solve these problems, by augmenting the dynamic optimization problems with forward sensi
This paper presents a convex-optimization-based technique to obtain parameters for a PID feedback controller, used to control the infusion rate of the anesthetic drug propofol. The controller design is based on a set of identified patient models, relating propofol infusion to an EEG-based conciousness index. The main contribution lies in the method automatically taking inter-patient variability in
When deploying networked computing-based applications, proper resource management of the server-side resources is essential for maintaining quality of service and cost efficiency. The work presented in this thesis is based on six papers, all investigating problems that relate to resource management of server-based systems. Using a queueing system approach we model the performance of a database sys
