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The problem of planning a trajectory for robots starting in an initial state and reaching a final state in a desired interval of time is tackled. We consider Model Predictive Control as an approach to the problem of point-to-point trajectory generation. We use the developed strategy to generate trajectories for transferring the state of the robot, fulfilling computational real-time requirements. E
We consider an iterative learning control (ILC) approach to machining with industrial robots. The robot and the milling process are modeled using system identification methods with a data-driven approach. Two different model-based ILC algorithms are proposed and subsequently experimentally verified in a milling scenario. The difference between the two approaches is the required sensors for acquiri
The emerging new idea of lane-keeping electronic stability control is investigated. In a critical situation, such as entering a road curve at excessive speed, the optimal behavior may differ from the behavior of traditional ESC, for example, by prioritizing braking over steering response. The important question that naturally arises is if this has a significant effect on safety. The main contribut
A comparative analysis shows how vehicle motion models of different complexity, capturing various characteristics, influence the solution when used in time-critical optimal maneuvering problems. Vehicle models with combinations of roll and pitch dynamics as well as load transfer are considered, ranging from a single-track model to a double-track model with roll and pitch dynamics combined with loa
This paper presents a method for modeling and control of a piezo-actuated high-dynamic compensation mechanism (HDCM) for usage together with an industrial robot during a machining operation, such as milling in aluminum. The spindle is attached to the compensation mechanism and the robot holds the workpiece. Due to the inherent resonant character of mechanical constructions of this type, and the no
This paper presents results from time-optimal path tracking for industrial robots. More specifically, three subproblems are studied and experimentally evaluated. The first is a contact-force control approach for determining the geometric robot motion, such that the tool centre point of the robot is moved according to the specification. The second problem is off-line solution of the optimisation pr
We consider a real-time system of multiple tasks, each task having a plant to control. The overall quadratic control cost is to be optimized. We exploit the periodicity of the task response time, which corresponds to a periodic delay pattern in the feedback control loop. Perturbed periods are used as a tool to find a finite hyperperiod. We present an analytical procedure to design a periodic linea
This paper presents a straightforward method to convert non-uniformly sampled data to uniform samples in order to be processed by some off-line techniques such as system identification. In such scenarios, we deal with a finite-length measurement sequence. We assume periodic extension of the signals, which results in a simple system of linear equations. Furthermore, we take into account a number of
For low-rank Frobenius-norm approximations of matrices with non-negative entries, it is shown that the Lagrange dual is computable by semi-definite programming. Under certain assumptions the duality gap is zero. Even when the duality gap is non-zero, several new insights are provided.
The relay autotuner provides a simple way of finding PID controller parameters. Even though relay autotuning is much investigated in the literature, the practical aspects are not that well-documented. In this paper an asymmetric relay autotuner with features such as a startup procedure and adaptive relay amplitudes is proposed. Parameter choices and handling of noise, disturbances, start in non-st
Low rank approximation is an important tool in many applications. Given an observed matrix with elements corrupted by Gaussian noise it is possible to find the best approximating matrix of a given rank through singular value decomposition. However, due to the non-convexity of the formulation it is not possible to incorporate any additional knowledge of the sought matrix without resorting to heuris
This paper presents a Bayesian indoor positioningsystem for smartphones based on the strengths of WiFi andBluetooth signals. A framework for improving the performanceof existing positioning methods with the help informationsharing between users is proposed and evaluated. Bluetoothsignals are sent between users, and the signal strengths containinformation about their relative distances, which is us
Future manufacturing systems need to be more flexible, to embrace tougher and constantly changing market demands. They need to make better use of plant data, ideally utilising all data from the entire plant. Low-level data should be refined toreal-time information for decision-making, to facilitate competitiveness through informed and timely decisions. The Line Information System Architecture (LIS
This paper describes the design of a robust PID controller for propofol infusion in children and presents the results of clinical evaluation of this closed-loop system during endoscopic investigations in children age 6y-17y. The controller design is based on a set of models that describes the inter- patient variability in the response to propofol infusion in the study population. The PID controlle
This paper suggests an extension of an existing, clinically evaluated, closed-loop drug delivery system for hypnotic depth control using propofol. The extension introduces closed-loop administration of the analgesic drug remifentanil, thus forming a multiple input–single output (MISO) control system. Remifentanil acts and is metabolized at a significantly faster time scale than propofol. Direct co
The phenomenon of adopting open source software development practices in a corporate environment is known by many names, one being inner source. The objective of this study is to investigate how an organization consisting of small development teams can benet from adopting inner source and assess the level of applicability. The research has been conducted as a case study at a software development c
Nowadays, the same piece of code should run on different architectures, providing performance guarantees in a variety of environments and situations. To this end, designers often integrate existing systems with ad-hoc adaptive strategies able to tune specific parameters that impact performance or energy—for example, frequency scaling. However, these strategies interfere with one another and unpred
Stochastic optimal power flow can provide the system operator with adequate strategies for controlling the power flow to maintain secure operation under stochastic parameter variations. One limitation of stochastic optimal power flow has been that only steady-state variable limits have been used as security constraints. In many systems voltage stability and small-signal stability also play an impo
Innovative engineering methods are needed to enhance the adaptability and agility of industrial control procedures and concurrently manage their rising complexity. Service-oriented Architecture (SOA) constitutes a promising paradigm to meet these challenges. To apply the rather abstract SOA principles to industrial automation, a model-driven engineering method is presented in this paper. Therefore
