Active Object Search Exploiting Probabilistic Object–Object Relations

\u3cp\u3eThis paper proposes a probabilistic object-object relation based approach for an active object search. An important role of mobile robots will be to perform object-related tasks and active object search strategies deal with the non-trivial task of finding an object in unstructured and dynamically changing environments. This work builds further upon an existing approach exploiting probabilistic object-room relations for selecting the room in which an object is expected to be. Learnt object-object relations allow to search for objects inside a room via a chain of intermediate objects. Simulations have been performed to investigate the effect of the camera quality on path length and failure rate. Furthermore, a comparison is made with a benchmark algorithm based the same prior knowledge but without using a chain of intermediate objects. An experiment shows the potential of the proposed approach on the AMIGO robot.\u3c/p\u3

Repetitive control for systems with uncertain period-time with application to a compact disc drive

Repetitive control is useful if periodic disturbances act on acontrol system. Perfect (asymptotic) disturbance rejection isachieved if the period-time is exactly known. For those caseswhere the period-time changes and can not be measured directly byan auxiliary signal, a robust repetitive controller structure isproposed. It uses multiple memory-loops in a certain feedbackconfiguration, such that small changes in period-time do notdiminish the disturbance rejection properties. The robustrepetitive controller shows good implementation results for atracking control problem of a Compact Disc playe

Mechatronics disrupted

\u3cp\u3eThe field of mechatronics started in the 1970s when mechanical systems needed more accurate controlled motions. This forced both industry and academia to explore sensors, and electronic assisted feedback, while using mostly electrical drives instead of, for instance, mechanical cam shafts in production facilities. This introduction of feedback-controlled motion formed the basis for the need to enable mechanical engineers and electronic engineers to work better together and to understand each others language. Note that in those days control engineering departments were mostly part of the electrical development or research departments of industry and academia. Various initiatives were also undertaken to develop a common language or methodology. Some institutes pushed mechatronics forward as being a new discipline.\u3c/p\u3

Dynamic modelling and analysis of a wind turbine with variable speed

On behalf of the operation of the Dutch National Wind Farm, which is under construction now, a study is being performed on the control system design of variable speed wind turbines. To realize this a non-linear dynamic model of a wind turbine with synchronous generator and AC/ DC/AC conversion has been set up, which is presented here. The specific dynamic coupling between generator and DC link results in an implicit set of equations. By using an expression for the load angle of the generator the model is made explicit, which makes it suitable for further analysis. With non-linear simulations and eigenvalue-analysis it is shown that the wind turbine has very fast as well as very slow dynamics. There is also a slightly damped oscillation. Using a linear input-output model the interaction has been investigated. Though speed and direct current are stationary decoupled, there is a large amount of dynamic interaction between them. Control systems have to take this interaction into account

Investigation of the repetitive process ILC

No abstract

Design and control of an Electronic Throttle Controller

No abstrac

Comparison of three iterative learning control algorithms

This report compares three algorithms from recent papers published on iterative learning control. This is done by applying the algorithms to a gantry robot both in simulations and experiments. Results of this is given. Similarities and differences between the algorithms are presented, which can be used to decide when to use what algorithm

Simulink model of a controlled AC drive

A model of the ABB ACS800 industrial drive using Matlab Simulink is presented in this report. The ACS800 (ABB, 2011) is a drive designed for industrial applications and contains a rectifier, DC link , inverter and an AC drive. A choice can be made between speed control or torque control of the drive shaft. The feedback for the control loop is supplied by a motor model instead of encoders on the motor shaft. Chapter 1 shows the derivation of a full motor model that is used to approximate the behavior of the AC drive. The motor input is a three phase, AC voltage that is generated in an AC-DC-AC converter, discussed in chapter 2. Switching the gates of the inverter allows control over the generated three phase output voltage. The switching commands are generated by the controller. Speed control can be realized as scalar control, or by using vector control. The control of the torque can only be done with the latter scheme. The used scalar control uses a direct relationship between the motor input peak voltage amplitude and the rotational frequency. It is named Volts per Hertz control (chapter 3). The desired motor input voltage wave is realized as a PWM signal by choosing appropriate switch commands for the inverter. Vector control (chapter 4) uses the motor input voltage to control the magnetic flux amplitude generated in the stator of the motor and the output torque. The switch commands for the inverter are chosen through the direct torque control (DTC) algorithm where the estimated stator flux and the estimated output torque, acquired from the motor model, are compared to reference values. The torque reference is obtained from the speed controller in chapter 5