Mario Vašak

Hybrid Theory-Based Time-Optimal Control of an Electronic Throttle

An electronic throttle is a dc-motor-driven valve that regulates air inflow into the combustion system of the engine. The throttle control system should ensure fast and accurate reference tracking of the valve plate angle while preventing excessive wear of the throttle components by constraining physical variables to their normal-operation domains. These high-quality control demands are hard to accomplish since the plant is burdened with strong nonlinear effects of friction and limp-home nonlinearity. In this paper, the controller synthesis is performed in discrete time by solving a constrained time-optimal control problem for the piecewise affine (PWA) model of the throttle. To that end, a procedure is proposed to model friction in a discrete-time PWA form that is suitable both for simulation and controller design purposes. The control action computation can, in general, be restated as a mixed-integer program. However, due to the small sampling time, solving such a program online (in a receding horizon fashion) would be very prohibitive. This issue is resolved by applying recent theoretical results that enable offline precomputation of the state-feedback optimal control law in the form of a lookup table. The technique employs invariant set computation and reachability analysis. The experimental results on a real electronic throttle are reported and compared with a tuned PID controller that comprises a feedforward compensation of the process nonlinearities. The designed time-optimal controller achieves considerably faster transient, while preserving other important performance measures, like the absence of overshoot and static accuracy within the measurement resolution

Stator-Current Spectrum Signature of Healthy Cage Rotor Induction Machines

Before applying current-signature-analysis-based monitoring methods, it is necessary to thoroughly analyze the existence of the various harmonics on healthy machines. As such an analysis is only done in very few papers, the objective of this paper is to make a clear and rigorous characterization and classification of the harmonics present in a healthy cage rotor induction motor spectrum as a starting point for diagnosis. Magnetomotive force space harmonics, slot permeance harmonics, and saturation of main magnetic flux path through the virtual air-gap permeance variation are taken into analytical consideration. General rules are introduced giving a connection between the number of stator slots, rotor bars, and pole pairs and the existence of rotor slot harmonics as well as saturation-related harmonics in the current spectrum. For certain combinations of stator and rotor slots, saturation-related harmonics are shown to be most prominent in motors with a pole pair number of two or more. A comparison of predicted and measured current harmonics is given for several motors with different numbers of pole pairs, stator slots, and rotor bars.

Constrained Optimal Control of an Electronic Throttle

The overall vehicle performance is strongly influenced by the quality of the control of the electronic throttle – a DC motor driven valve that regulates the inflow of air to the vehicles engine. Designing a controller for the throttle system is a challenging task since one has to cope with two strong non-linearities: the gearbox friction and the so-called “limp-home” non-linearity. In this paper we address these issues by solving a constrained optimal control problem formulated for the discrete-time piecewise affine (PWA) model of the throttle. In an off-line, dynamic programming procedure we obtain the look-up table like solution to the optimal control problem. Such a solution allows the real-time controller implementation that would otherwise be impossible to achieve due to the small sampling time needed for the application at hand. We address the issue of the PWA friction modelling in more detail by considering both static and dynamic friction models. Two different control strategies are studied: constrained finite time optimal control (CFTOC), used in the regulator case, and constrained time-optimal control (CTOC), used in the reference tracking case. We report experimental results with both control strategies. The reference tracking controller significantly outperformed a tuned PID controller with a feedforward compensation of non-linearities in terms of the response speed while preserving the response quality regarding the absence of an overshoot and the static accuracy within the measurement resolution.

State estimation of an electronic throttle body

Electronic throttle body (ETB) is a device used in cars to regulate air inflow into the motors combustion system. Its good behavior is crucial for the superimposed engine speed control system. However, electronic throttle body is a highly nonlinear process, and its only measurable state is the throttle valve position measured by a cheap potentiometer of low resolution, resulting in significant quantization noise. In order to apply an advanced control strategy, all states should be usually available and the measurement noise should be reduced. With these two goals in mind we have implemented an extended Kalman filter (EKF), as a common solution for state estimation of nonlinear systems, and an unscented Kalman filter (UKF), which is a preferable solution when the process nonlinearities are very strong. Both filters are based on discrete time piece-wise affine process model which uses new friction model. By experimental tests on a real ETB it is shown that UKF gives better estimates of its state variables.

Electronic throttle state estimation and hybrid theory based optimal control

Electronic throttle body (ETB) is a car device that regulates air inflow into the motors combustion system. Its performance has a major impact on the quality of the overall engine speed control. However, due to the usage of cheap components and some design features the ETB exhibits several nonlinear phenomena. This nonlinear behavior and the fact that there is only one measurement available - low quality measurement of the throttle position makes a design of the throttle controller a challenging task. Our approach is to model the ETB as a discrete time piecewise affine (PWA) system and apply model predictive control (MPC) strategy to design an explicit state feedback control law. Since MPC is a full-state controller and there is only one measurement available the rest of the states have to be estimated. We have chosen unscented Kalman filter (UKF) for the estimation purpose since it was performing the best in the presence of strong, almost discontinuous, process nonlinearities. In the end, MPC and UKF algorithm were implemented and tested on the real electronic throttle for the case of set-point reference. Experimental results indicate that the performance of cheaply produced components can be significantly improved with a good control strategy.

Hybrid system theory based optimal control of an electronic throttle

In this paper we show how hybrid system theory can be used to obtain a state-feedback optimal control law for an electronic throttle. After modelling the electronic throttle as a piece wise affine (PWA) system, we derive an optimal control law for such a hybrid system via dynamic programming. Results indicate that constrained finite time optimal control of small/medium sized PWA systems with fast sampling times can be successfully implemented.

Deep neural networks for ultra-short-term wind forecasting

The aim of this paper is to present input variable selection algorithm and deep neural networks application to ultra-short-term wind prediction. Shallow and deep neural networks coupled with input variable selection algorithm are compared on the ultra-short-term wind prediction task for a set of different locations. Results show that carefully selected deep neural networks outperform shallow ones. Input variable selection use reduces the neural network complexity and simplifies deep neural network training.

Analysis of microgrid power flow optimization with consideration of residual storages state

Microgrid is a cluster of distributed generation sources, storages and loads that cooperate so as to improve the reliability and quality of the local power supply and of the power system. In this paper we present a power flow optimization of a DC microgrid that consists of photovoltaic array, batteries stack and fuel cells stack with electrolyser, and is connected to the grid via bidirectional power converter. The optimization problem aims to minimize microgrid operating costs and is formulated using a linear program that takes into account the storages charge and discharge efficiency, and considers the residual state of the energy storage systems in the criterion function. Performance of the proposed approach is verified through year-scale simulations based on the actual meteorological, electricity price and consumption data. The analysis performed points out that especially for short prediction horizons it is very important to ensure proper penalization of the residual storages state in the criterion function in order to yield optimum revenue from microgrid operation.

Robust invariant set‐based protection of multi‐mass electrical drives

Purpose – The purpose of this paper is to elaborate a robust model‐based protective control algorithm for multi‐mass motor drives that are subjected to physical and safety constraints on their variables.Design/methodology/approach – The algorithm relies on the off‐line computed maximum robust controlled invariant set or its approximation for the given drive system and imposed constraints. It can be used to patch any existing drive control scheme with a firm constraints satisfaction guarantee. The online patch implementation is actually a simple correction of the control signal computed with the existing control scheme, with a mandatory state observer.Findings – Performance of the patch is tested on a two‐mass drive system in combination with classical two‐mass drive speed controllers – P+I and reduced state controller. All constraints violations that exist in the presented responses obtained without the protection patch are suppressed by using the patch which shows the effectiveness of the approach. A bri...

A method to detect missing magnetic slot wedges in AC machines without disassembling

In high voltage induction machines the stator slots usually are wide opened to facilitate the assembling of the stator winding coils. Thus the magnetically effective air gap and higher order harmonics are rising, the power factor is decreasing. To compensate this negative effect magnetic stator slot wedges are frequently applied. During operation these slot wedges can get loose and eventually fall out totally. Currently a detection of fallen out slot wedges is only possible by time consuming partially disassembling the machine and optical inspection. Simple and reliable testing methods can thus increase the reliability and reduce costs due to unnecessary disassembling of the machine. For such testing methods high frequency or transient electrical properties of an electrical machine suit very well as the base. When high frequency or transient voltage signals are applied to the terminals of the machine the resulting current response contains information about the machines magnetic state. Therein superposed are the magnetic material properties, several inherent asymmetries such as spatial saturation or slotting, as well as fault induced asymmetries. This paper introduces a new signal processing chain to detect and isolate the fault induced asymmetries caused by fallen out stator slot wedges. The chain consists of data capturing by collecting current response values due to voltage pulses and following Fast Fourier transformations. Measurements for several slot wedge fault cases are presented. The measured and calculated results show the high sensitivity and reliability of the proposed method.