Adaptive control of sinusoidal brushless DC motor actuators

Electrical Power Assisted Steering system (EPAS) will likely be used on future automotive power steering systems. The sinusoidal brushless DC (BLDC) motor has been identified as one of the most suitable actuators for the EPAS application. Motor characteristic variations, which can be indicated by variations of the motor parameters such as the coil resistance and the torque constant, directly impart inaccuracies in the control scheme based on the nominal values of parameters and thus the whole system performance suffers. The motor controller must address the time-varying motor characteristics problem and maintain the performance in its long service life. In this dissertation, four adaptive control algorithms for brushless DC (BLDC) motors are explored. The first algorithm engages a simplified inverse dq-coordinate dynamics controller and solves for the parameter errors with the q-axis current (iq) feedback from several past sampling steps. The controller parameter values are updated by slow integration of the parameter errors. Improvement such as dynamic approximation, speed approximation and Gram-Schmidt orthonormalization are discussed for better estimation performance. The second algorithm is proposed to use both the d-axis current (id) and the q-axis current (iq) feedback for parameter estimation since id always accompanies iq. Stochastic conditions for unbiased estimation are shown through Monte Carlo simulations. Study of the first two adaptive algorithms indicates that the parameter estimation performance can be achieved by using more history data. The Extended Kalman Filter (EKF), a representative recursive estimation algorithm, is then investigated for the BLDC motor application. Simulation results validated the superior estimation performance with the EKF. However, the computation complexity and stability may be barriers for practical implementation of the EKF. The fourth algorithm is a model reference adaptive control (MRAC) that utilizes the desired motor characteristics as a reference model. Its stability is guaranteed by Lyapunov’s direct method. Simulation shows superior performance in terms of the convergence speed and current tracking. These algorithms are compared in closed loop simulation with an EPAS model and a motor speed control application. The MRAC is identified as the most promising candidate controller because of its combination of superior performance and low computational complexity. A BLDC motor controller developed with the dq-coordinate model cannot be implemented without several supplemental functions such as the coordinate transformation and a DC-to-AC current encoding scheme. A quasi-physical BLDC motor model is developed to study the practical implementation issues of the dq-coordinate control strategy, such as the initialization and rotor angle transducer resolution. This model can also be beneficial during first stage development in automotive BLDC motor applications.

Efficient speed advisories for multi-stage-metering arrival management

This paper presents a methodology and algorithm for Air Traffic Control (ATC) to efficiently achieve schedules arrival times through speed control in the presence of uncertainty. The methodology does not assume the availability of airborne time of arrival control and can therefore be applied to legacy aircraft. The speed advisories are calculated in a manner that allows for sufficient control margin to, if required, adjust the aircraft's trajectory at a later stage to correct for estimated arrival time drift at the lowest impact to efficiency. The methodology is therefore envisioned to prevent major last-minute interventions and instead assists ATC in allowing more continuous descent approaches to be conducted by aircraft leading to more efficient operations.

Evaluation of the Intelligent Cruise Control System. Volume I: study results.

National Highway Traffic Safety Administration, Washington, D.C.

Solar PV-powered SRM drive for EVs with flexible energy control functions

Electric vehicles (EVs) provide a feasible solution to reducing greenhouse gas emissions and thus become a hot topic for research and development. Switched reluctance motors (SRMs) are one of promised motors for EV applications. In order to extend the EVs’ driving miles, the use of photovoltaic (PV) panels on the vehicle helps decrease the reliance on vehicle batteries. Based on phase winding characteristics of SRMs, a tri-port converter is proposed in this paper to control the energy flow between the PV panel, battery and SRM. Six operating modes are presented, four of which are developed for driving and two for standstill on-board charging. In the driving modes, the energy decoupling control for maximum power point tracking (MPPT) of the PV panel and speed control of the SRM are realized. In the standstill charging modes, a grid-connected charging topology is developed without a need for external hardware. When the PV panel directly charges the battery, a multi-section charging control strategy is used to optimize energy utilization. Simulation results based on Matlab/Simulink and experiments prove the effectiveness of the proposed tri-port converter, which has potential economic implications to improve the market acceptance of EVs.

Persistent ocean monitoring with underwater gliders : adapting sampling resolution

Ocean processes are dynamic, complex, and occur on multiple spatial and temporal scales. To obtain a synoptic view of such processes, ocean scientists collect data over long time periods. Historically, measurements were continually provided by fixed sensors, e.g., moorings, or gathered from ships. Recently, an increase in the utilization of autonomous underwater vehicles has enabled a more dynamic data acquisition approach. However, we still do not utilize the full capabilities of these vehicles. Here we present algorithms that produce persistent monitoring missions for underwater vehicles by balancing path following accuracy and sampling resolution for a given region of interest, which addresses a pressing need among ocean scientists to efficiently and effectively collect high-value data. More specifically, this paper proposes a path planning algorithm and a speed control algorithm for underwater gliders, which together give informative trajectories for the glider to persistently monitor a patch of ocean. We optimize a cost function that blends two competing factors: maximize the information value along the path, while minimizing deviation from the planned path due to ocean currents. Speed is controlled along the planned path by adjusting the pitch angle of the underwater glider, so that higher resolution samples are collected in areas of higher information value. The resulting paths are closed circuits that can be repeatedly traversed to collect long-term ocean data in dynamic environments. The algorithms were tested during sea trials on an underwater glider operating off the coast of southern California, as well as in Monterey Bay, California. The experimental results show significant improvements in data resolution and path reliability compared to previously executed sampling paths used in the respective regions.

Bond graph model of doubly fed three phase induction motor using the Axis Rotator element for frame transformation

Induction motor is a typical member of a multi-domain, non-linear, high order dynamic system. For speed control a three phase induction motor is modelled as a d–q model where linearity is assumed and non-idealities are ignored. Approximation of the physical characteristic gives a simulated behaviour away from the natural behaviour. This paper proposes a bond graph model of an induction motor that can incorporate the non-linearities and non-idealities thereby resembling the physical system more closely. The model is validated by applying the linearity and idealities constraints which shows that the conventional ‘abc’ model is a special case of the proposed generalised model.

A Hydraulic Micromanipulator

For biological experiments requiring manipulations under a microscope, it is necessary to have remote control for the manipulator. Available systems offer the required accuracy at a high cost. Passive micromanipulators are economical but are deficient in performance, the most serious defects being the inability to attenuate operator-induced vibrations and lack of speed control The manipulator described in this paper provides versatile remote control and may be constructed economically.

A Hydraulic Micromanipulator

For biological experiments requiring manipulations under a microscope, it is necessary to have remote control for the manipulator. Available systems offer the required accuracy at a high cost. Passive micromanipulators are economical but are deficient in performance, the most serious defects being the inability to attenuate operator-induced vibrations and lack of speed control The manipulator described in this paper provides versatile remote control and may be constructed economically.

Method of Analysis if Uniaxial Deformation Data

A comprehensive scheme for analysing uniaxial deformation data, taking into account the finite stiffness of the testing machine is presented. Equations relevant to tension and stress relaxation tests carried out under cross head speed control, and to creep testing under constant load, are described. For the first two cases, the implications of not using gauge length extensometry but relying upon cross head displacement for inferring specimen extension, and the role of uncertainty in machine stiffness are also examined. The final section touches upon the extension of the present scheme to account for specimen anelasticity.

Analysis of sine-triangle and zero-sequence injection modulation schemes for split-phase induction motor drive

A split-phase induction motor is fed from two three-phase voltage source inverters for speed control. This study analyses carrier-comparison based pulse width modulation (PWM) schemes for a split-phase motor drive, from a space-vector perspective. Sine-triangle PWM, one zero-sequence injection PWM where the same zero-sequence signal is used for both the inverters, and another zero-sequence injection PWM where different zero-sequence signals are employed for the two inverters are considered. The set of voltage vectors applied, the sequence in which the voltage vectors are applied, and the resulting current ripple vector are analysed for all the PWM methods. Besides all the PWM methods are compared in terms of dc bus utilisation. For the same three-phase sine reference, the PWM method with different zero-sequence signals for the two inverters is found to employ a set of vectors different from the other methods. Both analysis and experimental results show that this method results in lower total harmonic distortion and higher dc bus utilisation than the other two PWM methods.

Permutationally invariant state reconstruction

Feasible tomography schemes for large particle numbers must possess, besides an appropriate data acquisition protocol, an efficient way to reconstruct the density operator from the observed finite data set. Since state reconstruction typically requires the solution of a nonlinear large-scale optimization problem, this is a major challenge in the design of scalable tomography schemes. Here we present an efficient state reconstruction scheme for permutationally invariant quantum state tomography. It works for all common state-of-the-art reconstruction principles, including, in particular, maximum likelihood and least squares methods, which are the preferred choices in today's experiments. This high efficiency is achieved by greatly reducing the dimensionality of the problem employing a particular representation of permutationally invariant states known from spin coupling combined with convex optimization, which has clear advantages regarding speed, control and accuracy in comparison to commonly employed numerical routines. First prototype implementations easily allow reconstruction of a state of 20 qubits in a few minutes on a standard computer

Um ambiente de aprendizagem em automação baseado em sistemas nebulosos

Esta dissertação trata de um estudo e o desenvolvimento de uma proposta de um ambiente de aprendizagem, para qualquer instituição de ensino superior, em três níveis de ensino da área de controle e automação: graduação, pós-graduação Lato Sensu e Stricto Sensu. Primeiramente, foram feitas visitas aos laboratórios em universidades e entrevistas com professores que ministram as disciplinas de controle e automação nos três níveis de aprendizagem. Foram constatadas virtudes e fragilidades metodológicas na questão da prática laboratorial em relação a aspectos industriais na área de engenharia elétrica de três instituições do Estado do Rio de Janeiro, sendo uma federal, uma estadual e outra privada. Posteriormente, foram analisados mecanismos e instrumentos necessários para interagir com modelos experimentais propostos nas entrevistas de maneira didática, para fins de constituir o ambiente de aprendizagem em automação, no qual foi eleito o LABVIEW como a interface mais favorável para aplicação de controles, mantendo uma analogia de cunho prático-industrial. A partir dessas análises foram sugeridos ainda elementos típicos de automação e três estudos de caso: um sistema térmico, um controle de velocidade de motores e um pêndulo invertido, por meio de controles simples e avançados como o controlador nebuloso, caracterizando-se pelo fortalecimento da atividade acadêmico-industrial

Optimizing the energy output of vertical axis wind turbines for fluctuating wind conditions

The control of a wind turbine to the mean wind speed in a gusty wind results in very poor performance. Fluctuations in wind speed with time constants shorter than the response time of a wind turbine results in operation away from optimum design conditions. The effectiveness of a turbine operating in a gusty wind is shown though the use of an unsteady performance coefficient, C e. This performance coefficient is similar in form to a power coefficient. However in order to accommodate unsteady effects, Ce is defined as a ratio of energy extracted to the total wind energy available over a set time period. The turbine's response to real wind data is modelled, in the first instance, by assuming a constant rotational speed operation. It is shown that a significant increase in energy production can be realized by demanding a Tip Speed Ratio above the steady state optimum. The constant speed model is then further extended to incorporate inertial and controller effects. Parameters dictating how well a turbine can track a demand in Tip Speed Ratio have been identified and combined, to form a non-dimensional turbine response parameter. This parameter characterizes a turbine's ability to track a demand in Tip Speed Ratio dependent on an effective gust frequency. A significant increase in energy output of 42% and 245% is illustrated through the application of this over-speed control. This is for the constant rotational speed and Tip Speed Ratio feedback models respectively. The affect of airfoil choice on energy extraction within a gusty wind has been considered. The adaptive control logic developed enables the application of airfoils demonstrating high maximum L/D values but sharp stalling characteristics to be successfully used in a VAWT design.

基于神经网络的永磁同步电机矢量控制

采用单神经元自适应PID控制器对永磁同步电机进行了调速控制。详细介绍了PMSM(PermanentMagnetSynchronousMotor)的矢量控制原理。最后给出PMSM单神经元自适应PID控制的仿真结果和硬件实现方法。仿真结果表明,该系统具有良好的动态性能。

The VITEWRITE Model of Handwriting Production

This article describes the VITEWRITE model for generating handwriting movements. The model consists of a sequential controller, or motor program, that interacts with a trajectory generator to move a hand with redundant degrees of freedom. The neural trajectory generator is the Vector Integration to Endpoint (VITE) model for synchronous variable-speed control of multijoint movements. VITE properties enable a simple control strategy to generate complex handwritten script if the hand model contains redundant degrees of freedom. The controller launches transient directional commands to independent hand synergies at times when the hand begins to move, or when a velocity peak in the outflow command to a given synergy occurs. The VITE model translates these temporally disjoint synergy commands into smooth curvilinear trajectories among temporally overlapping synergetic movements. Each synergy exhibits a unimodal velocity profile during any stroke, generates letters that are invariant under speed and size rescaling, and enables effortless connection of letter shapes into words. Speed and size rescaling are achieved by scalar GO and GRO signals that express computationally simple volitional commands. Psychophysical data such as the isochrony principle, asymmetric velocity profiles, and the two-thirds power law relating movement curvature and velocity arise as emergent properties of model interactions.