Proceedings of the Institution of Electrical Engineers.

Vols.1-87,1872-1940 also called no.1-258.

Theory of mind and relational complexity

Cognitive complexity and control theory and relational complexity theory attribute developmental changes in theory of mind (TOM) to complexity. In 3 studies, 3-, 4-, and 5-year-olds performed TOM tasks (false belief, appearance-reality), less complex connections (Level 1 perspective-taking) tasks, and transformations tasks (understanding the effects of location changes and colored filters) with content similar to TOM. There were also predictor tasks at binary-relational and ternary-relational complexity levels, with different content. Consistent with complexity theories: (a) connections and transformations were easier and mastered earlier than TOM; (b) predictor tasks accounted for more than 80% of age-related variance in TOM; and (c) ternary-relational items accounted for TOM variance, before and after controlling for age and binary-relational items. Prediction did not require hierarchically structured predictor tasks.

Optimal unravellings for feedback control in linear quantum systems

For quantum systems with linear dynamics in phase space much of classical feedback control theory applies. However, there are some questions that are sensible only for the quantum case: Given a fixed interaction between the system and the environment what is the optimal measurement on the environment for a particular control problem? We show that for a broad class of optimal (state- based) control problems ( the stationary linear-quadratic-Gaussian class), this question is a semidefinite program. Moreover, the answer also applies to Markovian (current-based) feedback.

When do firms conform? The effect of regulatory control processes on compliance and opportunism

The authors use social control theory to develop a conceptual model that addresses the effectiveness of regulatory agencies’ (e.g., Food and Drug Administration, Occupational Safety and Health Administration) field-level efforts to obtain conformance with product safety laws. Central to the model are the control processes agencies use when monitoring organizations and enforcing the safety rules. These approaches can be labeled formal control (e.g., rigid enforcement) and informal control (e.g., social instruction). The theoretical framework identifies an important antecedent of control and the relative effectiveness of control’s alternative forms in gaining compliance and reducing opportunism. Furthermore, the model predicts that the regulated firms’ level of agreement with the safety rules moderates the relationships between control and firm responses. A local health department’s administration of state food safety regulations provides the empirical context for testing the hypotheses. The results from a survey of 173 restaurants largely support the proposed model. The study findings inform a discussion of effective methods of administering product safety laws. The authors use social control theory to develop a conceptual model that addresses the effectiveness of regulatory agencies’ (e.g., Food and Drug Administration, Occupational Safety and Health Administration) field-level efforts to obtain conformance with product safety laws. Central to the model are the control processes agencies use when monitoring organizations and enforcing the safety rules. These approaches can be labeled formal control (e.g., rigid enforcement) and informal control (e.g., social instruction). The theoretical framework identifies an important antecedent of control and the relative effectiveness of control’s alternative forms in gaining compliance and reducing opportunism. Furthermore, the model predicts that the regulated firms’ level of agreement with the safety rules moderates the relationships between control and firm responses. A local health department’s administration of state food safety regulations provides the empirical context for testing the hypotheses. The results from a survey of 173 restaurants largely support the proposed model. The study findings inform a discussion of effective methods of administering product safety laws.

Mathematical modelling and optimal multivariable control of chemical processes

This work reports the developnent of a mathenatical model and distributed, multi variable computer-control for a pilot plant double-effect climbing-film evaporator. A distributed-parameter model of the plant has been developed and the time-domain model transformed into the Laplace domain. The model has been further transformed into an integral domain conforming to an algebraic ring of polynomials, to eliminate the transcendental terms which arise in the Laplace domain due to the distributed nature of the plant model. This has made possible the application of linear control theories to a set of linear-partial differential equations. The models obtained have well tracked the experimental results of the plant. A distributed-computer network has been interfaced with the plant to implement digital controllers in a hierarchical structure. A modern rnultivariable Wiener-Hopf controller has been applled to the plant model. The application has revealed a limitation condition that the plant matrix should be positive-definite along the infinite frequency axis. A new multi variable control theory has emerged fram this study, which avoids the above limitation. The controller has the structure of the modern Wiener-Hopf controller, but with a unique feature enabling a designer to specify the closed-loop poles in advance and to shape the sensitivity matrix as required. In this way, the method treats directly the interaction problems found in the chemical processes with good tracking and regulation performances. Though the ability of the analytical design methods to determine once and for all whether a given set of specifications can be met is one of its chief advantages over the conventional trial-and-error design procedures. However, one disadvantage that offsets to some degree the enormous advantages is the relatively complicated algebra that must be employed in working out all but the simplest problem. Mathematical algorithms and computer software have been developed to treat some of the mathematical operations defined over the integral domain, such as matrix fraction description, spectral factorization, the Bezout identity, and the general manipulation of polynomial matrices. Hence, the design problems of Wiener-Hopf type of controllers and other similar algebraic design methods can be easily solved.

Design of a stock control methodology for use within an oil blending company

The thesis deals with the background, development and description of a mathematical stock control methodology for use within an oil and chemical blending company, where demand and replenishment lead-times are generally non-stationary. The stock control model proper relies on, as input, adaptive forecasts of demand determined for an economical forecast/replenishment period precalculated on an individual stock-item basis. The control procedure is principally that of the continuous review, reorder level type, where the reorder level and reorder quantity 'float', that is, each changes in accordance with changes in demand. Two versions of the Methodology are presented; a cost minimisation version and a service level version. Realising the importance of demand forecasts, four recognised variations of the Trigg and Leach adaptive forecasting routine are examined. A fifth variation, developed, is proposed as part of the stock control methodology. The results of testing the cost minimisation version of the Methodology with historical data, by means of a computerised simulation, are presented together with a description of the simulation used. The performance of the Methodology is in addition compared favourably to a rule-of-thumb approach considered by the Company as an interim solution for reducing stack levels. The contribution of the work to the field of scientific stock control is felt to be significant for the following reasons:- (I) The Methodology is designed specifically for use with non-stationary demand and for this reason alone appears to be unique. (2) The Methodology is unique in its approach and the cost-minimisation version is shown to work successfully with the demand data presented. (3) The Methodology and the thesis as a whole fill an important gap between complex mathematical stock control theory and practical application. A brief description of a computerised order processing/stock monitoring system, designed and implemented as a pre-requisite for the Methodology's practical operation, is presented as an appendix.

Fully probabilistic control design in an adaptive critic framework

Optimal stochastic controller pushes the closed-loop behavior as close as possible to the desired one. The fully probabilistic design (FPD) uses probabilistic description of the desired closed loop and minimizes Kullback-Leibler divergence of the closed-loop description to the desired one. Practical exploitation of the fully probabilistic design control theory continues to be hindered by the computational complexities involved in numerically solving the associated stochastic dynamic programming problem. In particular very hard multivariate integration and an approximate interpolation of the involved multivariate functions. This paper proposes a new fully probabilistic contro algorithm that uses the adaptive critic methods to circumvent the need for explicitly evaluating the optimal value function, thereby dramatically reducing computational requirements. This is a main contribution of this short paper.

Fuzzy Modeling and Control Based Virtual Machine Resource Management

Virtual machines (VMs) are powerful platforms for building agile datacenters and emerging cloud systems. However, resource management for a VM-based system is still a challenging task. First, the complexity of application workloads as well as the interference among competing workloads makes it difficult to understand their VMs’ resource demands for meeting their Quality of Service (QoS) targets; Second, the dynamics in the applications and system makes it also difficult to maintain the desired QoS target while the environment changes; Third, the transparency of virtualization presents a hurdle for guest-layer application and host-layer VM scheduler to cooperate and improve application QoS and system efficiency. This dissertation proposes to address the above challenges through fuzzy modeling and control theory based VM resource management. First, a fuzzy-logic-based nonlinear modeling approach is proposed to accurately capture a VM’s complex demands of multiple types of resources automatically online based on the observed workload and resource usages. Second, to enable fast adaption for resource management, the fuzzy modeling approach is integrated with a predictive-control-based controller to form a new Fuzzy Modeling Predictive Control (FMPC) approach which can quickly track the applications’ QoS targets and optimize the resource allocations under dynamic changes in the system. Finally, to address the limitations of black-box-based resource management solutions, a cross-layer optimization approach is proposed to enable cooperation between a VM’s host and guest layers and further improve the application QoS and resource usage efficiency. The above proposed approaches are prototyped and evaluated on a Xen-based virtualized system and evaluated with representative benchmarks including TPC-H, RUBiS, and TerraFly. The results demonstrate that the fuzzy-modeling-based approach improves the accuracy in resource prediction by up to 31.4% compared to conventional regression approaches. The FMPC approach substantially outperforms the traditional linear-model-based predictive control approach in meeting application QoS targets for an oversubscribed system. It is able to manage dynamic VM resource allocations and migrations for over 100 concurrent VMs across multiple hosts with good efficiency. Finally, the cross-layer optimization approach further improves the performance of a virtualized application by up to 40% when the resources are contended by dynamic workloads.

Contribuições para estratégia de controle aplicada à geração fotovoltaica interconectada à rede elétrica

Generation systems, using renewable sources, are becoming increasingly popular due to the need for increased use of electricity. Currently, renewables sources have a role to cooperate with conventional generation, due to the system limitation in delivering the required power, the need for reduction of unwanted effects from sources that use fossil fuels (pollution) and the difficulty of building new transmission and/or distribution lines. This cooperation takes place through distributed generation. Therefore, this work proposes a control strategy for the interconnection of a PV (Photovoltaic) system generation distributed with a three-phase power grid through a connection filter the type LCL. The compensation of power quality at point of common coupling (PCC) is performed ensuring that the mains supply or consume only active power and that his currents have low distorcion. Unlike traditional techniques which require schemes for harmonic detection, the technique performs the harmonic compensation without the use of this schemes, controlling the output currents of the system in an indirect way. So that there is effective control of the DC (Direct Current) bus voltage is used the robust controller mode dual DSMPI (Dual-Sliding Mode-Proportional Integral), that behaves as a sliding mode controller SM-PI (Sliding Mode-Proportional Integral) during the transition and like a conventional PI (Proportional Integral) in the steady-state. For control of current is used to repetitive control strategy, which are used double sequence controllers (DSC) tuned to the fundamental component, the fifth and seventh harmonic. The output phase current are aligned with the phase angle of the utility voltage vector obtained from the use of a SRF-PLL (Synchronous Reference Frame Phase-Locked-Loop). In order to obtain the maximum power from the PV array is used a MPPT (Maximum Power Point Tracking) algorithm without the need for adding sensors. Experimental results are presented to demonstrate the effectiveness of the proposed control system.

Controle ativo de vibração em estruturas inteligentes utilizando um controlador por modos deslizantes com compensação difusa

Smart structures and systems have the main purpose to mimic living organisms, which are essentially characterized by an autoregulatory behavior. Therefore, this kind of structure has adaptive characteristics with stimulus-response mechanisms. The term adaptive structure has been used to identify structural systems that are capable of changing their geometry or physical properties with the purpose of performing a specific task. In this work, a sliding mode controller with fuzzy inference is applied for active vibration control in an SMA two-bar truss. In order to obtain a simpler controller, a polynomial model is used in the control law, while a more sophisticated version, which presents close agreement with experimental data, is applied to describe the SMA behavior of the structural elements. This system has a rich dynamic response and can easily reach a chaotic behavior even at moderate loads and frequencies. Therefore, this approach has the advantage of not only obtaining a simpler control law, but also allows its robustness be evidenced. Numerical simulations are carried out in order to demonstrate the control system performance.

Controle ativo de vibração em estruturas inteligentes utilizando um controlador por modos deslizantes com compensação difusa

Smart structures and systems have the main purpose to mimic living organisms, which are essentially characterized by an autoregulatory behavior. Therefore, this kind of structure has adaptive characteristics with stimulus-response mechanisms. The term adaptive structure has been used to identify structural systems that are capable of changing their geometry or physical properties with the purpose of performing a specific task. In this work, a sliding mode controller with fuzzy inference is applied for active vibration control in an SMA two-bar truss. In order to obtain a simpler controller, a polynomial model is used in the control law, while a more sophisticated version, which presents close agreement with experimental data, is applied to describe the SMA behavior of the structural elements. This system has a rich dynamic response and can easily reach a chaotic behavior even at moderate loads and frequencies. Therefore, this approach has the advantage of not only obtaining a simpler control law, but also allows its robustness be evidenced. Numerical simulations are carried out in order to demonstrate the control system performance.

Digital geometric-sequence control technique for bidirectional dual active bridge DC-DC converters used in future electric vehicles

Bidirectional DC-DC converters are widely used in different applications such as energy storage systems, Electric Vehicles (EVs), UPS, etc. In particular, future EVs require bidirectional power flow in order to integrate energy storage units into smart grids. These bidirectional power converters provide Grid to Vehicle (V2G)/ Vehicle to Grid (G2V) power flow capability for future EVs. Generally, there are two control loops used for bidirectional DC-DC converters: The inner current loop and The outer loop. The control of DAB converters used in EVs are proved to be challenging due to the wide range of operating conditions and non-linear behavior of the converter. In this thesis, the precise mathematical model of the converter is derived and non-linear control schemes are proposed for the control system of bidirectional DC-DC converters based on the derived model. The proposed inner current control technique is developed based on a novel Geometric-Sequence Control (GSC) approach. The proposed control technique offers significantly improved performance as compared to one for conventional control approaches. The proposed technique utilizes a simple control algorithm which saves on the computational resources. Therefore, it has higher reliability, which is essential in this application. Although, the proposed control technique is based on the mathematical model of the converter, its robustness against parameter uncertainties is proven. Three different control modes for charging the traction batteries in EVs are investigated in this thesis: the voltage mode control, the current mode control, and the power mode control. The outer loop control is determined by each of the three control modes. The structure of the outer control loop provides the current reference for the inner current loop. Comprehensive computer simulations have been conducted in order to evaluate the performance of the proposed control methods. In addition, the proposed control have been verified on a 3.3 kW experimental prototype. Simulation and experimental results show the superior performance of the proposed control techniques over the conventional ones.

Análise e proposição de estratégias de estimação e controle de velocidade para motores de indução trifásicos

This study presents a proposal of speed servomechanisms without the use of mechanical sensors (sensorless) using induction motors. A comparison is performed and propose techniques for pet rotor speed, analyzing performance in different conditions of speed and load. For the determination of control technique, initially, is performed an analysis of the technical literature of the main control and speed estimation used, with their characteristics and limitations. The proposed technique for servo sensorless speed induction motor uses indirect field-oriented control (IFOC), composed of four controllers of the proportional-integral type (PI): rotor flux controller, speed controller and current controllers in the direct and quadrature shaft. As the main focus of the work is in the speed control loop was implemented in Matlab the recursive least squares algorithm (RLS) for identification of mechanical parameters, such as moment of inertia and friction coefficient. Thus, the speed of outer loop controller gains can be self adjusted to compensate for any changes in the mechanical parameters. For speed estimation techniques are analyzed: MRAS by rotóricos fluxes MRAS by counter EMF, MRAS by instantaneous reactive power, slip, locked loop phase (PLL) and sliding mode. A proposition of estimation in sliding mode based on speed, which is performed a change in rotor flux observer structure is displayed. To evaluate the techniques are performed theoretical analyzes in Matlab simulation environment and experimental platform in electrical machinery drives. The DSP TMS320F28069 was used for experimental implementation of speed estimation techniques and check the performance of the same in a wide speed range, including load insertion. From this analysis is carried out to implement closed-loop control of sensorless speed IFOC structure. The results demonstrated the real possibility of replacing mechanical sensors for estimation techniques proposed and analyzed. Among these, the estimator based on PLL demonstrated the best performance in various conditions, while the technique based on sliding mode has good capacity estimation in steady state and robustness to parametric variations.

Quantum Gate and Quantum State Preparation through Neighboring Optimal Control

Successful implementation of fault-tolerant quantum computation on a system of qubits places severe demands on the hardware used to control the many-qubit state. It is known that an accuracy threshold Pa exists for any quantum gate that is to be used for such a computation to be able to continue for an unlimited number of steps. Specifically, the error probability Pe for such a gate must fall below the accuracy threshold: Pe < Pa. Estimates of Pa vary widely, though Pa ∼ 10−4 has emerged as a challenging target for hardware designers. I present a theoretical framework based on neighboring optimal control that takes as input a good quantum gate and returns a new gate with better performance. I illustrate this approach by applying it to a universal set of quantum gates produced using non-adiabatic rapid passage. Performance improvements are substantial comparing to the original (unimproved) gates, both for ideal and non-ideal controls. Under suitable conditions detailed below, all gate error probabilities fall by 1 to 4 orders of magnitude below the target threshold of 10−4. After applying the neighboring optimal control theory to improve the performance of quantum gates in a universal set, I further apply the general control theory in a two-step procedure for fault-tolerant logical state preparation, and I illustrate this procedure by preparing a logical Bell state fault-tolerantly. The two-step preparation procedure is as follow: Step 1 provides a one-shot procedure using neighboring optimal control theory to prepare a physical qubit state which is a high-fidelity approximation to the Bell state |β01⟩ = 1/√2(|01⟩ + |10⟩). I show that for ideal (non-ideal) control, an approximate |β01⟩ state could be prepared with error probability ϵ ∼ 10−6 (10−5) with one-shot local operations. Step 2 then takes a block of p pairs of physical qubits, each prepared in |β01⟩ state using Step 1, and fault-tolerantly prepares the logical Bell state for the C4 quantum error detection code.

Modeling, control and field tests on an experimental irrigation canal

Irrigation canals are complex hydraulic systems difficult to control. Many models and control strategies have already been developed using linear control theory. In the present study, a PI controller is developed and implemented in a brand new prototype canal and its features evaluated experimentally. The base model relies on the linearized Saint-Venant equations which is compared with a reservoir model to check its accuracy. This technique will prove its capability and versatility in tuning properly a controller for this kind of systems.