Mayank Baranwal

Robust decentralized voltage control of DC-DC converters with applications to power sharing and ripple sharing

This paper addresses the problem of output voltage regulation for multiple DC-DC converters connected to a grid, and prescribes a robust scheme for sharing power among different sources. Also it develops a method for sharing 120 Hz ripple among DC power sources in a prescribed proportion, which accommodates the different capabilities of DC power sources to sustain the ripple. We present a decentralized control architecture, where a nested (inner-outer) control design is used at every converter. An interesting aspect of the proposed design is that the analysis and design of the entire multi-converter system can be done using an equivalent single converter system, where the multi-converter system inherits the performance and robustness achieved by a design for the single-converter system. Another key aspect of this work is that the voltage regulation problem is addressed as a disturbance-rejection problem, where unknown load current is viewed as an external signal, and thus, no prior information is required on the nominal loading conditions. The control design is obtained using robust optimal-control framework. Case studies presented show the enhanced performance of prescribed optimal controllers.

ABNORMAL MOTION DETECTION IN REAL TIME USING VIDEO SURVEILLANCE AND BODY SENSORS

This paper presents a method for detecting abnormal motion in real time using a computer vision system. The method is based on the modeling of human body image, which takes into account both orientation and velocity of prominent body parts. A comparative study is made of this method with other existing algorithms based on optical flow and the use of accelerometer body sensors. From the real time experiments conducted in the present work, the developed method is found to be efficient in characterizing human motion and classifying it into basic types such as falling, sitting, and walking. The method uses a Radial Basis Function Network (RBFN) to compute the severity coefficient associated with the type of motion, based on experience. The paper evaluates the various methods and incorporates the advantages of other methods in order to develop a more reliable system for abnormal motion detection.

Vehicle Routing Problem with Time Windows: A Deterministic Annealing approach

The Vehicle Routing Problem with Time-Windows (VRPTW) is an important problem in allocating resources on networks in time and space. We present in this paper a Deterministic Annealing (DA)-based approach to solving the VRPTW with its aspects of routing and scheduling, as well as to model additional constraints of heterogeneous vehicles and shipments. This is the first time, to our knowledge, that a DA approach has been used for problems in the class of the VRPTW. We describe how the DA approach can be adapted to generate an effective heuristic approach to the VRPTW. Our DA approach is also designed to not get trapped in local minima, and demonstrates less sensitivity to initial solutions. The algorithm trades off routing and scheduling in an n-dimensional space using a tunable parameter that allows us to generate qualitatively good solutions. These solutions differ in the degree of intersection of the routes, making the case for transfer points where shipments can be exchanged. Simulation results on randomly generated instances show that the constraints are respected and demonstrate near optimal results (when verifiable) in terms of schedules and tour length of individual tours in each solution.

Robust atomic force microscopy using multiple sensors

Atomic force microscopy typically relies on high-resolution high-bandwidth cantilever deflection measurements based control for imaging and estimating sample topography and properties. More precisely, in amplitude-modulation atomic force microscopy (AM-AFM), the control effort that regulates deflection amplitude is used as an estimate of sample topography; similarly, contact-mode AFM uses regulation of deflection signal to generate sample topography. In this article, a control design scheme based on an additional feedback mechanism that uses vertical z-piezo motion sensor, which augments the deflection based control scheme, is proposed and evaluated. The proposed scheme exploits the fact that the piezo motion sensor, though inferior to the cantilever deflection signal in terms of resolution and bandwidth, provides information on piezo actuator dynamics that is not easily retrievable from the deflection signal. The augmented design results in significant improvements in imaging bandwidth and robustness, especially in AM-AFM, where the complicated underlying nonlinear dynamics inhibits estimating piezo motions from deflection signals. In AM-AFM experiments, the two-sensor based design demonstrates a substantial improvement in robustness to modeling uncertainties by practically eliminating the peak in the sensitivity plot without affecting the closed-loop bandwidth when compared to a design that does not use the piezo-position sensor based feedback. The contact-mode imaging results, which use proportional-integral controllers for cantilever-deflection regulation, demonstrate improvements in bandwidth and robustness to modeling uncertainties, respectively, by over 30% and 20%. The piezo-sensor based feedback is developed using H∞ control framework.

Clustering with capacity and size constraints: A deterministic approach

This paper discusses a deterministic clustering approach to capacitated resource allocation problems. In particular, the Deterministic Annealing (DA) algorithm from the data-compression literature, which bears a distinct analogy to the phase transformation under annealing process in statistical physics, is adapted to address problems pertaining to clustering with several forms of size constraints. These constraints are addressed through appropriate modifications of the basic DA formulation by judiciously adjusting the free-energy function in the DA algorithm. At a given value of the annealing parameter, the iterations of the DA algorithm are of the form of a Descent Method, which motivate scaling principles for faster convergence.

Fast and robust control of nanopositioning systems: Performance limits enabled by field programmable analog arrays

This paper aims at control design and its implementation for robust high-bandwidth precision (nanoscale) positioning systems. Even though modern model-based control theoretic designs for robust broadband high-resolution positioning have enabled orders of magnitude improvement in performance over existing model independent designs, their scope is severely limited by the inefficacies of digital implementation of the control designs. High-order control laws that result from model-based designs typically have to be approximated with reduced-order systems to facilitate digital implementation. Digital systems, even those that have very high sampling frequencies, provide low effective control bandwidth when implementing high-order systems. In this context, field programmable analog arrays (FPAAs) provide a good alternative to the use of digital-logic based processors since they enable very high implementation speeds, moreover with cheaper resources. The superior flexibility of digital systems in terms of the implementable mathematical and logical functions does not give significant edge over FPAAs when implementing linear dynamic control laws. In this paper, we pose the control design objectives for positioning systems in different configurations as optimal control problems and demonstrate significant improvements in performance when the resulting control laws are applied using FPAAs as opposed to their digital counterparts. An improvement of over 200% in positioning bandwidth is achieved over an earlier digital signal processor (DSP) based implementation for the same system and same control design, even when for the DSP-based system, the sampling frequency is about 100 times the desired positioning bandwidth.

DC bus voltage regulation using photovoltaic module: A non-iterative method

Uncertainties in load power demand and unpredictabilities associated with renewable energy sources pose challenges to current microgrids. The situation worsens when the maximum power generated by a Photovoltaic (PV) module exceeds the power demanded by the load. The excess power increases the voltage at the point of common coupling (PCC). This paper addresses the issue of DC-link voltage regulation using a standalone PV module for the scenario when PV output at maximum power point (MPP) exceeds load demands. In particular, the time-scale separation between the fast PV dynamics and the slow variations in weather (temperature and irradiance) conditions is exploited to devise a novel non-iterative control strategy with fast closed-loop dynamics. A disturbance-rejection based robust control framework is employed and the closed-loop voltage regulation and load disturbance rejection performances are compared for the constant current and the constant voltage modes of operation of a PV module. Simulation case studies are presented which examine effectiveness and robustness of controllers for voltage regulation at the PCC.

Multiple traveling salesmen and related problems: A maximum-entropy principle based approach

This paper presents a new heuristic approach for multiple traveling salesmen problem (mTSP) and other variants of the TSP. In this approach, the TSP and its variants are seen as constrained resource allocation problems, where an ordered set of resources is associated to the cities, and the allocation is done through an iterative algorithm in such a way that eventually each city gets associated with a resource. The approach allows adding constraints on resources which translate to objectives such as minimum tour length (or multiple tour lengths as in mTSP) and other constraints that define the variants on the TSP problem. The algorithm for the associated resource allocation problem is based on maximum entropy principle (MEP) and the deterministic annealing algorithm. Besides mTSP, this article demonstrates this approach for close enough traveling salesman problem (CETSP), which is known to be computationally challenging since there is a continuum of possible edges between a pair of cities. The examples presented in this paper illustrate the effectiveness of this new framework for use in TSP and many variants thereof. Simulations demonstrate that the proposed MEP algorithm achieves significantly better solutions than the ones provided by the most commonly used simulated annealing algorithm with only marginal increase in run-time.

A robust scheme for distributed control of power converters in DC microgrids with time-varying power sharing

This paper addresses the problem of output voltage regulation for multiple DC/DC converters connected to a microgrid, and prescribes a scheme for sharing power among different sources. This architecture is structured in such a way that it admits quantifiable analysis of the closed-loop performance of the network of converters; the analysis simplifies to studying closed-loop performance of an equivalent single-converter system. The proposed architecture allows for the proportion in which the sources provide power to vary with time; thus overcoming limitations of our previous designs in [1]. Additionally, the proposed control framework is suitable to both centralized and decentralized implementations, i.e., the same control architecture can be employed for voltage regulation irrespective of the availability of common load-current (or power) measurement, without the need to modify controller parameters. The performance becomes quantifiably better with better communication of the demanded load to all the controllers at all the converters (in the centralized case); however guarantees viability when such communication is absent. Case studies comprising of battery, PV and generic sources are presented and demonstrate the enhanced performance of prescribed optimal controllers for voltage regulation and power sharing.

A decentralized scalable control architecture for islanded operation of parallel DC/AC inverters with prescribed power sharing

This paper addresses the problem of output voltage regulation at the point of common coupling (PCC) for multiple single-phase DC/AC inverters connected to a microgrid in islanded mode, and prescribes a robust decentralized scheme for sharing power among different sources. The problem of regulating voltage at PCC is posed as a disturbance-rejection problem, where the load current is regarded as an unknown disturbance signal and thus no assumptions are made regarding the power demanded by the load at the PCC. The disturbance-rejection controller has an inner-outer cascaded structure, where inner-current controller is parameterized by coupling inductance of the inverter, and is such that the inner-loop seen by the outer-voltage controller is identical for all the parallel inverters. This favors scalability by allowing multiple inverters to be added to the PCC without the need to separately design outer-loop controllers for individual inverters. A significant feature of the proposed control architecture is that the stability and performance analysis of the multi-inverter network is tractable; in fact, analysis can be done in terms of an equivalent single-inverter system. Case studies presented in this paper demonstrate the effectiveness of the proposed design in terms of voltage regulation, power sharing and robustness to parametric and modeling uncertainties.