Soumitri N. Kolavennu

Robust state feedback synthesis for control of non-square multivariable nonlinear systems

Abstract In this paper, a robust nonlinear controller is designed in the Input/Output (I/O) linearization framework, for non-square multivariable nonlinear systems that have more inputs than outputs and are subject to parametric uncertainty. A nonlinear state feedback is synthesized that approximately linearizes the system in an I/O sense by solving a convex optimization problem online. A robust controller is designed for the linear uncertain subsystem using a multi-model H 2 H ∞ synthesis approach to ensure robust stability and performance of non-square multivariable, nonlinear systems. This methodology is illustrated via simulation of a regulation problem in a continuous stirred tank reactor.

Robust control of I/O linearizable systems via multi-model H2/H∞ synthesis

Abstract Linearization of the input–output response of a nonlinear system via state feedback has found many applications in control of nonlinear processes. However, in the presence of uncertainties, this approach leads to inexact linearization and results in the loss of performance and stability. In this paper, a controller design methodology is developed based on input/output linearization and multi-objective H 2 /H ∞ synthesis that ensures robust stability and performance. This methodology is illustrated via simulation of a regulation problem in a continuous stirred tank reactor.

Robust controller design for multivariable nonlinear systems via multi-model H2/H∞ synthesis

Input/output (I/O) linearization via state feedback provides a convenient framework for designing controllers for multivariable nonlinear systems. However this approach does not account for parametric uncertainty which may lead to loss of stability and performance degradation. In this paper, a multi-model H2/H∞ approach is utilized to design a robust controller for minimum phase multivariable nonlinear systems that are subject to parametric uncertainty. It is first shown that a state feedback (inner loop) based on nominal parameters introduces nonlinear perturbations to the linear sub-system and results in loss of decoupling. The uncertain system is characterized in a form that provides a framework for robust controller design. Recent results from linear robust control theory are utilized to design an outer-loop controller to account for the parametric uncertainty. This methodology is illustrated via simulation of a regulation problem in a continuous stirred tank reactor.

Chaotic Routing: A Set-based Broadcasting Routing Framework for Wireless Sensor Networks

Data communication in wireless sensor networks (WSNs) exhibits distinctive characteristics. Routing in WSNs still relies on simple variations of traditional distance vector or link state based protocols, thus suffering low throughput and less robustness. Drawing intuitions from the Brownian motions where localized momentum exchanges enable global energy diffusion, we propose an innovative routing protocol, chaotic routing (CR), which achieves efficient information diffusion with seemingly chaotic local information exchanges. Leveraging emerging networking concepts such as potential based routing, opportunistic routing and network coding, CR improves throughput via accurate routing cost estimation, opportunistic data forwarding and localized node scheduling optimizing information propagation in mesh structures. Through extensive simulations, we prove that CR outperforms, in terms of throughput, best deterministic routing scheme (i.e. best path routing) by a factor of around 300% and beats the best opportunistic routing scheme (i.e. MORE) by a factor of around 200%. CR shows stable performance over wide range of network densities, link qualities and batch sizes.

Synthesis of robust controllers for nonsquare multivariable nonlinear systems

Input/output linearization via state feedback provides a convenient framework for designing controllers for multivariable nonlinear systems. However, in the presence of parametric uncertainty, this approach leads to inexact linearization as well as loss of decoupling. This could result in loss of performance and stability. In this paper, a controller design methodology is developed based on input/output linearization and multiobjective H/sub 2//H/sub /spl infin// synthesis that ensures robust stability and performance of nonsquare multivariable, nonlinear systems. This methodology is illustrated via simulation of a regulation problem in a continuous stirred tank reactor.

Nonlinear Controller Design by Uncovering Linear Dynamics Hidden by Input-Output Linearization

Abstract A great deal of research has addressed the problem of explicitly linearizing the input-output response of a nonlinear system via state feedback. However, this approach can often hide linear dynamics that could be useful for controller design. A controller design methodology is developed based on a coordinate transformation that uncovers the linear dynamics hidden by conventional input-output linearization. This methodology is illustrated via simulation of a CSTR example and it is shown that this controller performance is better than the performance of a standard input-output linearization approach.

Localization in Wireless Sensor Networks

Within wireless sensor networks, the location of the sensor can be a critical attribute of the data sensed. A device knowing its relative position to the other devices in the wireless network or its absolute position with respect to a map increases the value of the data sensed. Sensing the precise location of wireless devices has been a topic of serious study for some time. A number of methods and techniques have been suggested, using various physical attributes (IR, acoustic, time of flight); however, we have chosen to emphasize received signal strength (RSS), which is simple to implement and uses the signal strength sampling capability used by the network layer of a wireless network. Using algorithms such as fingerprinting and multilateration, a reasonably accurate position estimate can be established depending on the density of the network devices and the environment in which they must operate. We discuss the previous work in RSS localization and describe the limitations of these algorithms from a practical and an experimental perspective. We will conclude with a discussion of our work using these algorithms in 3 wireless network test beds constructed in an industrial refinery and an office environment.

Robust nonlinear control of nonsquare multivarlable systems

Abstract In this paper, a nonlinear controller is designed in the Input/Output (I/O) linearization framework, for non-square multivariable nonlinear systems that are subject to parametric uncertainty. A non linear state feedback is synthesized that approximately linearizes the system in an I/O sense by solving a convex optimization problem online. A robust controller is designed for the linear uncertain subsystem using a multi-objective H2/H∞ synthesis approach to ensure robust stability and performance of nons quare multivariable, nonlinear systems. This methodology is illustrated via simulation of a regulation problem in a continuous stirred tank reactor.

Synthesis of robust nonlinear state feedback for regulation of uncertain MIMO systems

Abstract Linearization of the input-output response of a nonlinear system via state feedback has found many applications in control of nonlinear processes. However, in the presence of uncertainties, this approach leads to inexact linearization and results in loss of performance and stability. In this paper, a controller design methodology is developed based on Input/Output linearization and multi-objective H 2 / H ∞ synthesis that ensures robust stability and performance MIMO nonlinear systems.