Stabilization of a synchronous generator with a controllable series capacitor via immersion and invariance

The immersion and invariance (I&I) technique (it IEEE Trans. Automat. Control 2003; 48 (4):590–606) is a recently proposed control methodology for stabilizing nonlinear systems. Here we apply this philosophy to stabilize a single machine infinite bus (SMIB) system using a controllable series capacitor (CSC). The synchronous generator is modeled using the second‐order swing equation and a first‐order model is used for the CSC. The control objective here is to immerse a desired second‐order dynamic model into the higher order system manifold and design an asymptotically stabilizing control law. Copyright © 2011 John Wiley & Sons, Ltd.     

Deriving Long-Term Value from Context-Aware Computing

Modern businesses are increasingly dynamic in nature, which creates a need for computer systems that can sense and respond to rapid changes in the environment, or “context,” of the enterprise. This article presents the authors' vision of a context “ecosystem” that helps enterprises, applications, and developers respond to these dynamic changes and derive long-term value from context information. the ecosystem includes providers of raw context information, components that derive more abstract context information from lower level sources, middleware that provides systematic context services to applications, development tools, and contextaware applications.     

Extremum seeking loops with quadratic functions: Estimation and control

Extremum-seeking (also peak-seeking ) controllers are designed to operate at an a priori unknown set-point that extremizes the value of a performance function. Traditional approaches to the problem assume a time-scale separation between the gradient computation and function minimization and the system dynamics. The work here, in contrast, assumes that the performance function can be approximated by a quadratic function with a finite number of parameters. These parameters are estimated on-line and the extremum seeking controller operates based on these estimated values. A significant advantage of a quadratic function is that it allows the peak-seeking control loop to be reduced to a linear system. For such a loop, the wealth of linear system analysis and synthesis tools can be employed. First, the control loop is analysed assuming that the parameters in the function are known (full information case) and then when the parameters are estimated on line (the partial information case).     

A swing-up of the acrobot based on a simple pendulum strategy

We propose a control law to swing-up the acrobot from an initial domain to a neighbourhood of the vertically upward equilibrium position. The methodology involves reducing the system to a one degree-of-freedom system, much like a simple pendulum, evolving on a critical value of the energy level set. The system is guaranteed to converge to a neighbourhood of the upward equilibrium position about which a linear feedback controller is switched on to stabilize the system.     

LQG controller designs from reduced order models for a launch vehicle

The suppression of liquid fuel slosh motion is critical in a launch vehicle (LV). In particular, during certain stages of the launch, the dynamics of the fuel interacts adversely with the rigid body dynamics of the LV and the feedback controller must attentuate these effects. This paper describes the effort of a multivariable control approach applied to the Geosynchronous Satellite Launch Vehicle (GSLV) of the Indian Space Research Organization (ISRO) during a certain stage of its launch. The fuel slosh dynamics are modelled using a pendulum model analogy. We describe two design methodologies using the Linear-Quadratic Gaussian (LQG) technique. The novelty of the technique is that we apply the LQG design for models that are reduced in order through inspection alone. This is possible from a perspective that the LV could be viewed as many small systems attached to a main body and the interactions of some of these smaller systems could be neglected at the controller design stage provided sufficient robustness is ensured by the controller. The first LQG design is carried out without the actuator dynamics incorporated at the design stage and for the second design we neglect the slosh dynamics as well.