Bahram Shafai

This paper considers the problem of the load frequency control of power systems when system states are not directly available for implementation and in the presence of unknown disturbances. The conventional proportional observer (PO) fails to solve this problem unless the disturbances are known or can be explicitly modeled. Therefore, we provide a detailed analysis of the proportional integral observer (PIO) and its generalization (GPIO) for the load frequency control (LFC) of a single-area power system. This study demonstrates that both observers can be reliably employed, depending on the scenarios of system dynamics. Since they are able to estimate both the states and unknown disturbances, they can be integrated in LFC with disturbance accommodation to ensure the system stability and to satisfy the specified performance measures. Numerical examples are given to illustrate the advantage of GPI observer-based LFC for a single-area power system model.

This paper considers the analysis of dynamic systems represented by state space models and general differential equations incorporating input derivatives. First, the connection between the class of systems with derivative inputs and singular systems is established. An elimination procedure for input derivatives is given, which transfers the derivative terms from the state equation to the output equation allowing stabilization by state feedback to be performed. Second, we consider the general differential equations with derivatives of inputs and outputs and derive an equivalent state space description in standard form, which incorporates the derivatives in the state variables. This is essential since a suitable feedback configuration should involve both input and output as well as their derivatives. We provide an appropriate state space model that allows stabilization by state feedback controller to be performed. Finally, a subclass of positive system involving input derivatives is considered as a special case. It is shown that stabilization of input derivative positive system can be achieved through its equivalent positive system in standard form using LMI. Numerical examples are included to support the theoretical results.

We propose a novel, heterogeneous multi-agent architecture that miniaturizes rovers by outsourcing power generation to a central hub. By delegating power generation and distribution functions to this hub, the size, weight, power, and cost (SWAP-C) per rover are reduced, enabling efficient fleet scaling. As these rovers conduct mission tasks around the terrain, the hub charges an array of replacement battery modules. When a rover requires charging, it returns to the hub to initiate an autonomous docking sequence and exits with a fully charged battery. This confers an advantage over direct charging methods, such as wireless or wired charging, by replenishing a rover in minutes as opposed to hours, increasing net rover uptime. This work shares an open-source platform developed to demonstrate battery swapping on unknown field terrain. We detail our design methodologies utilized for increasing system reliability, with a focus on optimization, robust mechanical design, and verification. Optimization of the system is discussed, including the design of passive guide rails through simulation-based optimization methods which increase the valid docking configuration space by 258%. The full system was evaluated during integrated testing, where an average servicing time of 98 seconds was achieved on surfaces with a gradient up to 10°. We conclude by briefly proposing flight considerations for advancing the system toward a space-ready design. In sum, this prototype represents a proof of concept for autonomous docking and battery transfer on field terrain, advancing its Technology Readiness Level (TRL) from 1 to 3.