Date of Award

6-2025

Degree Name

MS in Electrical Engineering

Department/Program

Electrical Engineering

College

College of Engineering

Advisor

Jason Poon

Advisor Department

Electrical Engineering

Advisor College

College of Engineering

Abstract

This thesis presents the design, implementation, and analysis of a hardware system for solving Linearly Constrained Quadratic Programs (LCQPs) in real time. The architecture follows a generalized feedback structure composed of three key elements: gradient descent on the quadratic cost function, saturation-based nonlinearity to enforce inequality constraints, and an integral controller with an anti-windup mechanism to regulate dynamic behavior and determine steady-state error. This majority analog system converges with equilibria that satisfy the Karush-Kuhn-Tucker (KKT) optimality conditions. Using a representative LCQP, this work presents simulation of the circuit in PLECS and LT Spice to confirm the feasibility of the novel architecture presented. In addition, a hardware implementation was designed on a printed circuit board (PCB) and tested in terms of accuracy and convergence speed, achieving equilibrium values within 0.5% error of the theoretical solutions and at speeds that rivals other hardware prototypes of its kind. These promising results lay the groundwork for the next phase of development: a VLSI-based implementation aimed at achieving even higher levels of integration and computational efficiency. Ultimately, this work contributes to the growing body of research on analog computing architectures that synthesize control, optimization, and computation in physical hardware.

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