Date of Award


Document Type



Santa Clara : Santa Clara University, 2016.

Degree Name

Master of Science (MS)


Mechanical Engineering

First Advisor

Mohammad A. Ayoubi


This study presents various fuzzy type controllers for a solar sail. First, a Twin Parallel Distributed Compensator (TPDC) is built for a Takagi-Sugeno fuzzy model of the solarsail. The T-S fuzzy model is constructed by linearizing the existing nonlinear equations fo motion of the solar sail. The T-S fuzzy model is used to solve a set of linear matrix inequalities to derive state feedback controller gains. The TPDC controls the solar sail using a combination of reaction wheels and roll stabilizer bars for attitude control and trim masses for disturbance rejection. The TPDC tracks and stabilizes the solar sail to any desired state in the presence of parameter uncertainties and external disturbances while satisfying actuator constraints. The performance of the TPDC is compared to a Ziegler-Nichols tuned proportional-integral-derivative (PID) controller. Numerical simulation shows the TPDC outperforms he PID controller when stabilizing the solar sail to a desired state. When compared to the particle swarm optimized PID controller, the TPDC has a slower response, irrespective of the initial conditions and desired states. To control the solar sail using trim masses, a hybrid fuzzy-logic supervisor with a PID attitude controller is built. Particle swarm optimization is also used to obtain gains for roll, pitch and yaw PID controllers. The calculated PID gains are used to build a fuzzy supervisor that tunes the PID controller gains based on the Euler angle error and error rate. The proposed PID controller stabilizes the solar sail about any commanded input from any initial condition. The supervisory fuzzy PID controller is shown to be robust model uncertainties and outperforms a particle swarm optimized PID controller when stabilized about a non-optimal state from a non-optimal initial condition.