Date of Award


Document Type


Degree Name

Doctor of Philosophy (PhD)


Electrical Engineering

First Advisor

Hamid Ossareh

Second Advisor

Taras Lakoba


Control systems that are subject to constraints due to physical limitations, hardware

protection, or safety considerations have led to challenging control problems that have

piqued the interest of control practitioners and theoreticians for many decades. In

general, the design of constraint management schemes must meet several stringent

requirements, for example: low computational burden, performance, recovery mechanisms

from infeasibility conditions, robustness, and formulation simplicity. These

requirements have been particularly difficult to meet for the following three classes

of systems: stochastic systems, linear systems driven by unmodeled disturbances,

and nonlinear systems. Hence, in this work, we develop three constraint management

schemes, based on Reference Governor (RG), for these classes of systems. The

first scheme, which is referred to as Stochastic RG, leverages the ideas of chance

constraints to construct a Stochastic Robustly Invariant Maximal Output Admissible

set (SR-MAS) in order to enforce constraints on stochastic systems. The second

scheme, which is called Recovery RG (RRG), addresses the problem of recovery from

infeasibility conditions by implementing a disturbance observer to update the MAS,

and hence recover from constraint violations due to unmodeled disturbances. The

third method addresses the problem of constraint satisfaction on nonlinear systems

by decomposing the design of the constraint management strategy into two parts: enforcement

at steady-state, and during transient. The former is achieved by using the

forward and inverse steady-state characterization of the nonlinear system. The latter

is achieved by implementing an RG-based approach, which employs a novel Robust

Output Admissible Set (ROAS) that is computed using data obtained from the nonlinear

system. Added to this, this dissertation includes a detailed literature review

of existing constraint management schemes to compare and highlight advantages and

disadvantages between them. Finally, all this study is supported by a systematic

analysis, as well as numerical and experimental validation of the closed-loop systems

performance on vehicle roll-over avoidance, turbocharged engine control, and inverted

pendulum control problems.



Number of Pages

188 p.