Advances in Control of Uncertain Dynamical Systems with Optimal and Adaptive Approaches

<p>"This research starts with designing optimal control for uncertain systems, adding the adaptive control input to suppress the uncertainty. It then follows with designing the optimal control for state constraint, designing the optimal nonlinear reference model, designing adaptive control to handle state constraint and uncertainty. Finally, it designs the finite-time controller for uncertain multiagent systems.</p> <p>It is well known that the design of the control algorithm for an uncertain dynamical system is not trivial. Motivated by this standpoint, this study focuses on optimal and adaptive control approaches with stability and performance guarantees for uncertain sole and multiagent dynamical systems. From the different perspectives of the controller design, designing the proper control input with the optimal method and suppressing the uncertain part with adaptive control are considered. An adaptive guidance/control method is also presented that has the capability to land the aircraft safely once a fault has occurred. Then, the extension of optimal control with state constraint is considered based inverse optimal control formulation with a set-theoretic barrier Lyapunov function (STBLF). The optimal nonlinear reference model with the $\Theta$-D method is also proposed since linear reference model may not provide desired behavior of these systems. Another challenge in state constraint problems is that the dynamical system also has uncertainty. To solve both state constraint and uncertainty problems together, a new set-theoretic model reference adaptive control is further proposed with an adaptive control approach for uncertain nonlinear systems. Finally, the nonlinear reference model is proposed for multiagent systems with finite-time stability guarantees using a distributed adaptive control approach.</p> <p>To conclude, the proposed new optimal and adaptive control methods are introduced with stability analysis using the optimal solution and Lyapunov stability. The efficacy of the proposed methods is further demonstrated with illustrative numerical and experimental results"--Abstract, p. iv</p>

Name thesis:degree_name

Ph. D. in Mechanical Engineering

Grantor

Missouri University of Science and Technology

Author dc:creator

• Deniz, Meryem

• Adaptive control
• Finite-time
• Nonlinear reference model
• Optimal control
• Engineering
• Mechanical Engineering

Repository record dc:identifier

https://scholarsmine.mst.edu/doctoral_dissertations/3196

OAI identifier oai:identifier

oai:scholarsmine.mst.edu:doctoral_dissertations-4201