Alireza Seyedi

SY
3papers
52citations
Novelty45%
AI Score22

3 Papers

OCJan 23, 2014
Stabilization of Networked Control Systems with Sparse Observer-Controller Networks

Mohammad Razeghi-Jahromi, Alireza Seyedi

In this paper we provide a set of stability conditions for linear time-invariant networked control systems with arbitrary topology, using a Lyapunov direct approach. We then use these stability conditions to provide a novel low-complexity algorithm for the design of a sparse observer-based control network. We employ distributed observers by employing the output of other nodes to improve the stability of each observer dynamics. To avoid unbounded growth of controller and observer gains, we impose bounds on their norms. The effects of relaxation of these bounds is discussed when trying to find the complete decentralization conditions.

SYNov 19, 2015
Bounded Stability in Networked Systems with Parameter Mismatch and Adaptive Decentralized Estimation

Saeed Manaffam, Alireza Seyedi, Azadeh Vosoughi et al.

Here, we study the ultimately bounded stability of network of mismatched systems using Lyapunov direct method. The upper bound on the error of oscillators from the center of the neighborhood is derived. Then the performance of an adaptive compensation via decentralized control is analyzed. Finally, the analytical results for a network of globally connected Lorenz oscillators are verified.

SYJul 22, 2016
Synchronization in Networked Systems with Parameter Mismatch: Adaptive Decentralized and Distributed Controls

Saeed Manaffam, Alireza Seyedi, Azadeh Vosoughi et al.

Here, we study the ultimately bounded stability of network of mismatched systems using Lyapunov direct method. We derive an upper bound on the norm of the error of network states from its average states, which it achieves in finite time. Then, we devise a decentralized compensator to asymptotically pin the network of mismatched systems to a desired trajectory. Next, we design distributed estimators to compensate for the mismatched parameters performances of adaptive decentralized and distributed compensations are analyzed. Our analytical results are verified by several simulations in a network of globally connected Lorenz oscillators.