Sungkyunkwan University · Engineering
Professor R. Sakthivel's research lab specializes in advanced control theory and stochastic systems, with a focus on fractional-order dynamics, impulsive systems, and fuzzy modeling. The lab investigates resilient, fault-tolerant, and robust control strategies for complex systems under uncertainties such as time delays, actuator faults, and stochastic disturbances. Key research directions include approximate controllability of stochastic and impulsive systems, reliable H∞ and passivity-based control, and the development of LMI-based stabilization techniques for Markovian jump and Takagi-Sugeno fuzzy systems. The lab emphasizes theoretical rigor combined with practical applicability through numerical validation and real-world system modeling.
Figures are computed from collected data and may differ slightly.
In this paper, we investigate the approximate controllability of fractional stochastic differential inclusions with nonlocal conditions. In particular, we obtain a new set of sufficient conditions for the approximate controllability of nonlinear fractional stochastic differential inclusions under the assumption that the corresponding linear system is approximately controllable. In addition, we establish the approximate controllability results for the fractional stochastic control system with inf
This paper is concerned with the problem of reliable mixed H ∞ and passivity-based control for a class of stochastic Takagi-Sugeno (TS) fuzzy systems with Markovian switching and probabilistic time varying delays. Different from the existing works, the H∞ and passivity control problem with probabilistic occurrence of time-varying delays and actuator failures is considered in a unified framework, which is more general in some practical situations. The main aim of this paper is to design a reliabl
This brief investigates the problem of passivity-based resilient sampled-data control for Markovian jump systems subject to actuator faults via an adaptive fault-tolerant mechanism. By constructing a proper Lyapunov function, a set of sufficient conditions is obtained in terms of linear matrix inequalities (LMIs), which ensures that the closed-loop system is stochastically passive. In order to reflect the imprecision in controller, the additive gain variations is considered. Then, the resilient
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