Katherin Indriawati

2papers

2 Papers

22.7SYApr 6
Adaptive Kalman Filtering with Exact Linearization and Decoupling Control on Three-Tank Process

Bambang L. Widjiantoro, Katherin Indriawati, Moh Kamalul Wafi

Water treatment and liquid storage are the two plants implementing the hydraulic three-tank system. Maintaining certain levels is the critical scenario so that the systems run as desired. To deal with, the optimal linear control and the complex advanced non-linear problem have been proposed to track certain dynamic reference. This paper studies those two using the combination of linearization and decoupling control under some assumptions. The result shows that the designed methods have successfully traced the dynamic reference signals. Beyond that, the adaptive system noise Kalman filter (AKF) algorithm is used to examine the estimation performance of the true non-linear system and the performance yields a rewarding prediction of the true system.

4.7SYApr 5
Cooperative Observer-Based $\mathcal{H}_\infty$ Fault-Tolerant Tracking Control for Networked Processes with Sensor Faults

Moh Kamalul Wafi, Yurid E. Nugraha, Bambang L. Widjiantoro et al.

This paper develops a cooperative fault-tolerant control framework for heterogeneous networked linear systems subject to sensor degradation and external disturbances. Each unit employs an augmented $\mathcal{H}_\infty$ observer that jointly reconstructs its state and sensor fault, providing disturbance-attenuated estimation guarantees. An inner state-feedback gain is then synthesized via convex $\mathcal{H}_\infty$ LMIs to ensure robust closed-loop stabilization, while an outer distributed integral action drives all units to track a constant setpoint source. The resulting network error dynamics satisfy an input-to-state stability condition with respect to disturbances and estimation imperfections, and converge to zero in their absence. Simulations on star, cyclic, and path topologies with heterogeneous agents confirm reliable tracking despite abrupt sensor faults and bounded disturbances, demonstrating a scalable and resilient coordination strategy for multi-agent systems with sensing imperfections.