Abstract: Methods, systems, and computer readable media to control a cyber physical system using an observer-based controller are described. The observer-based controller including a detector to determine an occurrence of an attack on the cyberphysical system and to inform the observer-based controller via a signal. An observer estimates a system state of the cyberphysical system based on at least partial information about the cyber physical system. The observer-based controller is configured with a predetermined observer gain and controller gain. The observer-based controller is configured to control the cyberphysical system using an estimated error determination that is altered depending on a type of cyber attack. The observer-based controller is configured to control the cyberphysical system subjected to cyber attacks in both a forward channel connecting at least one sensor with the observer and a backward channel connecting the observer-based controller with actuators.

Abstract: Methods, systems, and computer readable media to control a cyber physical system using an observer-based controller are described.

Abstract: Methods, systems, and computer readable media to control a cyber physical system using an observer-based controller are described.

Abstract: In the control method for mobile parallel manipulators, kinematic singularity and redundancy are solved through joint limits avoidance and manipulability criteria. By taking the MPM self-motion into consideration due to its redundancy, the inverse kinematic is derived using a hybrid neuro-fuzzy system, such as NeFIK. The discrete augmented Lagrangian (AL) technique is used to solve the highly nonlinear constrained multi-objective optimal control problem. An adaptive neuro-fuzzy inference system (ANFIS)-based structure (based on the result of the AL solution) is used to solve the online trajectory planning of the MPM.

Abstract: In the control method for mobile parallel manipulators, kinematic singularity and redundancy are solved through joint limits avoidance and manipulability criteria. By taking the MPM self-motion into consideration due to its redundancy, the inverse kinematic is derived using a hybrid neuro-fuzzy system, such as NeFIK. The discrete augmented Lagrangian (AL) technique is used to solve the highly nonlinear constrained multi-objective optimal control problem. An adaptive neuro-fuzzy inference system (ANFIS)-based structure (based on the result of the AL solution) is used to solve the online trajectory planning of the MPM.