Thavida Maneewarn

Visceral Leishmaniasis (VL) is a prevalent vector-borne disease that affects both human and animal populations in subtropical and tropical regions, contributing to a substantial mortality rate. Establishing efficient control policies is crucial to eradicating the VL epidemic. The VL epidemic system, containing reservoirs, vectors, and human populations, can be accurately modeled through differential equations. Managing the VL epidemic under multiple control policies can be considered a high-order nonlinear feedback control challenge. This study explores the application of Terminal Synergetic Control (TSC) to eradicate Zoonotic Visceral Leishmaniasis (ZVL). Notably, Synergetic Control (SC) is one of the suitable feedback control methods for manipulating high-order nonlinear systems, providing practical control inputs because of their chattering-free behavior. Additionally, the convergence properties of the control system can be enhanced through terminal attraction. Optimization of control parameters within the system is achieved through the integration of control mechanisms by the Dragonfly Algorithm (DA). The results demonstrate that the multiple control policies synthesized by the TSC method effectively regulate subpopulations in alignment with the specified control objectives. Furthermore, the enhanced convergence rate achieved by the TSC method, in comparison to the SC method, serves as evidence of TSC's effectiveness in guiding the dynamics of ZVL epidemic eradication. This research underscores the potential of the TSC method, utilizing optimal control parameters provided by the DA, to achieve targeted outcomes with improved convergence properties.

This study proposed a strategy for a quick fault recovery response when an actuator failure problem occurred while a humanoid robot with 7-DOF anthropomorphic arms was performing a task with upper body motion. The objective of this study was to develop an algorithm for joint reconfiguration of the receptionist robot called Namo so that the robot can still perform a set of emblematic gestures if an actuator fails or is damaged. We proposed a gesture similarity measurement to be used as an objective function and used bio-inspired artificial intelligence methods, including a genetic algorithm, a bacteria foraging optimization algorithm, and an artificial bee colony, to determine good solutions for joint reconfiguration. When an actuator fails, the failed joint will be locked at the average angle calculated from all emblematic gestures. We used grid search to determine suitable parameter sets for each method before making a comparison of their performance. The results showed that bio-inspired artificial intelligence methods could successfully suggest reconfigured gestures after joint motor failure within 1 s. After 100 repetitions, BFOA and ABC returned the best-reconfigured gestures; there was no statistical difference. However, ABC yielded more reliable reconfigured gestures; there was significantly less interquartile range among the results than BFOA. The joint reconfiguration method was demonstrated for all possible joint failure conditions. The results showed that the proposed method could determine good reconfigured gestures under given time constraints; hence, it could be used for joint failure recovery in real applications.

This paper aims to present the design and prototype of an inspection robot that can perform both horizontal and vertical locomotion in ferromagnetic pipelines. The proposed robot applies to a range from 5-inch (127 mm) diameter pipes to flat plates. The train-like robot is mainly composed of three sealed modules with omnidirectional driving wheels for longitudinal and transverse movements. Permanent magnets were designed to provide sufficient magnetic adhesion between the robot and the ferromagnetic surface of the pipes. The internal condition of the pipe can be monitored visually through cameras and sensors. Specific experimental conditions have been carried out to validate the robot’s capabilities, including maximum speed, payload capacity, and vertical climbing distance. The experimental results also show that the robot is capable of passing through a straight pipe and elbow fitting in both upward and downward directions.

Biological pest control has a strong advantage in its non-chemical effects on the environment. In this study, a fixed-time synergetic control scheme for the biological pest control problems represented by the n-dimensional Lotka-Volterra model was proposed. The proof of stability shows that the proposed controller can regulate the biological pest control systems with the characteristic of fixed-time convergence. The performance of the proposed scheme was demonstrated through simulation studies. The simulation results show that the pre-specified bound of the settling time can be satisfied regardless of the initial conditions, confirming a desired fixed-time convergence characteristic. Moreover, unlike the existing control policy based on the sliding mode control, the control inputs of the proposed policy are free from chattering.

Soft gripper can grasp various types of objects even deformable objects or complex shapes. In this work, the design of a soft gripper is inspired by a tube foot of a starfish. Tube foot can deform in multiple directions. The proposed gripper has three soft silicone fingers which are driven by pneumatic actuation. Each finger can be curved in 6 directions using a three sided air chamber. This gripper can be controlled by a binary command into four states: home, open, close and twist. The tube feet inspired soft gripper was developed, modelled and tested.

In this paper, we study the effect of unobserved energy in the haptic system due to different types of system delay and the observed pair of power variables. When the previously proposed passivity observer (PO) can not observe the energy produced by some types of system delay, the passivity controller (PC) may not be able to stabilize the system. We propose a fuzzy controller which is designed based on passivity that can improve system performance during virtual wall contact even when the passivity observer cannot detect the energy generated in the system due to delays

This paper describes a study of whether haptic feedback can be used to represent information that is normally difficult to obtain via visual feedback in telerobotic system. Problems of manipulator kinematic condition such as singularity and joint limit have been well known for a long time. Kinematic condition of the manipulator is difficult to be recognized visually. Poor kinematic condition often causes trajectory error or other undesirable effects in the system. This problem is quite significant in telerobotics since a fully pre-planned path that completely excludes poor kinematic condition is usually not available.