As satellite missions become more complex, reliable power management is crucial for success. Traditional power budgeting approaches often operate at the system level, leading to inefficiencies in power allocation, particularly during critical phases such as eclipse mode. This study presents a component-level power budgeting framework to enhance operational integrity for next-generation satellites, specifically focusing on power load calculation, power generation, and battery capacity requirements. Key challenges such as power shortages, thermal fluctuations, and battery management require efficient power allocation and thermal control to ensure system reliability. Additionally, laser communication, while a critical capability for advanced satellites, becomes more complex during eclipse mode as in this period the mission execution will totally depends on the onboard available power. This analysis is based on detailed component-level power load calculations for eclipse mode. The total power load in this scenario is 38.922 W, with an operational mode of 27.5179 W, accounting for the power consumption of other subsystems. These calculations incorporate each module's power load, weighted by its duty cycle per orbit. The solar panels generate 65 W of power, with an effective power output of 45.599 W, as simulated in STK software. The eclipse mode, at an altitude of 525 km and an inclination angle of 83 degrees, lasts for 37.7% of the orbit, resulting in a power consumption of 27.343 W during this time. The calculated power consumption in eclipse mode is 27.343 W, with a minor error of 0.175 W. To meet battery requirements, the battery must provide at least 48.34 W, considering an 80% Depth of Discharge (DOD), for a 10-second high-power communication window. The battery capacity should exceed 48.34 W to ensure safe operation in eclipse mode. Based on these calculations, the satellite's power generation and storage system are sufficient to support its operations during eclipse mode, ensuring reliable and uninterrupted performance.

We design a remote fault-tolerant control for an industrial surveillance system. The designed controller simultaneously tolerates the effects of local faults of a node, the propagated undesired effects of neighboring connected nodes, and the effects of network-induced uncertainties from a remote location. The uncertain network-induced time delays of communication links from the sensor to the controller and from the controller to the actuator are modeled using two separate Markov chains and packet dropouts using the Bernoulli process. Based on linear matrix inequalities, we derive sufficient conditions for output feedback-based control law, such that the controller does not directly depend on output, for stochastic stability of the system. The simulation study shows the effectiveness of the proposed approach.

In the current age of automation, robots have been designed to interact and work with humans. Humanoid robots are mostly used for this social interaction. To interact in a social environment, robots need high decoupling of a camera sensor from the head skeleton to point, track and recognize the stimuli. This high decoupling of a camera sensor from the head skeleton is easily achieved by using the decoupling property of a gimbal system. To further increase the tracking performance, we estimate the friction disturbance torque and then compensate it using MATLAB/SIMULINK. We addressed the frictional disturbance torque in both the channels of the gimbal system using observer-based controller design and stabilize the gimbal-based robotic eye. To show the Saccade like the human eye, we performed simulations for tracking control. The designed controller is robust against frictional disturbance. The simulation results illustrate the stabilization and tracking control of the gimbal-based robotic eye and the estimation and compensation of frictional disturbance. This will be a valuable step towards humanoid robots.

This paper presents the design, real-time implementation, and experimental validation of a low-cost, embedded multi-sensor fusion framework for dead reckoning, localization, and obstacle detection in mobile ground robots. The proposed system integrates a MEMS inertial measurement unit (IMU), a GPS receiver, and an ultrasonic sensor (HC–SR04) within a single synchronized execution loop to achieve GPS-resilient and obstacle-aware navigation on resource-constrained hardware. A hybrid complementary–Kalman filtering scheme is implemented, where the complementary filter fuses accelerometer and gyroscope data for roll and pitch estimation, while periodic GPS updates perform lightweight Kalman corrections to bound drift. Ultrasonic range measurements are processed in the same loop and mapped relative to the estimated trajectory to provide continuous hazard awareness. The complete system, implemented on a 16 MHz Arduino-class MCU, achieves real-time operation at 20 Hz with a total hardware cost below USD 150. Field trials conducted under mixed GPS conditions demonstrate that the fused solution outperforms individual sensors, achieving a position RMSE of 1.19 m—a 49.6% improvement over GPS-only and an 80.7% improvement over IMU-only estimates—and maintains 99.2% localization continuity during GPS outages. The proposed framework demonstrates that reliable, low-cost, and real-time multi-sensor navigation can be achieved without high-performance processors, offering a practical architecture for educational robotics, cost-sensitive autonomous vehicles, and preliminary planetary rover prototypes.

This paper presents two new fault models for networked systems. These fault models are more realistic and generalized for networked systems in the sense that they can represent the effects of fault at the node and network levels. At the network layer, the uncertain effects of the network lines are modeled using a Markov chain with complex transition probabilities simultaneously with the stochastic behavior of the network using a Bernoulli process. A new output feedback-based controller, which is two-mode dependent and considers network uncertainties and output measurements for gain calculation, is presented. Using the tools of robust control and stochastic stability, linear matrix inequality-based sufficient conditions are derived. The proposed controller successfully maintains the system’s performance by tolerating the effects of simultaneous sensor and actuator faults, ensuring the stability of networked loops. Simulation results verify the applicability of the presented fault-tolerant control against multiple simultaneous faults.