The Design of an Automatic Flight Control System and Dynamic Simulation for Fixed-Wing Unmanned Aerial Vehicle (UAV) using X-Plane and LabVIEW

This research focuses on developing an automatic flight control system for a fixed-wing unmanned aerial vehicle (UAV) using a software-in-the-loop method in which the PID controller is implemented in National Instruments LabVIEW software and the flight dynamics of the fixed-wing UAV are simulated using the X-Plane flight simulator. The fixed-wing UAV model is created using the Plane Maker software and is based on existing geometry and propulsion data from the literature. Gain tuning for the PID controller is accomplished using the pole placement technique. In this approach, the controller gain can be calculated using the dynamic parameters in the transfer function model and the desired characteristic equation. The proposed controller designs' performance is validated using attitude, altitude, and velocity hold simulations. The results demonstrate that the technique can be an effective tool for researchers to validate their UAV control algorithms by utilising the realistic UAV or manned aircraft models available in the X-Plane flight simulator.

Active Compliant PID Learning Control for Grinding Robots

This article proposes a Proportional, Integral, and Derivative (PID) learning controller for rigid robotic disk grinding mechanism. It has been observed that the stiffness of the robotic arm for a grinder has a direct correlation with the sensitivity of the grinding forces. It is also drastically influenced by the end-effector path tracking error resulting in limited accuracy of the robot. The error in robot’s accuracy is also increased by external interferences, such as surface imperfections and voids in the subject material. These errors can be mitigated via efficient feedback. In the proposed methodology, the controller gain is tuned by implementing a learning-based methodology to PID controllers. The learning control for the robotic grinding system helps by progressively decreasing error between the actual grinded paths and required trace. Experimental results demonstrate that as the grinder machines the required path iteratively, its grinding accuracy improves due to the learning algorithm.

Accommodation of Multi-Shaft Gas Turbine Switching Control Gain Tuning Problem to IGV Position

This article aims to discuss the influence of compressor Inlet Guide Vane (IGV) position on gas turbine switching control system gain tuning problem. The distinction between IGV and normally reckoned working conditions is differentiated, and an improved double-layer LPV model is proposed to estimate the protected parameters under various IGV positions. Controller gain tuning is conducted with single and multi-objective intellectual optimization algorithms. Simulation results reveal that normally used multi-objective optimization procedure is unnecessary and time-consuming. While with the comprehensive indicator introduced in this paper, the calculation burden can be greatly eased. This improvement is especially advantageous when tuning work is carried out under multiple IGV positions.

A novel platoon topology and performance analysis with cloud brain control center for multi-functional unmanned ground vehicle

Unmanned ground vehicles (UGVs) are of great significance to the development of Intelligent Transportation System (ITS). The UGVs are supposed to serve a large number of missions with multiple functions in civilian use. Therefore, it requires UGV to be grouped as a platoon to complete the given missions. A novel platoon topology, Vehicle-Cloud Bidirectional Leader (VCBDL), is proposed in this paper to provide the basement for the group control of multi-functional UGVs. The VCBDL topology takes consideration of a cloud brain control center, which is capable of analyzing and making autonomous decisions for the UGVs. In order to realize the stable operation of the platoon with VCBDL topology, this paper analyzes the design of the platoon controller based on the graph theory method and obtains the range of controller gain. The robustness of the running platoon is analyzed and the convergence range of the platoon robustness index is defined. The above conclusions are verified by simulation based on the control of the police-used patrol UGV. The simulation results demonstrate the effectiveness of controller design, and the robustness performance is investigated by simulated random platoon disturbance. In addition, the experiments with real shuttle UGVs testbeds platoon are performed to verify the performance of the proposed controller.

A PI Controller with a Robust Adaptive Law for a Dielectric Electroactive Polymer Actuator

Dielectric electroactive polymer actuators are new important transducers in control system applications. The design of a high performance controller is a challenging task for these devices. In this work, a PI controller was studied for a dielectric electroactive polymer actuator. The pole placement problem for a closed-loop system with the PI controller was analyzed. The limitations of a PI controller in the pole placement problem are discussed. In this work, the analytic PI controller gain rules were obtained, and therefore extension to adaptive control is possible. To minimize the influence of unmodeled dynamics, the robust adaptive control law is applied. Furthermore, analysis of robust adaptive control was performed in a number of simulations and experiments.