On the trade-off between electrical power consumption and flight performance in fixed-wing UAV autopilots

This paper sets out a study of the autopilot design for fixed wing Unmanned Aerial Vehicles (UAVs) taking into account the aircraft stability, as well as the power consumption as a function of the selected control strategy. To provide some generality to the outcomes of this study, construction of a reference small-UAV model, based on averaging the main aircraft defining parameters, is proposed. Using such a reference model of small, fixed-wing UAVs, different control strategies are assessed, especially with a view towards enlarging the controllers' sampling time. A beneficial consequence of this sample time enlargement is that the clock rate of the UAV autopilots may be proportionally reduced. This reduction in turn leads directly to decreased electrical power consumption. Such energy saving becomes proportionally relevant as the size and power of the UAV decrease, with benefits of lengthening battery life and, therefore, the flight endurance. Additionally, through the averaged model, which is derived from both published data and computations made from actual data captured from real UAVs, it is shown that behavior predictions beyond that of any particular UAV model may be extrapolated.Peer ReviewedPostprint (author's final draft

Modelling the robustness properties of HVAC plant under feedback control

Most existing building simulation programs fail to capture sufficient of the underlying dynamics of nonlinear HVAC plant and some have restricted room space modelling capabilities for low-time-horizon analyses. In this work, a simplified model of a room space with hot water heating and a chilled ceiling system is developed for the main purpose of analysing control system response. The room model is based on a new approach to lumped capacitance modelling and the heating and chilled ceiling emitters are modelled using third-order descriptions. Control system components are treated in detail and both controllers are ‘tuned’ at a nominal region of plant operation using a gradient-descent-based optimization procedure. Robustness qualities of the controllers are analysed with reference to extremes in plant operating conditions. A key feature of the work is the transparency of the modelling procedure, designed to have appeal to researchers as well as practitioners involved with HVAC control system design problems

Stability Control Structure of Hovercraft Prototype Utilising PID Controller

Hovercraft is a method of transportation as an option for clients who remain on the waterway and swamp surface. The issue with hovercraft is when dubious climate and natural condition, e.g. wind speed and wave tallness exasperate solidness of hovercraft to jeopardise the driver. We propose an approach to keep up adjust of the hovercraft by controlling the focal point of gravity (PG) to be determined position. The controller monitors the position of load to change the position. A 6-DOF IMU Sensor MPU 6050 was utilised to create information as an examination with setpoint. PID control strategy was employed. The test outcome demonstrates that the model of air cushion vehicle could keep its adjust the axis orientation of the roll in spite of the fact that it was less compelling in the pitch pivot direction

Development Of A Semi-Swath Craft For Malaysian Waters

Small Waterplane Area Twin Hull (SWATH) and Catamaran vessels are known to have more stable platform as compared to mono-hulls. A further advantage of SWATH as compared to Catamaran is its smaller waterplane area that provides better seakeeping qualities. However, the significant drawback of the SWATH vessel is when encountering head-sea at high forward speed. Due to its low stiffness, it has a tendency for large pitch motions. Consequently, this may lead to excessive trim or even deck wetness. This phenomenon will not only degrade the comfortability but also results in structural damage with greater safety risks. In this research a modified SWATH design is proposed. The proposed design concept represents a combination of Catamaran and SWATH vessel hull features that will lead to reduce in bow-diving but still maintains good seakeeping capabilities. This is then called the Semi- SWATH vessel. In addition, the full-design of this vessel has been equipped by fixed fore fins and controllable aft fins attached on each lower hull. In the development of controllable aft fins, the PID controller system was applied to obtain an optimal vessel’s ride performance at speeds of 15 (medium) and 20 (high) knots. In this research work, the seakeeping performance of Semi-SWATH vessel was evaluated using time-domain simulation approach. The effect of fin stabilizer on the bare hull performance is considered. The validity of numerical evaluation was then compared with model experiments carried out in the Towing Tank at Marine Technology Laboratory, UTM. It is shown that the Semi-SWATH vessel with controllable fin stabilizer can have significantly reduction by about 42.57% of heave motion and 48.80% of pitch motion

Optimisation of Mobile Communication Networks - OMCO NET

The mini conference “Optimisation of Mobile Communication Networks” focuses on advanced methods for search and optimisation applied to wireless communication networks. It is sponsored by Research & Enterprise Fund Southampton Solent University. The conference strives to widen knowledge on advanced search methods capable of optimisation of wireless communications networks. The aim is to provide a forum for exchange of recent knowledge, new ideas and trends in this progressive and challenging area. The conference will popularise new successful approaches on resolving hard tasks such as minimisation of transmit power, cooperative and optimal routing

The effect of PID control scheme on the course-keeping of ship in oblique stern waves

Sailing in oblique stern waves causes a ship to make sharp turns and uncontrollable course deviation, which is accompanied by a large heel and sometimes leads to capsizing. Studying the control algorithm in oblique stern waves is imperative because an excellent controller scheme can improve the ship’s course-keeping stability. This paper uses the Maneuvering Modelling Group (MMG) method based on hydrodynamic derivatives and the Computational Fluid Dynamics (CFD)-based self-navigation simulation to simulate ship navigation in waves. This study examines the effect of proportion-integral-derivative (PID) controller schemes on the stability of course maintenance based on hydrodynamic derivatives and 3DOF MMG methods. Then, the optimized PID control parameters are used to simulate the ship’s 6DOF self-propulsion navigation in oblique waves using the CFD method. The nonlinear phenomena during the process, such as side-hull emergency, slamming, and green water, are considered. This study found that the range of the control bandwidth should be optimized based on the ship\u27s heading and wave parameters

Implementing PID Control on Arduino Uno for Air Temperature Optimization

This research investigates the precise regulation of liquid filling in tanks, specifically focusing on water storage systems. It employs the Proportional-Integral-Derivative (PID) control method in conjunction with an HC-SR04 ultrasonic sensor and an Arduino Uno microcontroller. Given the paramount importance of water as a resource, accurate management of its storage is of utmost significance. The PID control method, known for its rapid responsiveness, minimal overshoot, and robust stability, effectively facilitates this task. Integrating the ultrasonic sensor and microcontroller further augments the precision of water level regulation. The article expounds upon the foundational principles of the PID control method and elucidates its application in the context of liquid tank filling. It offers a comprehensive insight into the hardware configuration, encompassing pivotal components such as the Arduino Uno microcontroller, HC-SR04 ultrasonic sensor, and the L298 driver responsible for water pump control. The experimental approach is meticulous, presenting results from tests involving the Proportional Controller, Proportional Integral (PI) Controller, and Proportional Integral Derivative (PID) Controller. These tests rigorously analyze the impact of varying Proportional Gain (Kp), Integral Gain (Ki), and Derivative Gain (Kd) parameters on crucial performance metrics such as response time, overshoot, and steady-state error. The findings underscore the critical importance of an optimal parameter configuration, emphasizing the delicate equilibrium between response speed, precision, and error minimization. This research significantly advances PID control implementation in liquid tank filling, offering insights that pave the way for developing more efficient liquid management systems across various sectors. The identified optimal parameter configuration is Kp = 5.0, Ki = 0.3, and Kd = 0.2

Interpretable PID Parameter Tuning for Control Engineering using General Dynamic Neural Networks: An Extensive Comparison

Modern automation systems rely on closed loop control, wherein a controller interacts with a controlled process, based on observations. These systems are increasingly complex, yet most controllers are linear Proportional-Integral-Derivative (PID) controllers. PID controllers perform well on linear and near-linear systems but their simplicity is at odds with the robustness required to reliably control complex processes. Modern machine learning offers a way to extend PID controllers beyond their linear capabilities by using neural networks. However, such an extension comes at the cost of losing stability guarantees and controller interpretability. In this paper, we examine the utility of extending PID controllers with recurrent neural networks-namely, General Dynamic Neural Networks (GDNN); we show that GDNN (neural) PID controllers perform well on a range of control systems and highlight how they can be a scalable and interpretable option for control systems. To do so, we provide an extensive study using four benchmark systems that represent the most common control engineering benchmarks. All control benchmarks are evaluated with and without noise as well as with and without disturbances. The neural PID controller performs better than standard PID control in 15 of 16 tasks and better than model-based control in 13 of 16 tasks. As a second contribution, we address the lack of interpretability that prevents neural networks from being used in real-world control processes. We use bounded-input bounded-output stability analysis to evaluate the parameters suggested by the neural network, thus making them understandable. This combination of rigorous evaluation paired with better interpretability is an important step towards the acceptance of neural-network-based control approaches. It is furthermore an important step towards interpretable and safely applied artificial intelligence