Motion control design for unmanned ground vehicle in dynamic environment using intelligent controller

The motion control of unmanned ground vehicles is essential in the industry of automation. In this paper, the sensors of a fuzzy inference system that is based on a navigation technique for an unmanned ground vehicle are formulated in a cluttered dynamic environment. This fuzzy inference system consists of two controllers. The first controller uses three sensors based on the distances from the front, the right and the left. The second controller employs the angle difference between the heading of the vehicle and the targeted angle to choose the optimal route based on the dynamic environment and reach the desired destination with minimum running power and time. Experimental tests have been carried out in three different case studies to investigate the validation and effectiveness of the introduced controllers of the fuzzy inference system. The reported simulation results are conducted using MATLAB software package. The results show that the controllers of the fuzzy inference system consistently perform the maneuvering task and route planning efficiently even in a complex environment with populated dynamic obstacles

Review of sliding mode control application in autonomous underwater vehicles

973-984This paper presents a review of sliding mode control for autonomous underwater vehicles (AUVs). The AUVs are used under water operating in the presence of uncertainties (due to hydrodynamics coefficients) and external disturbances (due to water currents, waves, etc.). Sliding mode controller is one of the nonlinear robust controllers which is robust towards uncertainties, parameter variations and external disturbances. The evolution of sliding mode control in motion control studies of autonomous underwater vehicles is summarized throughout for the last three decades. The performance of the controller is examined based on the chattering reduction, accuracy (steady state error reduction), and robustness against perturbation. The review on sliding mode control for AUVs provides insights for readers to design new techniques and algorithms, to enhance the existing family of sliding mode control strategies into a new one or to merge and re-supervise the control techniques with other control strategies, in which, the aim is to obtain good controller design for AUVs in terms of great performance, stability and robustness

An adaptive autopilot design for an uninhabited surface vehicle

An adaptive autopilot design for an uninhabited surface vehicle Andy SK Annamalai The work described herein concerns the development of an innovative approach to the design of autopilot for uninhabited surface vehicles. In order to fulfil the requirements of autonomous missions, uninhabited surface vehicles must be able to operate with a minimum of external intervention. Existing strategies are limited by their dependence on a fixed model of the vessel. Thus, any change in plant dynamics has a non-trivial, deleterious effect on performance. This thesis presents an approach based on an adaptive model predictive control that is capable of retaining full functionality even in the face of sudden changes in dynamics. In the first part of this work recent developments in the field of uninhabited surface vehicles and trends in marine control are discussed. Historical developments and different strategies for model predictive control as applicable to surface vehicles are also explored. This thesis also presents innovative work done to improve the hardware on existing Springer uninhabited surface vehicle to serve as an effective test and research platform. Advanced controllers such as a model predictive controller are reliant on the accuracy of the model to accomplish the missions successfully. Hence, different techniques to obtain the model of Springer are investigated. Data obtained from experiments at Roadford Reservoir, United Kingdom are utilised to derive a generalised model of Springer by employing an innovative hybrid modelling technique that incorporates the different forward speeds and variable payload on-board the vehicle. Waypoint line of sight guidance provides the reference trajectory essential to complete missions successfully. The performances of traditional autopilots such as proportional integral and derivative controllers when applied to Springer are analysed. Autopilots based on modern controllers such as linear quadratic Gaussian and its innovative variants are integrated with the navigation and guidance systems on-board Springer. The modified linear quadratic Gaussian is obtained by combining various state estimators based on the Interval Kalman filter and the weighted Interval Kalman filter. Change in system dynamics is a challenge faced by uninhabited surface vehicles that result in erroneous autopilot behaviour. To overcome this challenge different adaptive algorithms are analysed and an innovative, adaptive autopilot based on model predictive control is designed. The acronym ‘aMPC’ is coined to refer to adaptive model predictive control that is obtained by combining the advances made to weighted least squares during this research and is used in conjunction with model predictive control. Successful experimentation is undertaken to validate the performance and autonomous mission capabilities of the adaptive autopilot despite change in system dynamics.EPSRC (Engineering and Physical Sciences Research Council

Analysis and Comparison of Clothoid and Dubins Algorithms for UAV Trajectory Generation

The differences between two types of pose-based UAV path generation methods clothoid and Dubins are analyzed in this thesis. The Dubins path is a combination of circular arcs and straight line segments; therefore its curvature will exhibit sudden jumps between constant values. The resulting path will have a minimum length if turns are performed at the minimum possible turn radius. The clothoid path consists of a similar combination of arcs and segments but the difference is that the clothoid arcs have a linearly variable curvature and are generated based on Fresnel integrals. Geometrically, the generation of the clothoid arc starts with a large curvature that decreases to zero. The clothoid path results are longer than the Dubins path between the same two poses and for the same minimum turn radius. These two algorithms are the focus of this research because of their geometrical simplicity, flexibility, and low computational requirements.;The comparison between clothoid and Dubins algorithms relies on extensive simulation results collected using an ad-hoc developed automated data acquisition tool within the WVU UAV simulation environment. The model of a small jet engine UAV has been used for this purpose. The experimental design considers several primary factors, such as different trajectory tracking control laws, normal and abnormal flight conditions, relative configuration of poses, and wind and turbulence. A total of five different controllers have been considered, three conventional with fixed parameters and two adaptive. The abnormal flight conditions include locked or damaged actuators (stabilator, aileron, or rudder) and sensor bias affecting roll, pitch, or yaw rate gyros that are used in the feedback control loop. The relative configuration of consecutive poses is considered in terms of heading (required turn angle) and relative location of start and end points (position quadrant). Wind and turbulence effects were analyzed for different wind speed and direction and several levels of turbulence severity. The evaluation and comparison of the two path generation algorithms are performed based on generated and actual path length and tracking performance assessed in terms of tracking errors and control activity.;Although continuous position and velocity are ensured, the Dubins path yields discontinuous changes in path curvature and hence in commanded lateral accelerations at the transition points between the circular arcs and straight segments. The simulation results show that this generally leads to increased trajectory tracking errors, longer actual paths, and more intense control surface activity. The gradual (linear) change in clothoid curvature yields a continuous change in commanded lateral accelerations with general positive effects on the overall UAV performance based on the metrics considered. The simulation results show general similar trends for all factors considered. As a result, it may be concluded that, due to the continuous change in commanded lateral acceleration, the clothoid path generation algorithm provides overall better performance than the Dubins algorithm, at both normal and abnormal flight conditions, if the UAV mission involves significant maneuvers requiring intense lateral acceleration commands

Reducing the Noise Impact of Unmanned Aerial Vehicles by Flight Control System Augmentation

The aim of this thesis is to explore methods to reduce the noise impact of unmanned aerial vehicles operating within acoustically sensitive environments by flight control system augmentation. Two methods are investigated and include: (i) reduction of sound generated by vehicle speed control while flying along a nominal path and (ii) reduction of acoustic exposure by vehicle path control while flying at a nominal speed. Both methods require incorporation of an acoustic model into the flight control system as an additional control objective and an acoustic metric to characterize primary noise sources dependent on vehicle state. An acoustic model was developed based on Gutin’s work to estimate propeller noise, both to estimate source noise and observer noise using two separate acoustic metrics. These methods can potentially mitigate the noise impact of unmanned aerial systems operating near residential communities. The baseline flight control system of a representative aircraft was augmented with a control law to reduce propeller noise using feedback control of the commanded flight speed until an acoustic target was met, based on the propeller noise model. This control approach focuses on modifying flight speed only, with no perturbation to the trajectory. Multiple flight simulations were performed and the results showed that integrating an acoustic metric into the flight control system of an unmanned aerial system is possible and useful. A second method to mitigate the effects of noise on an observer was also pursued to optimize a trajectory in order to avoid an acoustically sensitive region during the path planning process. After the propeller noise model was incorporated into the vehicle system, simulations showed that it is possible to reduce the noise impact on an observer through an optimization of the trajectory with no perturbation to the flight speed

Collision-free Multiple Unmanned Combat Aerial Vehicles Cooperative Trajectory Planning for Time-critical Missions using Differential Flatness Approach

This paper investigates the cooperative trajectory planning for multiple unmanned combat aerial vehicles in performing autonomous cooperative air-to-ground target attack missions. Firstly, the collision-free cooperative trajectory planning problem for time-critical missions is formulated as a cooperative trajectory optimal control problem (CTP-OCP), which is based on an approximate allowable attack region model, several constraints model, and a multi-criteria objective function. Next, a planning algorithm based on the differential flatness, B-spline curves and nonlinear programming is designed to solve the CTP-OCP. In particular, the notion of the virtual time is introduced to deal with the temporal constraints. Finally, the proposed approach is validated by two typical scenarios and the simulation results show the feasibility and effectiveness of the proposed planning approach.Defence Science Journal, Vol. 64, No. 1, January 2014, DOI:10.14429/dsj.64.299

Aerial vehicle trajectory design for spatio-temporal task satisfaction and aggregation based on utility metric

Flight trajectories are mainly designed in order to make sure that the aerial vehicle reaches the destination point from the start point. In addition to that, the flight path is designed in such a way that the flight avoids dangerous zones and the maneuvers required for the path are practically feasible for the flight. This thesis focuses on the aerial vehicle trajectory generation passing through a set of pre-defined way points while satisfying the task points sent by the ground base station in between the way points. Each specified waypoint is reached exactly at the specified location and time. Intermediate waypoints are generated in such a way that they satisfy the task points, which give high benefit measure, i.e. satisfying tasks with high task priority and QoS (Quality of Service) priority. Generated waypoints are points from where imagery data of the tasks are collected. Task points are aggregated by the TABUM (Task Aggregation Based on Utility Metric) approach, which takes into consideration factors such as task points\u27 priorities, sensory capability and deviation required from the shortest path to satisfy that waypoint. We generate a 4D flight trajectory, which is a collection of predefined waypoints and generated waypoints by taking the velocities, maneuverability of the aerial vehicle into consideration while ensuring that the vehicle avoids the no-fly zones. We finally frame the problem of trajectory generation in a constrained environment as an optimization problem and solve it by increasing the benefit measure and decreasing the cost measure (deviation from line-of-sight path). We perform experiments to show the effect of the utility metric threshold value and compare the performance of the vehicles\u27 trajectory with flight maneuverability and helicopter maneuverability capabilities. We also show how the performance of the sensor/camera attached to the flight will effect the benefit measure --Abstract, page iv

An intelligent navigation system for an unmanned surface vehicle

Merged with duplicate record 10026.1/2768 on 27.03.2017 by CS (TIS)A multi-disciplinary research project has been carried out at the University of Plymouth to design and develop an Unmanned Surface Vehicle (USV) named ýpringer. The work presented herein relates to formulation of a robust, reliable, accurate and adaptable navigation system to enable opringei to undertake various environmental monitoring tasks. Synergistically, sensor mathematical modelling, fuzzy logic, Multi-Sensor Data Fusion (MSDF), Multi-Model Adaptive Estimation (MMAE), fault adaptive data acquisition and an user interface system are combined to enhance the robustness and fault tolerance of the onboard navigation system. This thesis not only provides a holistic framework but also a concourse of computational techniques in the design of a fault tolerant navigation system. One of the principle novelties of this research is the use of various fuzzy logic based MSDF algorithms to provide an adaptive heading angle under various fault situations for Springer. This algorithm adapts the process noise covariance matrix ( Q) and measurement noise covariance matrix (R) in order to address one of the disadvantages of Kalman filtering. This algorithm has been implemented in Spi-inger in real time and results demonstrate excellent robustness qualities. In addition to the fuzzy logic based MSDF, a unique MMAE algorithm has been proposed in order to provide an alternative approach to enhance the fault tolerance of the heading angles for Springer. To the author's knowledge, the work presented in this thesis suggests a novel way forward in the development of autonomous navigation system design and, therefore, it is considered that the work constitutes a contribution to knowledge in this area of study. Also, there are a number of ways in which the work presented in this thesis can be extended to many other challenging domains.DEVONPORT MANAGEMENT LTD, J&S MARINE LTD AND SOUTH WEST WATER PL