Detecting and Resolving Air Traffic Conflicts Using a Point of Closest Approach Method

A geometrical point of closest approach method is used to solve air traffic conflict detection/resolution problems with a single conflict vehicle that is unaware or unable to aid in resolving the conflict. Nonlinear, three degree of freedom equations of motion for a point-mass vehicle are derived and formulated to allow commanded trajectories to steer the vehicle to a desired location. A dynamic model is developed to propagate the vehicle in three dimensions. A closed-loop model implementing a negative feedback controller using a Proportional-Integral-Derivative control scheme is used to drive the vehicle to match the commanded trajectories. A conflict detection/resolution algorithm implementing a point of closest approach method is developed to determine the point at which the simulated, target vehicle will be just on the edge of a safe sphere surrounding the conflict aircraft to simulate the Federal Aviation Administration’s requirements for proper spacing between aircraft. A velocity vector is created to steer the target vehicle to this point to avoid any conflict. MathWorks’ Simulink computational environment is used to simulate the target vehicle and conflict vehicle. Various trajectories for the target vehicle and the conflict vehicle are tested to evaluate the performance of the algorithm. The algorithm performed satisfactorily in detecting and steering the vehicle away from a conflict, always improving the relative spacing between the two vehicles. However, the algorithm was lacking in capability to precisely satisfy the separation requirement. In all cases the target vehicle mildly penetrated the safe region. Future research directions are discussed with the goal of improving the conflict detection/resolution algorithm performance so that the separation requirement can be reliably met

Path Tracking and Position Control of Nonholonomic Differential Drive Wheeled Mobile Robot

Differential drive wheeled mobile robot (DDWMR) is one example of a robot with a constrained movement, Multiple Input Multiple Output (MIMO), and nonlinear system. Designing a low resource position and heading controller using linear MIMO methods such as LQR became a problem because of the linearization of robot dynamics at zero value. One of the solutions is to design a MIMO controller using a Single Input Single Output (SISO) controller. This work design a controller using PID for DDWMR Jetbot and selects the best feedback gain using different scenarios. The designed controller manipulates both motors by using calculated control signal to achieve a complex task such as path tracking with robot position in x-Axis, y-Axis, and heading angle as the feedback. The priority between position and heading angle can be adjusted by changing three feedback gains. The controller was tested, and the best gain was selected using Integral Absolute Error (IAE) metrics in a path tracking task with four different path shapes. The proposed methods can track square, circle, and two types of infinity shape paths, with the less well-formed shape being the four edges square path

MODELING AND PRESSURE CONTROL SYSTEM FOR AIR PLANT

This paper present about Modeling and Controlling linear process. Currently linear process is highly important for plant operation optimization. Modeling of the plant could be said is one of the major part of the plant, where the behavior and control tuning parameters could be dependent on it. Some problems that are met in modeling could be unpredictable behavior of the model, thus causing the tuning parameters inaccurate value, which may cause undesired output at the end. Another reason could be lack of experiment on obtained plant model. Empirical and Statistical modeling is the technique that has been used throughout the paper. Since the Process Reaction Curve method is known as simple and reliable method to be used, obtained parameters have been compared to other parameters that have been obtained several times from the same process plant. Obtained model has been analyzed step by step, to make sure that model parameters are valid to be used

Wordlength optimization for linear digital signal processing

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Efficiency optimization of the push-belt CVT by variator slip control

Continuously Variable Transmissions (CVT) are becoming increasingly popular in automotive applications. What makes them attractive is the ability to vary the transmission ratio in a stepless manner without interrupting the torque transfer. This increases comfort by eliminating the discrete shifting events and increases performance by choosing the most suitable transmission ratio for every driving situation. Using a CVT could potentially save more than 15% of fuel consumption compared to manually shifted vehicles. This figure however is never met, because of the internal losses in the CVTs in production today. If the losses in a CVT can be lowered, then the overall fuel economy of a CVT equipped vehicle will be improved with the same amount. With current CVTs ranging around 80% efficiency, an improvement of around 10% is possible compared to currently available CVTs if an optimal actuation and control system is used. This thesis is about the optimization of the control system of the CVT by using slip as the control variable. This is part of a larger project focussing on the entire actuation and control system. Also a CVT with Electro-Mechanically Pulley Actuation (EMPAct) is developed aiming to reduce the power consumption of the CVT actuation system. Combined, these two projects aim to improve the fuel economy of the CK2 transmission from Jatco with 10%. Models for the clamping forces and traction in the variator are compared. The continuous belt model is compared with a pushbelt model. A parameter study shows the influence of the model parameters on the outcome of the models. The output of the models are also compared to measured values. A nonlinear dynamic model for slip in the variator is derived. This model can be linearized in certain operating points. This model can be used for the design of a control system, simulation of slip in the variator or for analysis. Measurement of slip directly is not possible, therefore a good estimation method is needed. Several estimations of slip in the variator are compared. The position measurement of the pulley is used in the measurements shown in this thesis. Measurements on a beltbox testrig are given that clearly show a relation between slip and efficiency and slip and traction. This relation changes as a function of other parameters like speed, ratio, clamping force etc. Estimation of the efficiency potential of the pushbelt variator shows that a potential of between 5% for high torques and 20% for low torques exists. A slip control system is developed to show the possible efficiency improvement. First, a beltbox setup is used to test a simplified slip controlled variator. Ratio changing is not taken into account in this setup. After successful tests with this setup another setup is used that incorporates a Jatco CK2 transmission and an internal combustion engine. This test setup is more realistic, but therefore also more complicated to control. A gain scheduled approach is used to compensate for the slower actuation system. This system is then also applied to a testing vehicle

Precise Trajectory Tracking of Multi-Rotor UAVs Using Wind Disturbance Rejection Approach

This paper discusses the resilience of the UAV quadrotor to wind disturbances. An unknown input-state observer is presented that uses the Lipschitz method to estimate the internal states and disturbances of the quadrotor and compensate for them by varying the velocities of the four rotors. The observer intends to use existing sensor measurements to estimate the unknown states of the quadrotor and reconstruct the three-dimensional wind disturbances. The estimated states and external disturbances are sent to the PD controller, which compensates for the disturbances to achieve the desired position and attitude, as well as robustness and accuracy. The Lipschitz observer was designed using the LMI approach, and the results were validated using Matlab/Simulink and using the Parrot Mambo mini quadrotor