Tag: uav

Categories
control

Translation Movement Stability Control of Quad Tiltrotor Using LQR and LQG

by Andi Dharmawan, Ahmad Ashari, Agfianto Eko Putra

Abstract

Quadrotor as one type of UAV (Unmanned Aerial Vehicle) is a system that underactuated. It means that the system has a signal control amount is lower than the degrees of freedom or DOF (Degree Of Freedom). This condition causes the quadrotor have limited mobility. If quadrotor is made to have 6 DOF or more (over-actuated system), the motion control system to optimize the flight will be different from before. We need to develop over-actuated quadrotor control. Quadtiltrotor as the development of quadrotor has some control signal over its DOF. So we call it as an over-actuated system. Based on the type of maneuver to do, the transition process when the quad tiltrotor performs a translational motion using the tilting rotor need special treatment. The tilt angle change is intended that the quad tiltrotor can perform translational motion while still maintaining its orientation angle near 0°. This orientation angle can change during the undesirable rotational movement as the effect of the transition process. If additional rotational movements cannot be damped, the quad tiltrotor can experience multi overshoot, steady-state error, or even fall. Because of this matter, we need to develop flight control system to handle it. The flight control system of quad tiltrotor can be designed using a model of the system. Models can be created using quad tiltrotor dynamics by the Newton-Euler approach. Then the model is simulated along with the control system using the method of control. Several control methods can be utilized in a quad tiltrotor flight systems. However, with the implementation of LQG control method and Integrator, optimal translational control of the quad tiltrotor can be achieved.

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Categories
control

Mathematical Modelling of Translation and Rotation Movement in Quad Tiltrotor

by Andi Dharmawan, Ahmad Ashari, Agfianto Eko Putra

Abstract

Quadrotor as one type of UAV (Unmanned Aerial Vehicle) is an underactuated mechanical system. It means that the system has some control inputs is lower than its DOF (Degrees of Freedom). This condition causes quadrotor to have limited mobility because of its inherent under actuation, namely, the availability of four independent control signals (four-speed rotating propellers) versus 6 degrees of freedom parameterizing quadrotor position or orientation in space. If a quadrotor is made to have 6 DOF, a full motion control system to optimize the flight will be different from before. So it becomes necessary to develop over actuated quad tiltrotor. Quad tiltrotor has control signals more than its DOF. Therefore, we can refer it to the overactuated system. We need a good control system to fly the quad tiltrotor. Good control systems can be designed using the model of the quad tiltrotor system. We can create quad tiltrotor model using its dynamics based on Newton-Euler approach. After we have a set of model, we can simulate the control system using some control method. There are several control methods that we can use in the quad tiltrotor flight system. However, we can improve the control by implementing a modern control system that uses the concept of state space. The simulations show that the quad tiltrotor has done successful translational motion without significant interference. Also, undesirable rotation movement in the quad tiltrotor flight when performing the translational motions resulting from the transition process associated with the tilt rotor change was successfully reduced below 1 degree.

International Journal on Advanced Science, Engineering and Information Technology, Vol. 7 (2017) No. 3, pages: 1104-1113, DOI:10.18517/ijaseit.7.3.2171 [online]

Categories
control

PID Self Tuning Control Based on Mamdani fuzzy Logic Control for quadrotor stabilization

Quadrotor as one type of UAV can perform Vertical Take-Off and Landing (VTOL). It allows the Quadrotor to be stationary hovering in the air. PID (Proportional Integral Derivative) control system is one of the control methods that are commonly used. It is usually used to optimize the Quadrotor stabilization at least based on the three Eulerian angles (roll, pitch, and yaw) as input parameters for the control system. Various methods can obtain the three constants of PID. The simplest way is tuning manually. This approach has several weaknesses. For example, if the three constants are not exact, the resulting response will deviate from the desired result. By combining the methods of PID with fuzzy logic systems where human expertise is implemented into the machine language is expected to optimize the control system further.

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Categories
control

The use of Video Processing for Quadrotor Flight Stability Control Monitoring

The quadrotor is one kind of Unmanned Aerial Vehicles (UAV). Quadrotor can hover with minimal translational velocity approaching a stationary state. The four rotors support this capability. These rotors are used to lift the Quadrotor to fly. These rotors are placed on all four sides of the tip of Quadrotor. To operate with excellent stability, we can use an IMU sensor (Inertial Measurement Unit). IMU sensor consists of some DOF (degrees of freedom) sensors, such as 3-axis accelerometer sensor, 3-axisgyroscope sensor, 3-axis magnetometer sensor, and so on under the needs of flight. To test the stability of Quadrotor can be done by utilizing the video and image processing methods. This processing acts as the ’eyes’ of Quadrotor. Sobel method as one of the picture processing algorithms can be used to read the edges of the object. This method can measure the level of stability fly. But before reading the results of the edge must first be converted to black and white format. Otsu method can be used to perform the conversion. Then we find the center point of the result of the transformation of the object being viewed. This point can be used to read the movement of Quadrotor. It is used to determine the position of the quadrotor movement on vertical and horizontal axes. The position can be utilized as input to control the quadrotor flight stability.

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Categories
control

Quadrotor flight stability system with Routh stability and Lyapunov analysis

UAV (Unmanned Aerial Vehicle) can fly autonomously or be controlled remotely by a pilot. Quadrotor as one type of UAV has been widely implemented in various needs. Its system design has a lot of control techniques involved. The design starts with the physical modeling. Quadrotor physical modeling is modeling based on the laws of physics as a theory and mathematical modeling of physical interpretation. The problem arises when actual plants are not fit with mathematical models that are used as the control design before. Such discrepancy arises because of external interference, plant parameters, and dynamics models that are nonlinear. If control systems are not designed to deal with non-linear interference, it is difficult to us to maintain quadrotor flight. Therefore, we need control methods that can be applied to linear and nonlinear systems. Routh Stability can be used to generate PID (Proportional Integral and Derivative) constants as a linear control method by using a Ziegler-Nichols. Lyapunov as a method of non-linear control method offers distinct advantages over other control methods. Lyapunov second method is further implemented by a control technique that gives a good effect. So the PID and Lyapunov method can make quadrotor approaching the stationary state.

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Categories
Mikrokontroler

Optimizing control based on ant colony logic for Quadrotor stabilization

Quadrotor as one type of UAV (Unmanned Aerial Vehicle) have the ability to perform Vertical Take Off and Landing (VTOL). It allows the Quadrotor to be stationary hovering in the air. PID (Proportional Integral Derivative) control system is one of the control methods that are commonly used. It is usually used to optimize the Quadrotor stabilization at least based on the three Eulerian angles (roll, pitch, and yaw) as input parameters for the control system. The three constants of PID can be obtained in various ways or methods. However, to produce a robust control, we need a method that can optimize the PID components. Ant Colony Optimization (ACO) is one of PID controller optimization method which adapted by ant colony ability to find the shortest way from their nest to food. Some ACO parameters are number of ants, parameters, and pheromone constant for pheromone. Pheromones are the values given by the ants when they use the road.

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