Amir A. Bature

Output-based command shaping technique for an effective payload sway control of a 3D crane with hoisting

This paper presents an output-based command shaping (OCS) technique for an effective payload sway control of a 3D crane with hoisting. A crane is a challenging and time-varying system, as the cable length changes during the operation. The OCS technique is designed based on output signals of an actual system and reference model, does not require the natural frequency and damping ratio of the system, and thus can be utilized to minimize the hoisting effects on the payload sway. The shaper was designed by using the derived non-linear model of a 3D crane. To test the effectiveness of the controller, simulations using a non-linear 3D crane model and experiments on a lab-scale 3D crane were performed and compared with a zero vibration derivative (ZVD) shaper and a ZVD shaper designed using an average travel length (ATL) technique. In both the simulations and the experiments, the OCS technique was shown to be superior in reducing the payload sway with reductions of more than 56% and 33% in both of the transient and residual sways that were achieved when compared with both the ZVD and the ATL shapers, respectively. In addition, the OCS technique provided the fastest time response during the hoisting. It is envisaged that the method can be very useful in reducing the complexity of closed-loop controllers for both tracking and sway control.

Identification and Real Time Control of a DC Motor

This paper presents identification and control of a DC motor. The dynamic model of the DC motor was first developed through system identification using least square parametric estimation method. Based on the developed dynamic model a state feedback tracking controller was then designed using optimal linear quadratic regulator for speed and position control of the DC motor. The developed dynamic model of the DC motor was validated via simulations and experiments. The performance of the controller was also verified through experiment.

LMI-based state feedback controller design for vibration control of a negative imaginary system

This paper presents state feedback control via linear matrix inequality (LMI) for vibration control of a flexible link manipulator (FLM) system. FLM is a negative imaginary (NI) system with high amplitude vibration and oscillation. In this work, pole placement controller (PPC) which is NI controller is used to control the FLM vibration, to achieve a precise hub angle positioning with minimum tip deflection. A decay rate is introduced to improve the speed of the system and investigate the effect on the system performance. LMI optimization technique is used to obtain the optimal and best control gains of PPC using Matlab LMI toolbox with different values of the decay rate. Simulation results show that satisfactory hub angle and tip deflection responses are achieved using the proposed controller. Damping is successfully added into the system and reduces the system vibration at the first two vibration modes by 40 dB. Hub angle positioning is achieved with minimum tip deflection by changing the value of decay rate.

Position Control of a 2D Nonlinear Gantry Crane System Using Model Predictive Controller

This paper presents the application of model predictive controller for controlling a nonlinear 2D gantry crane system with a DC motor as an actuator. The gantry crane system (GCS) dynamics is derived using Lagrange equation method. A model predictive controller is designed based on the linearised GCS and prediction cost function to ensure accurate positioning and oscillation reduction. Simulation via MATLAB and Simulink was performed to investigate the performance of the model predictive controller on the GCS. The controller test was done under several elements altering the behaviour of the system. The closed loop system was analysed considering different cable length, payload mass and trolley position. It was found that the closed loop control meets the main goal of this work, trolley positioning as fast as possible with minimum payload swinging all within a robust input voltage.

Position Tracking Controllers for Two Wheeled Inverted Pendulum Robot

: This paper present comparison between model based controller and nonmodel based controller in position tracking of a two wheeled inverted pendulum (TWIP). A Linear Quadratic Controller (LQR) which is a state feedback linear controller and fuzzy logic controller (FLC) which is non-model based intelligent controller are designed and simulated and the performances of the two controllers are compared. The FLC shows better performance than the LQR controller.

Biased Robust Composite Nonlinear Feedback Control of Under Actuated Systems

This paper proposes a method of designing composite nonlinear feedback (CNF) control for under actuated systems. By biasing the output error feedback of the nonlinear part of CNF, a state that is not the reference state but also important, can be given attention not only in the linear part but in the nonlinear part of CNF as well. The proposed scheme is tested on two wheeled inverted pendulum (TWIP) mobile robot which is highly under actuated robot, and shows a better performance in balancing the robot and also in energy consumption.

Adaptive input shaping for sway control of 3D crane using a pole-zero cancellation method

This paper presents an adaptive input shaping based on pole-zero cancellation (APZC) technique to suppress load sway of a crane system. In this method, a reference system is selected and the proposed adaptive shaper is made to force the actual system to adapt to the changes in natural frequency and damping ratio as the cable length increases or decreases. Simulation results are compared with a zero vibration derivative input shaper designed based on average travel length (ATL) to investigate the performance of the proposed shaper. Simulation using three cable length of 0.7 m, 0.5 m and 0.3 m shows that APZC gives better payload sway reduction with smallest maximum sway.

Sensorless position and velocity estimation of two wheeled inverted pendulum mobile robot

One of the problem with complex machines is the sensor used to measure the outputs or the states of the machine. The sensors are prone to noise and add to design complexity. To overcome these problems, sensorless techniques are used as substitutes to common physical sensors. This paper presents sensorless estimation of position and velocity of a two wheeled inverted pendulum (TWIP) mobile robot, using the robot model. The model is developed using identification method, and shows acceptable estimation of both the position and velocity of the robot in meters and meter per second respectively.