In this study a real-time open loop estimate of the disturbance displacement input to the tire and an external disturbance force, representing handling and aerodynamic forces, acting on the sprung mass of a quarter-car suspension test rig was generated. This information is intended for use in active control methods applied to vehicle suspensions. This estimate is achieved with two acceleration measurements as inputs to the estimator; one each on the sprung and unsprung masses. This method is differentiated from current disturbance accommodating control, bilinear observers, and preview control methods. A description of the quarter-car model and the experimental test rig is given. The equations of motion for the quarter-car model are derived in state space as well as a transfer function form. Several tests were run in simulation to investigate the performance of three integration techniques used in the estimator. These tests were first completed in continuous time prior to transforming to discrete time. Comparisons are made between the simulated and estimated displacement and velocity of the disturbance input to the tire and disturbance force input to the sprung mass. The simulated and estimated dynamic tire normal forces are also compared. This process was necessary to select preliminary values for the integrator transfer function to be implemented in real-time. Using the acceleration measurements from the quarter-car test rig, a quarter-car parameter optimization for use in the estimator was performed. The measured and estimated tire disturbance input, disturbance input velocity, and dynamic tire normal force signals are compared during experimental tests. The results show that the open loop observer provides estimates of the tire disturbance velocity and dynamic tire normal force with acceptable error. The results also indicate the quarter-car test rig behaves linearly within the frequency range and amplitude of the disturbance involved in this study. The resultant access to the disturbance estimate and dynamic tire force estimate in real-time enables pursuit of novel control methods applied to active vibration control of vehicle suspensions. / Master of Science

<div>Cyber-Physical Systems (CPSs) consist of physical and computational components usually interconnected through the internet. This type of systems have found applications in robotic surgery, smart medical services, driverless cars, smart power grids as well as in modern homes and offices. For a CPS to function properly, a reliable and secure communications between the system physical and cyber elements is of utmost importance. Malicious attacks during control signals and output measurements transmission between the physical plant and the control center must be addressed, which is the main research problem studied in this thesis.</div><div><br></div><div>A novel robust observer was proposed to synthesize a combined controller-observer compensator for a class of CPSs with sparse malicious attacks and arbitrary disturbances. The compensator consists of a controller, a norm approximator, and an unknown input observer (UIO). The proposed observer was compared with a norm-based observer given in the literature to show its advantage. To further enhance the proposed observer's performance against arbitrary disturbances, design methods were given that use fictitious output measurements and error correcting code (ECC) approach. The design of the UIO was extended to a bank of UIOs in order to improve the observer's performance against sparse malicious attacks.</div><div><br></div><div>The proposed observer can be used in the design of UIO-based fault detection and isolation (FDI) algorithms as well as in the distributed fault-tolerant control of large-scale interconnected systems. The results of this thesis can be applied to the design of controller-observer compensators for CPSs with modeling uncertainties.</div>

A growing population is driving automatization in agricultural industry to strive for more productive arable land. Being part of this process, this work is aimed to investigate the possibility to implement sensor-based automation in a particular system called Front End Loader, which is a lifting arms that is commonly mounted on the front of a tractor. Two main tasks are considered here, namely Electronic Self Leveling (ESL) and payload estimation. To propose commercially implementable solutions for these tasks, specific objectives are set, which are: 1) to propose a controller to perform ESL under typical disturbances 2) to propose a methodology for payload estimation considering realistic estimation conditions. Lastly, aligned with these goals, 3) to propose models for the Front End Loader under consideration for derivation of solutions of the specified tasks. The self-leveling task assists farmers in maintaining the angular position of the mounted implements, e.g. a bale handler or a bucket, with respect to the ground when the loader is manually lifted or lowered. Experimental results show that different controllers are required in lifting and lowering motions to maintain the implement's angular position with a required accuracy due to principle differences in gravity impact. The gravity helps the necessary correction in lifting motion, but works against the correction in lowering motions. This led us to propose a controller with a proportional term, a discontinuous term and an on-line disturbance estimation and compensation as well as the tuning procedure to achieve a 2 degrees tracking error for lowering motions in steady state. The proposed controller shows less sensitive performance to lowering velocity, as the main disturbance, in comparison to a linear controller. The second task, payload estimation, assists farmers to work within safety range as well as to work with a weight measurement tool. A mechanical model derived based on equations of motion is improved by a pressure based friction to sufficiently accurately represent the motion of the front end loader under consideration. The proposed model satisfies the desired estimation accuracy of 2\% full scale error in a certain estimation condition domain in constant velocity regions, with off-line calibration step and off-line payload estimation step. An on-line version of the estimation based on Recursive Least Squares also fulfills the desired accuracy, while keeping the calibration step off-line.

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