L1 adaptive control for nonlinear and non-square multivariable systems

This research presents development of L1 adaptive output-feedback control theory for a class of uncertain, nonlinear, and non-square multivariable systems. The objective is to extend the L1 adaptive control framework to cover a wide class of underactuated systems with uniform performance and robustness guarantees. This dissertation starts by investigating some structural properties of multivariable systems that are used in the development of L1 adaptive output feedback controllers. In particular, a state-decomposition is introduced for adaptive laws that only depends on the output signals. The existence of the decomposition is ensured by defining a virtual system for underactuated plants. Based on the mathematical findings, we propose a set of output feedback solutions for uncertain underactuated systems. In adaptive control applications, a baseline control augmentation is often preferred, where the baseline controller defines the nominal system response. Adaptive controllers are incorporated into the control loop to improve the system response by recovering the nominal performance in the presence of uncertainties. This thesis provides a solution for L1 output feedback control augmentation. Stability and transient performance bounds are proven using Lyapunov analysis. To demonstrate the benefits of the L1 adaptive controllers we consider a missile system and an inverted pendulum, which are both underactuated systems. Finally, we propose a filter design framework in the frequency domain. A new sufficient condition is presented to ensure stability of the closed loop and the reference systems, which is subsequently used in the optimal filter design. Existing H-infinity optimization techniques are leveraged to address the performance and robustness trade-off issues

Real-time response estimation of structural vibration with inverse force identification

This study aimed to develop a virtual sensing algorithm of structural vibration for the real-time identification of unmeasured information. First, certain local point vibration responses (such as displacement and acceleration) are measured using physical sensors, and the data sets are extended using a numerical model to cover the unmeasured quantities through the entire spatial domain in the real-time computation process. A modified time integrator is then proposed to synchronize the physical sensors and the numerical model using inverse dynamics. In particular, an efficient inverse force identification method is derived using implicit time integration. The second-order ordinary differential formulation and its projection-based reduced-order modeling is used to avoid two times larger degrees of freedom within the state space form. Then, the Tikhonov regularization noise-filtering algorithm is employed instead of Kalman filtering. The performance of the proposed method is investigated on both numerical and experimental testbeds under sinusoidal and random excitation loading conditions. In the experimental test, the algorithm is implemented on a single-board computer, including inverse force identification and unmeasured response prediction. The results show that the virtual sensing algorithm can accurately identify unmeasured information, forces, and displacements throughout the vibration model in real time in a very limited computing environment.Comment: 24 Pages, 15 Figures, 10 Table

Multilingual Question Answering with High Portability on Relational Databases

This paper describes a highly-portable multilingual question answering system on multiple relational databases. We apply semantic category and pattern-based grammars, into natural language interfaces to relational databases. Lexico-semantic pattern (LSP) and multi-level grammars achieve portability of languages, domains, and DBMSs. The LSP-based linguistic processing does not require deep analysis that sacrifices robustness and flexibility, but can handle delicate natural language questions. To maximize portability, we drive various dependent parts into two tight corners, i.e., language-dependent part into front linguistic analysis, and domain-dependent and database-dependent parts into backend SQL query generation

Reconstruction of 3D Interacting Solids of Revolution from 2D Orthographic Views

3D CAD is replacing 2D CAD to improve efficiency of product design and manufacturing. Therefore, converting legacy 2D drawings into 3D solid models is required. CSG based approaches reconstruct solid models from orthographic views more efficiently than traditional B-rep based approaches. A major limitation of CSG based approaches has been the limited domain of objects that can be handled. This paper aims at extending the capabilities of CSG based approaches by proposing a hint-based recognition of interacting solids of revolution. This approach can handle interacting solids of revolution as well as isolated solids of revolution

Design of a LIOR-Based De-Dust Filter for LiDAR Sensors in Off-Road Vehicles

LiDAR sensors have played an important role in a variety of related applications due to their merits of providing high-resolution and accurate information about the environment. However, their detection performance significantly degrades under dusty conditions, thereby making the whole perception of the vehicles prone to failure. To deal with this problem, we designed a de-dust filter using a LIOR filtering technique that offers a viable method of eliminating dust particles from the measurement data. Experimental results confirm that the proposed method is robust in the face of dust particles by successfully removing them from the measured point cloud with good filtering accuracy while maintaining rich information about the environment