Vision-Based Fuzzy 2D Motion Control of a Model Helicopter

©2006 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or distribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.Presented at NAFIPS 2006 : 2006 Annual Meeting of the North American Fuzzy Information Processing Society : Montréal, Canada, 3-6 June 2006.DOI: 10.1109/NAFIPS.2006.365497In this paper the 2D motion of a model helicopter is studied. The position control of a 2D model helicopter falls into complex nonlinear problems domain which makes it rather hard. In this paper a fuzzy controller is proposed to stabilize the helicopter on a designated target. The 3D model of the helicopter is simplified to derive a 2D model and all the states are assumed to be measurable. Based on the model, it was possible to decouple the position and orientation control of the helicopter. However the two parts are related through a fuzzy rule base. To verify the proposed method a simulation program is written in C++ which takes advantages of OpenGL to enable having 3D features. The response graphs are then presented       

Closed-loop control for cardiopulmonary management and intensive care unit sedation using digital imaging

This dissertation introduces a new problem in the delivery of healthcare, which could result in lower cost and a higher quality of medical care as compared to the current healthcare practice. In particular, a framework is developed for sedation and cardiopulmonary management for patients in the intensive care unit. A method is introduced to automatically detect pain and agitation in nonverbal patients, specifically in sedated patients in the intensive care unit, using their facial expressions. Furthermore, deterministic as well as probabilistic expert systems are developed to suggest the appropriate drug dose based on patient sedation level. This framework can be used to automatically control the level of sedation in the intensive care unit patients via a closed-loop control system. Specifically, video and other physiological variables of a patient can be constantly monitored by a computer and used as a feedback signal in a closed-loop control architecture. In addition, the expert system selects the appropriate drug dose based on the patient's sedation level. In clinical intensive care unit practice sedative/analgesic agents are titrated to achieve a specific level of sedation. The level of sedation is currently based on clinical scoring systems. In general, the goal of the clinician is to find the drug dose that maintains the patient at a sedation score corresponding to a moderately sedated state. This is typically done empirically, administering a drug dose that usually is in the effective range for most patients, observing the patient's response, and then adjusting the dose accordingly. However, the response of patients to any drug dose is a reflection of the pharmacokinetic and pharmacodynamic properties of the drug and the specific patient. In this research, we use pharmacokinetic and pharmacodynamic modeling to find an optimal drug dosing control policy to drive the patient to a desired sedation score.Ph.D.Committee Chair: Haddad, Wassim M.; Committee Co-Chair: Tannenbaum, Allen R.; Committee Member: Bailey, James M.; Committee Member: Clarke, John-Paul; Committee Member: Feron, Eri

Controller Synthesis with Guaranteed Closed-Loop Phase Constraints

©2007 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or distribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.Presented at the 46th IEEE Conference on Decision and Control, New Orleans, LA, USA, Dec. 12-14, 2007.DOI: 10.1109/CDC.2007.4434291In this paper, we present an analysis and synthesis framework for guaranteeing that the phase of a single-input, single-output closed-loop transfer function is contained in the interval [-alpha, alpha] for a given alpha>0 at all frequencies. Specifically, we first derive a sufficient condition involving a frequency domain inequality for guaranteeing a given phase constraint. Next, we use the Kalman-Yakubovich-Popov theorem to derive an equivalent time domain condition. In the case where alpha=pi/2, we show that frequency and time domain sufficient conditions specialize to the positivity theorem. Furthermore, using linear matrix inequalities, we develop a controller synthesis framework for guaranteeing a phase constraint on the closed-loop transfer function. Finally, we extend this synthesis framework to address mixed gain and phase constraints on the closed-loop transfer function

Receding horizon control of uncertain systems

In the first part of this thesis stability robustness for quasi-infinite Receding Horizon Control (RHC) of an uncertain nonlinear system is investigated. A sufficient condition is developed for stability of a general nonlinear RHC system subject to perturbations. The result is further specialized to linear systems. For this case it is demonstrated that the closed-loop system is stable out side a bounded set containing the desired equilibrium point upon satisfaction of an LMI constraint along with a bounded perturbation assumption. The new result is applied for control of a mobile robot system which demonstrates the validity of the approach. In the second part, RHC of an uncertain nonlinear system is considered where the computational time is not negligible. The existing method proposes a solution to deal with non-zero computation time by predicting the states at the next sampling time, which provides the controller with sufficient time to generate the required input signal. This work extends this previous result by applying neighboring extremal paths theory to improve the performance further through the addition of a correction phase to the algorithm. The proposed method is composed of three steps: state prediction, trajectory generation, and trajectory correction. The new approach is applied for control of a mobile robot system, which demonstrates significant performance improvements over the existing method

Uncertain Nonlinear Receding Horizon Control Systems Subject to Non-Zero Computation Time

©2005 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or distribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.Presented at the 44th IEEE Conference on Decision and Control, and the European Control Conference 2005, Seville, Spain, December 12-15, 2005.In this paper Receding Horizon Control (RHC) of an uncertain nonlinear system is considered where the computation time is non-negligible. In a well-known method, the solution process of the optimal control problem is started one sampling period in advance by using the prediction of the initial conditions, thus giving the controller a reasonable deadline to complete the optimization process. The current work suggests the use of the theory of neighboring extremal paths to improve the performance of the existing method by adding a correction phase to the previous method and therefore recovering the exact solution in the presence of prediction errors. An immediate result would be that the properties of the RHC techniques involving zero computation time would be valid for practical systems in the actual implementation, where a zero computation time is unachievable. The new approach is applied for the control of a mobile robot system which demonstrates significant performance improvements over the existing method