F-14 modeling study

Preliminary results in the application of a closed loop pilot/simulator model to the analysis of some simulator fidelity issues are discussed in the context of an air to air target tracking task. The closed loop model is described briefly. Then, problem simplifications that are employed to reduce computational costs are discussed. Finally, model results showing sensitivity of performance to various assumptions concerning the simulator and/or the pilot are presented

Quantum control theory and applications: A survey

This paper presents a survey on quantum control theory and applications from a control systems perspective. Some of the basic concepts and main developments (including open-loop control and closed-loop control) in quantum control theory are reviewed. In the area of open-loop quantum control, the paper surveys the notion of controllability for quantum systems and presents several control design strategies including optimal control, Lyapunov-based methodologies, variable structure control and quantum incoherent control. In the area of closed-loop quantum control, the paper reviews closed-loop learning control and several important issues related to quantum feedback control including quantum filtering, feedback stabilization, LQG control and robust quantum control.Comment: 38 pages, invited survey paper from a control systems perspective, some references are added, published versio

Multivariable Adaptive Control Design Under Internal Model Control Structure.

A new adaptive multivariate control scheme has been devised. The method combines the best characteristics of conventional adaptive systems and internal model control (IMC) structure. The control scheme builds by itself the required models and avoids the ambiguities in the definition of performance specifications. The problem of plant inversion associated with the IMC structure has been solved. The method introduced in this work is based on the properties of the Smith-McMillan form. However, the method does not require the explicit determination of the form. Furthermore, the computation of a stable plant inverse requires only matrix inversion and scalar polynomial factorization. The resulting algorithm is suitable for on-line operation. The control schemed is implemented through the following stages: (1) Identification. The parameters of a multivariable ARX model are estimated using a recursive least square algorithm with variable forgetting factor. The input and output orders can be used as additional degrees of freedom. The algorithm developed shows good numerical characteristics with fast convergence even for a large number of parameters. (2) Computation of the manipulated variables. The model is used to determine a controller following the IMC approach. The resulting equations are solved to compute the required manipulated variables. The algorithm for system inversion allows computations to be executed on-line. (3) Filtering. The usual filters of the IMC approach are also used in the adaptive scheme. The objective is to reduce the sensitivity of the controller. Only non-adaptive non-interactive filters have been considered. The results with first order low pass filters are satisfactory. The bandwidth of the filter is used as an additional tuning parameter. The adaptive control strategy has been extensively tested using computer simulation. The tests include extensions to non-linear plants. Comparisons with non-adaptive IMC control show the advantage of the new scheme developed in this work

Nonlinear Modeling and Control of Driving Interfaces and Continuum Robots for System Performance Gains

With the rise of (semi)autonomous vehicles and continuum robotics technology and applications, there has been an increasing interest in controller and haptic interface designs. The presence of nonlinearities in the vehicle dynamics is the main challenge in the selection of control algorithms for real-time regulation and tracking of (semi)autonomous vehicles. Moreover, control of continuum structures with infinite dimensions proves to be difficult due to their complex dynamics plus the soft and flexible nature of the manipulator body. The trajectory tracking and control of automobile and robotic systems requires control algorithms that can effectively deal with the nonlinearities of the system without the need for approximation, modeling uncertainties, and input disturbances. Control strategies based on a linearized model are often inadequate in meeting precise performance requirements. To cope with these challenges, one must consider nonlinear techniques. Nonlinear control systems provide tools and methodologies for enabling the design and realization of (semi)autonomous vehicle and continuum robots with extended specifications based on the operational mission profiles. This dissertation provides an insight into various nonlinear controllers developed for (semi)autonomous vehicles and continuum robots as a guideline for future applications in the automobile and soft robotics field. A comprehensive assessment of the approaches and control strategies, as well as insight into the future areas of research in this field, are presented.First, two vehicle haptic interfaces, including a robotic grip and a joystick, both of which are accompanied by nonlinear sliding mode control, have been developed and studied on a steer-by-wire platform integrated with a virtual reality driving environment. An operator-in-the-loop evaluation that included 30 human test subjects was used to investigate these haptic steering interfaces over a prescribed series of driving maneuvers through real time data logging and post-test questionnaires. A conventional steering wheel with a robust sliding mode controller was used for all the driving events for comparison. Test subjects operated these interfaces for a given track comprised of a double lane-change maneuver and a country road driving event. Subjective and objective results demonstrate that the driver’s experience can be enhanced up to 75.3% with a robotic steering input when compared to the traditional steering wheel during extreme maneuvers such as high-speed driving and sharp turn (e.g., hairpin turn) passing. Second, a cellphone-inspired portable human-machine-interface (HMI) that incorporated the directional control of the vehicle as well as the brake and throttle functionality into a single holistic device will be presented. A nonlinear adaptive control technique and an optimal control approach based on driver intent were also proposed to accompany the mechatronic system for combined longitudinal and lateral vehicle guidance. Assisting the disabled drivers by excluding extensive arm and leg movements ergonomically, the device has been tested in a driving simulator platform. Human test subjects evaluated the mechatronic system with various control configurations through obstacle avoidance and city road driving test, and a conventional set of steering wheel and pedals were also utilized for comparison. Subjective and objective results from the tests demonstrate that the mobile driving interface with the proposed control scheme can enhance the driver’s performance by up to 55.8% when compared to the traditional driving system during aggressive maneuvers. The system’s superior performance during certain vehicle maneuvers and approval received from the participants demonstrated its potential as an alternative driving adaptation for disabled drivers. Third, a novel strategy is designed for trajectory control of a multi-section continuum robot in three-dimensional space to achieve accurate orientation, curvature, and section length tracking. The formulation connects the continuum manipulator dynamic behavior to a virtual discrete-jointed robot whose degrees of freedom are directly mapped to those of a continuum robot section under the hypothesis of constant curvature. Based on this connection, a computed torque control architecture is developed for the virtual robot, for which inverse kinematics and dynamic equations are constructed and exploited, with appropriate transformations developed for implementation on the continuum robot. The control algorithm is validated in a realistic simulation and implemented on a six degree-of-freedom two-section OctArm continuum manipulator. Both simulation and experimental results show that the proposed method could manage simultaneous extension/contraction, bending, and torsion actions on multi-section continuum robots with decent tracking performance (e.g. steady state arc length and curvature tracking error of 3.3mm and 130mm-1, respectively). Last, semi-autonomous vehicles equipped with assistive control systems may experience degraded lateral behaviors when aggressive driver steering commands compete with high levels of autonomy. This challenge can be mitigated with effective operator intent recognition, which can configure automated systems in context-specific situations where the driver intends to perform a steering maneuver. In this article, an ensemble learning-based driver intent recognition strategy has been developed. A nonlinear model predictive control algorithm has been designed and implemented to generate haptic feedback for lateral vehicle guidance, assisting the drivers in accomplishing their intended action. To validate the framework, operator-in-the-loop testing with 30 human subjects was conducted on a steer-by-wire platform with a virtual reality driving environment. The roadway scenarios included lane change, obstacle avoidance, intersection turns, and highway exit. The automated system with learning-based driver intent recognition was compared to both the automated system with a finite state machine-based driver intent estimator and the automated system without any driver intent prediction for all driving events. Test results demonstrate that semi-autonomous vehicle performance can be enhanced by up to 74.1% with a learning-based intent predictor. The proposed holistic framework that integrates human intelligence, machine learning algorithms, and vehicle control can help solve the driver-system conflict problem leading to safer vehicle operations

Variable structure techniques in control system design

During the last twenty years, control theorists belonging almost exclusively to the USSR, have laid down the foundations of variable-structure systems (commonly abbreviated to vsS). As the name implies, such systems are allowed to change their structure through time in accordance with some preassigned algorithm. The theory has demonstrated that some significant advantages could be gained by adopting that approach in the, design of automatic control systems, amongst which are good transient responses and insensitivity to parametric variations and to external disturbances. The VS controller is slightly more complex than a fixed structure design based on standard methods such as state feedback or frequency response techniques, but is a great deal less complex than some adaptive designs. It also lends itself to a straightforward microcomputer implementation. While the theoretical aspect of VSS has been well explored, its general applicability to engineering problems is yet to be established. There are still unanswered questions as to the suitability of the method for practical systems, which invariably contain a certain amount of noise, uncertainties and nonlinearities. The work described in this thesis concentrates on that particular aspect and is, in brief, an investigation of VSS as an engineering design procedure. The theory of VSS is reviewed and the principles are then applied to a number of engineering examples. The performance of the systems are assessed from digital simulation runs, hybrid computation and the microcomputer control of a DC motor