1,014 research outputs found
Robust Adaptive Control of Linear Parameter-Varying Systems with Unmatched Uncertainties
This paper presents a robust adaptive control solution for linear
parameter-varying (LPV) systems with unknown input gain and unmatched nonlinear
(state- and time-dependent) uncertainties based on the adaptive
control architecture and peak-to-peak gain (PPG) analysis/minimization from
robust control. Specifically, we introduce new tools for stability and
performance analysis leveraging the PPG bound of an LPV system that is
computable using linear matrix inequality (LMI) techniques. A
piecewise-constant estimation law is introduced to estimate the lumped
uncertainty with quantifiable error bounds, which can be systematically
improved by reducing the estimation sampling time. We also present a new
approach to attenuate the unmatched uncertainty based on the PPG minimization
that is applicable to a broad class of systems with linear nominal dynamics. In
addition, we derive transient and steady-state performance bounds in terms of
the input and output signals of the actual closed-loop system as compared to
the same signals of a virtual reference system that represents the possibly
best achievable performance. Under mild assumptions, we prove that the
transient performance bounds can be uniformly reduced by decreasing the
estimation sampling time, which is subject only to hardware limitations. The
theoretical development is validated by extensive simulations on the
short-period dynamics of an F-16 aircraft
Output Feedback M-MRAC Backstepping With Aerospace Applications
The paper presents a certainty equivalence output feedback backstepping adaptive control design method for the systems of any relative degree with unmatched uncertainties without over-parametrization. It uses a fast prediction model to estimate the unknown parameters, which is independent of the control design. It is shown that the system's input and output tracking errors can be systematically decreased by the proper choice of the design parameters. The approach is applied to aerospace control problems and tested in numerical simulations
Integrated Optimal and Robust Control of Spacecraft in Proximity Operations
With the rapid growth of space activities and advancement of aerospace science and technology, many autonomous space missions have been proliferating in recent decades. Control of spacecraft in proximity operations is of great importance to accomplish these missions. The research in this dissertation aims to provide a precise, efficient, optimal, and robust controller to ensure successful spacecraft proximity operations. This is a challenging control task since the problem involves highly nonlinear dynamics including translational motion, rotational motion, and flexible structure deformation and vibration. In addition, uncertainties in the system modeling parameters and disturbances make the precise control more difficult. Four control design approaches are integrated to solve this challenging problem. The first approach is to consider the spacecraft rigid body translational and rotational dynamics together with the flexible motion in one unified optimal control framework so that the overall system performance and constraints can be addressed in one optimization process. The second approach is to formulate the robust control objectives into the optimal control cost function and prove the equivalency between the robust stabilization problem and the transformed optimal control problem. The third approach is to employ the è-D technique, a novel optimal control method that is based on a perturbation solution to the Hamilton-Jacobi-Bellman equation, to solve the nonlinear optimal control problem obtained from the indirect robust control formulation. The resultant optimal control law can be obtained in closedorm, and thus facilitates the onboard implementation. The integration of these three approaches is called the integrated indirect robust control scheme. The fourth approach is to use the inverse optimal adaptive control method combined with the indirect robust control scheme to alleviate the conservativeness of the indirect robust control scheme by using online parameter estimation such that adaptive, robust, and optimal properties can all be achieved. To show the effectiveness of the proposed control approaches, six degree-offreedom spacecraft proximity operation simulation is conducted and demonstrates satisfying performance under various uncertainties and disturbances
Modeling and Direct Adaptive Robust Control of Flexible Cable-Actuated Systems
Cable-actuated systems provide an effective method for precise motion transmission over various distances in many robotic systems. In general, the use of cables has many potential advantages such as high-speed manipulation, larger payloads, larger range of motion, access to remote locations and applications in hazardous environments. However, cable flexibility inevitably causes vibrations and poses a concern in high-bandwidth, high-precision applications
M-MRAC With Normalization
This paper presents a normalization based modified reference model adaptive control method for multi-input multi-output (MIMO) uncertain systems in the presence of bounded external disturbances. It has been shown that desired tracking performance can be achieved for the system's output and input signals with the proper choice of design parameters. The resulting adaptive control signal satisfies a second order linear time invariant (LTI) system, which is the effect of the normalization term in the adaptive laws. This LTI system provides the guideline for the design parameter selection. The theoretical findings are confirmed via a simulation example
Model Based Control of Soft Robots: A Survey of the State of the Art and Open Challenges
Continuum soft robots are mechanical systems entirely made of continuously
deformable elements. This design solution aims to bring robots closer to
invertebrate animals and soft appendices of vertebrate animals (e.g., an
elephant's trunk, a monkey's tail). This work aims to introduce the control
theorist perspective to this novel development in robotics. We aim to remove
the barriers to entry into this field by presenting existing results and future
challenges using a unified language and within a coherent framework. Indeed,
the main difficulty in entering this field is the wide variability of
terminology and scientific backgrounds, making it quite hard to acquire a
comprehensive view on the topic. Another limiting factor is that it is not
obvious where to draw a clear line between the limitations imposed by the
technology not being mature yet and the challenges intrinsic to this class of
robots. In this work, we argue that the intrinsic effects are the continuum or
multi-body dynamics, the presence of a non-negligible elastic potential field,
and the variability in sensing and actuation strategies.Comment: 69 pages, 13 figure
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