161 research outputs found
On Observer-Based Control of Nonlinear Systems
Filtering and reconstruction of signals play a fundamental role in modern signal processing, telecommunications, and control theory and are used in numerous applications. The feedback principle is an important concept in control theory. Many different control strategies are based on the assumption that all internal states of the control object are available for feedback. In most cases, however, only a few of the states or some functions of the states can be measured. This circumstance raises the need for techniques, which makes it possible not only to estimate states, but also to derive control laws that guarantee stability when using the estimated states instead of the true ones. For linear systems, the separation principle assures stability for the use of converging state estimates in a stabilizing state feedback control law. In general, however, the combination of separately designed state observers and state feedback controllers does not preserve performance, robustness, or even stability of each of the separate designs. In this thesis, the problems of observer design and observer-based control for nonlinear systems are addressed. The deterministic continuous-time systems have been in focus. Stability analysis related to the Positive Real Lemma with relevance for output feedback control is presented. Separation results for a class of nonholonomic nonlinear systems, where the combination of independently designed observers and state-feedback controllers assures stability in the output tracking problem are shown. In addition, a generalization to the observer-backstepping method where the controller is designed with respect to estimated states, taking into account the effects of the estimation errors, is presented. Velocity observers with application to ship dynamics and mechanical manipulators are also presented
Control Of Nonh=holonomic Systems
Many real-world electrical and mechanical systems have velocity-dependent constraints in their dynamic models. For example, car-like robots, unmanned aerial vehicles, autonomous underwater vehicles and hopping robots, etc. Most of these systems can be transformed into a chained form, which is considered as a canonical form of these nonholonomic systems. Hence, study of chained systems ensure their wide applicability. This thesis studied the problem of continuous feed-back control of the chained systems while pursuing inverse optimality and exponential convergence rates, as well as the feed-back stabilization problem under input saturation constraints. These studies are based on global singularity-free state transformations and controls are synthesized from resulting linear systems. Then, the application of optimal motion planning and dynamic tracking control of nonholonomic autonomous underwater vehicles is considered. The obtained trajectories satisfy the boundary conditions and the vehicles\u27 kinematic model, hence it is smooth and feasible. A collision avoidance criteria is set up to handle the dynamic environments. The resulting controls are in closed forms and suitable for real-time implementations. Further, dynamic tracking controls are developed through the Lyapunov second method and back-stepping technique based on a NPS AUV II model. In what follows, the application of cooperative surveillance and formation control of a group of nonholonomic robots is investigated. A designing scheme is proposed to achieves a rigid formation along a circular trajectory or any arbitrary trajectories. The controllers are decentralized and are able to avoid internal and external collisions. Computer simulations are provided to verify the effectiveness of these designs
Feedback Linearization Techniques for Collaborative Nonholonomic Robots
Collaborative robots performing tasks together have significant advantages over a single
robot. Applications can be found in the fields of underwater robotics, air traffic control,
intelligent highways, mines and ores detection and tele-surgery. Collaborative wheeled
mobile robots can be modeled by a nonlinear system having nonholonomic constraints.
Due to these constraints, the collaborative robots arc not stabilizable at a point by
continuous time-invariant feedback control laws. Therefore, linear control is ineffective,
even locally, and innovative design techniques are needed. One possible design technique
is feedback control and the principal interest of this thesis is to evaluate the best feedback
control technique.
Feedback linearization is one of the possible feedback control techniques. Feedback
linearization is a method of transforming a nonlinear system into a linear system using
feedback transformation. It differs from conventional Taylor series linearization since it
is achieved using exact coordinates transformation rather than by linear approximations
of the system. Linearization of the collaborative robots system using Taylor series results
in a linear system which is uncontrollable and is thus unsuitable. On the other hand, the
feedback linearized control strategies result in a stable system. Feedback linearized
control strategies can he designed based on state or input, while both state and input
linearization can be achieved using static or dynamic feedback.
In this thesis, a kinematic model of the collaborative nonholonomic robots is derived,
based on the leader-follower formation. The objective of the kinematic model is to
facilitate the design of feedback control strategies that can stabilize the system and
Minimize the error between the desired and actual trajectory. The leader-follower
formation is used in this research since the collaborative robots are assumed to have
communication capabilities only.
The kinematic model for the leader-follower formation is simulated using
MATLAB/Simulink. A comparative assessment of various feedback control strategies is
evaluated. The leader robot model is tested using five feedback control strategies for
different trajectories. These feedback control strategies are derived using cascaded
system theory, stable tracking method based on linearization of corresponding error
model, approximation linearization, nonlinear control design and full state linearization
via dynamic feedback. For posture stabilization of the leader robot, time-varying and full
state dynamic feedback linearized control strategies are used. For the follower robots
using separation bearing and separation-separation formation, the feedback linearized
control strategies are derived using input-output via static feedback.
Based on the simulation results for the leader robot, it is found that the full state dynamic
feedback linearized control strategy improves system performance and minimizes the
mean of error more rapidly than the other four feedback control strategies. In addition to
stabilizing the system, the full state dynamic feedback linearized control strategy
achieves posture stabilization. For the follower robots, the input-output via static
feedback linearization control strategies minimize the error between the desired and
actual formation. Furthermore, the input-output linearized control strategies allow
dynamical change of the formation at run-time and minimize the disturbance of formation
change. Thus, for a given feasible trajectory, the full state feedback linearized strategy for
the leader robot and input-output feedback linearized strategies for the follower robots are
found to be more efficient in stabilizing the system
A path planning and path-following control framework for a general 2-trailer with a car-like tractor
Maneuvering a general 2-trailer with a car-like tractor in backward motion is
a task that requires significant skill to master and is unarguably one of the
most complicated tasks a truck driver has to perform. This paper presents a
path planning and path-following control solution that can be used to
automatically plan and execute difficult parking and obstacle avoidance
maneuvers by combining backward and forward motion. A lattice-based path
planning framework is developed in order to generate kinematically feasible and
collision-free paths and a path-following controller is designed to stabilize
the lateral and angular path-following error states during path execution. To
estimate the vehicle state needed for control, a nonlinear observer is
developed which only utilizes information from sensors that are mounted on the
car-like tractor, making the system independent of additional trailer sensors.
The proposed path planning and path-following control framework is implemented
on a full-scale test vehicle and results from simulations and real-world
experiments are presented.Comment: Preprin
Finite-Time Stabilization of Dynamic Nonholonomic Wheeled Mobile Robots with Parameter Uncertainties
Adaptive control of uncertain nonholonomic systems in finite time
summary:In this paper, the finite-time stabilization problem of chained form systems with parametric uncertainties is investigated. A novel switching control strategy is proposed for adaptive finite-time control design with the help of Lyapunov-based method and time-rescaling technique. With the proposed control law, the uncertain closed-loop system under consideration is finite-time stable within a given settling time. An illustrative example is also given to show the effectiveness of the proposed controller
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