Esta proposta de dissertação de mestrado trata da aplicação de Estimadores Algébricos em sistemas de controle como alternativa ao uso de observadores. Devido à dificuldade de obtenção de resultados teóricos, dificuldade essa oriunda da natureza complexa dos estimadores algébricos, o trabalho é desenvolvido através do estudo de casos. Considera-se que a topologia de controle é a união de uma técnica tradicional de controle (por exemplo, uma realimentação de estado ou o método do torque calculado) com a estimação algébrica. Os resultados obtidos defendem a idéia de que os Estimadores Algébricos, quando usados como estimadores de estado, permitem obter um desempenho e uma robustez que se aproxima muito do desempenho e a robustez da mesma lei de controle no caso em que o estado é perfeitamente conhecido.; The control topology that is considered in this work is the union of a traditional control technique (e.g. a state feedback or the computed torque method) with the Algebraic Estimator. The obtained results reinforce the common sense about this class of estimators, that the use of Algebraic Estimators may produce the performance, robustness and noise immunity that mimics the case where perfect information of the state is available.
In this article, we provide invariance conditions for control systems whose dynamics are given by measure driven differential inclusions. The solution concept plays a critical role in the extension of the conventional conditions for the impulsive control context. A couple of examples illustrating the specific features of impulsive control systems are included.
Introduction to the state-space approach to control system analysis and control synthesis. State-space representation of dynamic systems; controllability and observability; state-space realizations of transfer functions; and canonical forms. Design of controllers using state-space methods, including pole placement and optimal control methods. Introduction to the Kalman filter. Limitations on performance of control systems from classical and state-space perspectives. Introduction to robustness of multivariable control systems, using frequency domain techniques. From the course home page: Course Description The goal of this subject is to teach the fundamentals of control design and analysis using state-space methods. This includes both the practical and theoretical aspects of the topic. By the end of the course, students should be able to design controllers using state-space methods and evaluate whether these controllers are "robust," that is, if they are likely to work well in practice.
In this brief, we consider impulsive control for master-slave synchronization schemes that consist of identical chaotic Lur'e systems. Impulsive control laws are investigated which make use of linear static measurement feedback, instead of full state feed
New manufacturing control paradigms are being developed to improve the ability of enterprises to respond to change. However, there are no agreed definitions and methodologies for the evaluation and comparison of achievements of different manufacturing control systems approaches, making also difficult the communication and cooperation between manufacturing control systems developers. In this paper some qualitative performance indicators are identified and defined - re-configurability, robustness and agility - and methodologies for their evaluation are suggested.
This paper studies robustness of MIMO control systems with parametric
uncertainties, and establishes a lower dimensional robust stability criterion.
For control systems with interval transfer matrices, we identify the minimal
testing set whose stability can guarantee the stability of the entire uncertain
set. Our results improve the results in the literature, and provide a
constructive solution to the robustness of a family of MIMO control systems.
Several concepts on the measure of observability, reachability, and
robustness are defined and illustrated for both linear and nonlinear control
systems. Defined by using computational dynamic optimization, these concepts
are applicable to a wide spectrum of problems. Some questions addressed include
the observability based on user-information, the determination of strong
observability vs. weak observability, partial observability of complex systems,
the computation of $L^2$-gain for nonlinear control systems, and the measure of
reachability in the presence of state constraints. Examples on dynamic systems
defined by both ordinary and partial differential equations are shown.; Comment: 31 pages, 10 figures
In this paper, we consider the L∞-bounded robust control problem for a class of nonlinear cascade systems with disturbances. Sufficient conditions are provided under which a hard bound is imposed on the system performance measure. The backstepping appro
This paper investigates the synthesis of discrete supervisors for hybrid systems where the control objective is to enforce a language inclusion specification in the presence of plant uncertainty. The discussion is set within Willems' behavioural system theory, where we find a relationship between robustness of closed-loop performance and earlier results on abstraction based synthesis. From this relationship, we develop our main result: a method for the synthesis of robust supervisory controllers. Note that virtually any engineering system must possess some amount of robustness in order to fulfil even minimal reliability requirements. This commonly accepted fact is of a particular importance for hybrid control systems, since the motivating application areas are safety-critical and high-confidence systems as air traffic control or medical instrumentation.
This paper discusses the problem of robust H∞ control for singular impulsive uncertain systems. Some new fundamental properties of singular systems with impulse effect are derived. Based on the Riccati inequality approach, sufficient conditions for robu
We present two novel approaches for obtaining stability robustness information about linear time-invariant systems with norm-bounded time-varying output multiplicative perturbations using Vinnicombe metrics. First, a time-varying Vinnicombe metric approximation between a nominal linear time-invariant system and the perturbed linear time-varying system is developed, and we show that a calculable tight upper bound may be placed on the approximation for a subclass of small, periodic output multiplicative errors. Second, we show that a worst-case time-invariant Vinnicombe metric may be used to obtain stability robustness information about the perturbed time-varying system.
This paper presents a joint space formulation for robot manipulator's hybrid motion/force control. The motivations come from 1) extending the previous work to general (either constrained or redundant) robots; and 2) improving the robustness against disturbances originated at the joint level. Contact geometry and closed-loop dynamics will be derived in this paper, also a joint space hybrid control scheme will be proposed. At the end, we show some simulation results to verify the applicability of our theory on a constrained (4-degree-of-freedom) robot WAM.
In this paper, a novel stability robustness test for systems with linear time-varying uncertainties is introduced. The advantages of the stability robustness test lie in the fact that it can cope with multi-input multi-output, stable, or unstable systems
A pure image-based strategy for visual servo control of a class of dynamic systems is proposed. The proposed design concerns the dynamics of unmanned aerial vehicles capable of quasi-stationary flight (hover and near hover flight). The visual servo control task considered is to locate the camera relative to a stationary target. The paper extends earlier work, by weakening the assumption on the construction of the visual error used. In prior work some inertial information was used in the error construction to guarantee the passivity properties of the control design. In this paper the visual error is defined purely in terms of the 2D image features derived from the camera signal.
We propose a model validation procedure that consists of a prediction error identification experiment with a full order model. It delivers a parametric uncertainty ellipsoid and a corresponding set of parameterized transfer functions, which we call prediction error (PE) uncertainty set. Such uncertainty set differs from the classical uncertainty descriptions used in robust control analysis and design. We develop a robust control analysis theory for such uncertainty sets, which covers two distinct aspects: (1) Controller validation. We present necessary and sufficient conditions for a specific controller to stabilize - or to achieve a given level of performance with - all systems in such PE uncertainty set. (2) Model validation for robust control. We present a measure for the size of such PE uncertainty set that is directly connected to the size of a set controllers that stabilize all systems in the model uncertainty set. This allows us to establish that one uncertainty set is better tuned for robust control design than another, leading to control-oriented validation objectives.
In a recent work, a new linear adaptive controller based on certainty-equivalence and backstepping design, which promises a level of transient and asymptotic performance comparable to that of the tuning functions adaptive backstepping controller without using high order nonlinearities, was proposed for linear time invariant systems. The proposal was supplemented with robustness and performance analysis in the presence of modeling uncertainties. In this note, the same idea is used to develop a new linear adaptive controller for slowly time varying systems with modeling uncertainties. The new adaptive control scheme guarantees robustness with respect to modeling errors via normalizing damping, parameter projection, and static normalization. Use of normalizing damping is essential in protecting the "linearity" of the system, which plays a key role in reaching the stability and robustness results.
The development of robust controllers for high-speed flywheel rotors supported on active magnetic bearings (AMBs) has been extensively studied over the past decade. Such flywheels can be used as energy momentum wheels (EMWs) onboard spacecraft, and pose a challenging control problem due to their high flexibility, nontrivial parametric uncertainty, and rotor-speed dependence. A combined H∞ loop shaping and μ-synthesis approach is used in this paper to design controllers for EMWs supported on AMBs. This combination between these two well-established control methodologies is novel to the design of robust controllers for such systems. H∞ loop shaping guarantees (through the specification of loop-shaping weights) closed-loop performance and robustness to generic unstructured coprime factor uncertainty, whereas robustness to highly directional parametric uncertainty is incorporated through a μ-synthesis design. Furthermore, in order to reduce the computational complexity of the control design and the order of the synthesized controllers, a method is proposed in this paper to reduce the number of states that depend on the rotor speed. The proposed methodology is demonstrated through numerical simulations and experimental results.
The purpose of this paper is to describe systematic analysis and design tools for robust control problems with l∞ criteria. We first generalize the Hill-Moylan-Willems framework for dissipative systems to accommodate l∞ criteria, and then derive state