Showing papers on "Robust control published in 1986"

A robust layered control system for a mobile robot

Abstract: A new architecture for controlling mobile robots is described. Layers of control system are built to let the robot operate at increasing levels of competence. Layers are made up of asynchronous modules that communicate over low-bandwidth channels. Each module is an instance of a fairly simple computational machine. Higher-level layers can subsume the roles of lower levels by suppressing their outputs. However, lower levels continue to function as higher levels are added. The result is a robust and flexible robot control system. The system has been used to control a mobile robot wandering around unconstrained laboratory areas and computer machine rooms. Eventually it is intended to control a robot that wanders the office areas of our laboratory, building maps of its surroundings using an onboard arm to perform simple tasks.

A New Adaptive Law for Robust Adaptation without Persistent Excitation

Abstract: A new adaptive law motivated by that given in [1] is proposed for the robust adaptive control of plants with unknown parameters. In this adaptive law the output error e l plays a dual role in the adjustment of the control parameter vector. In the ideal case the adaptive system has bounded solutions; in addition the error equations are uniformly asymptotically stable in the large when the reference input is sufficiently persistently exciting. The adaptive system is also shown to be robust under bounded external disturbances. Finally it is shown that, by suitably modifying the adaptive law, the overall system can be made robust in the presence of unmodeled dynamics of the plant.

Robust adaptive controller designs for robot manipulator systems

Abstract: Adaptive controllers are designed for robot manipulator systems that yield robust trajectory in spite of the unwanted effects of external disturbances and fast maneuvering of the manipulator. These controllers are designed with improved convergence rate and their transient oscillation are reduced considerably. The analyses in this paper stem from the model reference adaptive control techniques. In conjunction with this methodology an optimal auxiliary input is introduced to complete our controller designs. These results are extensively verified on a three-joint revolute manipulator by computer simulations.

General solution of robust tracking problem in two-degree-of-freedom control systems

Abstract: In this note, we study linear time-invariant multivariable systems with two-degree-of-freedom compensators. First, we give a new parametrization of all stabilizing compensators from the viewpoint of independent design of transfer function and robustness property. Second, utilizing this parametrization, we solve a general robust tracking problem including the case of nonsquare plants, and show that "tracking" and "robustness" can be independently specified in two-degree-of-freedom control systems.

Practical robust control of robot arm using variable structure system

Abstract: The high-gain effect of sliding mode control based on VSS (Variable Structure System) suppresses the uncertainties due to parametric variations, external disturbances and variable payloads. The resulting system is completely robust whereas the obtained control law is simple and easy to be applied to on-line computer control. In this paper, the sliding mode controller for MIMO (Multi-Input Multi-Output) robot arm is realized using "Estimated Inertia Matrix" which has inevitably small uncertainties dependent on arm structure and inaccuracies of computation. This technique contributes to practical design of sliding mode for MIMO system compared with the well-known "Hierarchy Method". In addition, simple nonlinear compensation and proper continuous function (instead of relay type component) with "Integral Mode" are implemented to diminish chattering caused by switching input. The validity of this control is confirmed in simulations and experiments where the system shows the robust performances in spite of the existing nonlinear interactions and unknown parametric changes.

Nonlinear state estimation using sliding observers

Abstract: Sliding controllers have recently been shown to feature excellent robustness and performance properties for specific classes of nonlinear tracking problems. This paper examines the potential use of sliding surfaces for observer design. A particular observer structure including switching terms is shown to have promising properties in the presence of modelling errors and sensor noise.

The control of robot manipulators with bounded input

Abstract: The problem of tracking a desired trajectory in the state space of an n -link robotic manipulator with bounds on the allowable input torque is considered. Using a so-called optimal decision strategy (ODS), a pointwise optimal control law is derived which, at each time t , minimizes the deviation between the vector of joint accelerations and a desired joint acceleration vector, subject to the input constraints. The design of the optimal control law is reduced to the solution of a quadratic programming problem which is solved using the primal-dual method. The solution gives an on-line feedback control scheme for trajectory following in the presence of input constraints. In addition, we extend the above optimal decision strategy to the case where the controller design is based on a simplified model or where the plant itself is imprecisely known. The resulting torque optimization scheme may be incorporated into any existing control scheme to account for input bounds. This has important implications for the problem of deriving robust control schemes that take into account parameter uncertainty and model simplification. Simulations are presented for the case of a three-link manipulator with bounded torque, and our results are compared to the computed torque method. Our simulations show that by optimally adjusting the input torque to each joint when one or more of them saturates, significant improvement in tracking performance can result.

New perturbation bounds for the robust stability of linear state space models

Abstract: In this paper, the problem of robust stability of linear time-invariant systems in state space models is considered. Explicit bounds on linear time-invariant perturbations which do not destabilize the system are given for both unstructured and structured perturbations. These bounds are superior to those reported in the recent literature in two senses: i) they are less conservative and ii) they can be applied to a more general class of systems and perturbations. The bounds are easy to compute numerically. Several simple examples are given to demonstrate the new bounds and compare them with results previously reported.

On Sliding Observers for Nonlinear Systems

Abstract: Sliding controllers have recently been shown to feature excellent robustness and performance properties for specific classes of nonlinear tracking problems. This paper examines the potential use of sliding surfaces for observer design. A particular observer structure including switching terms is shown to have promising properties in the presence of modelling errors and sensor noise.

Robust controller synthesis using the maximum entropy design equations

Abstract: This note presents an application of the optimality conditions obtained in [1] for dynamic compensation in the presence of state-, control-, and measurement-dependent noise. By solving these equations, which represent a fundamental generalization of standard steady-state LQG theory, a series of increasingly robust control designs is obtained for the example considered in [2].

On the predictive functional control of an elastic industrial robot

Abstract: In this paper a new control concept for industrial robots (IR) will be presented which is based on predictive control principles. It can be easily implemented even for elastic mechanical IR structures. Both an excellent performance and robustness with respect to uncertainties or variations of the model parameters can be provided. The proposed algorithm has been practically applied for the point-to-point and path control of a conventional IR (KUKA 160) with elastic mechanical multibody structure. The performance quality will be demonstrated by experimental and simulation results.

Adaptive robust control (convergence, stability and performance)

Abstract: The contributions of this paper are in two main areas. The first is an "integrated" approach to the development of a practical adaptive control algorithm. In particular, we bring many existing ideas together and explore the effect of various design parameters available to a user. We also extend the theory in the following areas: we show how the problem of pole-zero cancellation in the estimated model can be overcome by running parallel estimations and we show how asymptotic tracking can be achieved in the presence of unmodelled dynamics. A feature of our presentation is that we treat continuous and discrete systems in a unified framework.

Positive Realness in Discrete-Time Adaptive Control Systems

Abstract: Recently, it was shown for continuous-time systems, that the positive realness conditions can be satisfied without the need for the prior knowledge about the order and the pole-excess of the controlled plant. Thes results are extended here to discrete-time systems. It is shown that the positive realness conditions can be satisfied in "almost stable" discrete-time multivariable linear systems, namely, systems that can be stabilized via static or dynamic output feedback, including non-minimum phase systems, at the price of bounded rather than vanishing output tracking errors. Satisfaction of the positivity conditions may facilitate implementation of simple adaptive control procedures that maintain robustness in the presence of parasitic dynamics and disturbances.

Optimal Control of Cross-Machine Direction Web Profile with Constraints on the Control Effort

Abstract: Spatial coupling between the control points in a cross-machine profile of a sheet property is a primary concern in cross-machine control problems. The goal of the cross-machine direction (CD) control is to minimize the deviation from a desired profile with certain constraints on the control action. Two approaches, quadratic programming (QP) and quadratic penalty function (QPF), were evaluated for inclusion in a commercial CD control product. The optimal control is obtained from the QP approach, but the QPF which produces near-optimal control, is more robust and easier to implement in real-time applications. A comparison between QP and QPF results is shown by simulated examples. Field test results of the QPF method are also included. The QPF approach is well suited for practical applications and has been successfully incorporated in over 40 commercial installations.

Averaging analysis for discrete time and sampled data adaptive systems

Abstract: We extend our earlier continuous time averaging theorems to the nonlinear discrete time case. We use theorems for the study of the convergence analysis of discrete time adaptive identification and control systems. We also derive instability theorems and use them for the study of robust stability and instability of adaptive control schemes applied to sampled data systems. As a by product we also study the effects of sampling on unmodeled dynamics in continuous time systems.

A robust discrete-time adaptive controller

Abstract: This paper proposes a discrete-time model reference adaptive control algorithm which is robust with respect to stable additive and multiplicative plant uncertainties. The algorithm employs the same controller structure as the one that would be used if the parameters of the dominant part of the plant were known and a robust adaptive law for adjusting the controller parameters. Using essentially the same assumptions that are necessary to design a fixed controller based on the exact knowledge of the dominant part of the plant, we show that the proposed algorithm guarantees boundedness for all signals in the closed loop and "small" residual tracking errors for any bounded initial conditions. In the absence of plant uncertainties, the algorithm guarantees zero residual tracking errors.

Adaptive calibration: An approach to uncertainty modeling and on-line robust control design

Abstract: An approach is presented to the problem of on-line robust control design, referred to here as adaptive calibration. It is an iterative approach which modifies the filter and model structure characteristics used in methods of system identification involving the filtered prediction error. An estimate of model uncertainty is obtained which is then used to predict closed-loop system performance with the new control if it were implemented. If predicted performance does not meet the specified performance the filters and/or model structure are modified to enhance model accuracy in the frequency range required. An analysis is presented along with an illustrative example.

Microprocessor-based robust control of a DC servo motor

Abstract: A multiloop feedback control system supplemented by a complementary controller is used to improve the drive performance of a DC servo motor and reduce sensitivity to parameter variations, nonlinear effects, and other disturbances. Experimental results based on 8086 microprocessor implementation are presented to illustrate improved response and reduced sensitivity.

Practical implications of recent results in robustness of adaptive control schemes

Abstract: Adaptive control is finding its way to the real world life, mainly as result of considerable advances in computer technology and understanding of adaptive control theory. An important number of industrial feasibility studies have been performed and several general purpuse adaptive controllers are now commercially available. In this paper the authors aim at providing a new design approach that allows to obtain a LQ-adaptive controller with an asymptotic reference partial state tracking capability while ensuring fundamental engineering features such as robust stable input-output behaviour, dynamic tracking, offset-free performance and safe operation.

On the robustness of the computed torque technique in manipulator control

Abstract: In this paper, the robustness of the computed torque technique for manipulator control is investigated in the presence of model errors. The robustness analysis is performed in the frequency domain by means of the block Gerschgorin theorem. The block Gerschgorin theorem gives inclusion regions for the eigenvalues of the linearized state space model. The stability of the system close to a trajectory can then be investigated. The results indicate that relatively large errors in the nonlinear feedback compensation of system nonlinearities may be tolerated without affecting system stability. However, even small errors in the computed inertia matrix may result in instability.

Decentralized control for descriptor type systems

Abstract: The decentralized robust servomechanism problem [1] for a linear time-invariant system described by: Tx = Ax + Bu + Ew y = Cx + Du + Fw e = y - yref where E may be singular, is considered in this paper, where u, y, e, w denotes the input, output, error and disturbance respectively for the system. In particular, necessary and sufficient conditions to solve the robust decentralized control problem are obtained and a constructive controller synthesis procedure is given for this class of systems. Some simple examples are given to illustrate the result obtained.

Robust Control Design Techniques for a Class of Nonlinear Systems

Abstract: We consider the design of robust stabilizing control laws for nonlinear systems which are equivalent under C?-state space coordinate transformations and nonlinear feedback to controllable linear systems. We are motivated by the problem of nonlinear control given simplified or uncertain system models. Assuming that certain structure matching conditions are satisfied between the plant and the model of the plant, we reduce the problem to that of stabilizing a perturbed linear system and discuss several design schemes that can be used to guarantee stability. An example of robust tracking for a robot manipulator is given.

Model reference adaptive control of a link flexible arm

Abstract: Based on a model reference adaptive control approach, a robust controller for a one link flexible arm moving along a pre-defined trajectory is proposed. In order to satisfy the perfect model following conditions, the model is chosen from the linearized model of the system as optimally controlled. The nominal trajectory is commanded to the system by means of a dynamic filter. Simulation results for the prototype in the laboratory show the improvements obtained with the outer adaptive feed-back loop with respect to a pure optimal control regulator. Robustness is finally tested by varying the nominal payload mass.

Design Method for Robust Compliant Motion for Manipulators

Abstract: This paper describes a controller-design methodology to develop a robust compliant motion for robot manipulators. The achievement of the target dynamics (the target impedance is introduced in Part one (22) 1 and preservation of stabilty robustness in the presence of bounded model uncertainties are the key issues in the design method. State-feedback and force-feedforward gains are chosen to guarantee the achievement of the target dynamics, while preserving stability in the presence of model uncertainties. In general, the closed-loop behavior of a system cannot be shaped arbitrarily over an arbitrarily wide frequency range. We prove, however, that a special class of impedances that represent our set of performance specifications are mathematically achievable through state-feedback end interaction-force feedforward and we offer a geometrical design method for achieving them in the presence of model uncertainties.