Showing papers on "Robustness (computer science) published in 1993"

Variable structure control: a survey

Abstract: A tutorial account of variable structure control with sliding mode is presented. The purpose is to introduce in a concise manner the fundamental theory, main results, and practical applications of this powerful control system design approach. This approach is particularly attractive for the control of nonlinear systems. Prominent characteristics such as invariance, robustness, order reduction, and control chattering are discussed in detail. Methods for coping with chattering are presented. Both linear and nonlinear systems are considered. Future research areas are suggested and an extensive list of references is included. >

Variable structure control of nonlinear systems: a new approach

Abstract: A new approach for the design of variable structure control (VSC) of nonlinear systems is presented. It is based on a new method called the reaching law method, and is complemented by a sliding-mode equivalence technique. They facilitate the design of the system dynamics in all three modes of a VSC system including the sliding, reaching, and steady-state modes. Invariance and robustness properties are discussed. The approach is applied to a robot manipulator to demonstrate its effectiveness. >

Robust receding horizon control of constrained nonlinear systems

Abstract: We present a method for the construction of a robust dual-mode, receding horizon controller which can be employed for a wide class of nonlinear systems with state and control constraints and model error. The controller is dual-mode. In a neighborhood of the origin, the control action is generated by a linear feedback controller designed for the linearized system. Outside this neighborhood, receding horizon control is employed. Existing receding horizon controllers for nonlinear, continuous time systems, which are guaranteed to stabilize the nonlinear system to which they are applied, require the exact solution, at every instant, of an optimal control problem with terminal equality constraints. These requirements are considerably relaxed in the dual-mode receding horizon controller presented in this paper. Stability is achieved by imposing a terminal inequality, rather than an equality, constraint. Only approximate minimization is required. A variable time horizon is permitted. Robustness is achieved by employing conservative state and stability constraint sets, thereby permitting a margin of error. The resultant dual-mode controller requires considerably less online computation than existing receding horizon controllers for nonlinear, constrained systems. >

Synchronization of Lorenz-based chaotic circuits with applications to communications

Abstract: A circuit implementation of the chaotic Lorenz system is described. The chaotic behavior of the circuit closely matches the results predicted by numerical experiments. Using the concept of synchronized chaotic systems (SCS's), two possible approaches to secure communications are demonstrated with the Lorenz circuit implemented in both the transmitter and receiver. In the first approach, a chaotic masking signal is added at the transmitter to the message, and at the receiver, the masking is regenerated and subtracted from the received signal. The second approach utilizes modulation of the coefficients of the chaotic system in the transmitter and corresponding detection of synchronization error in the receiver to transmit binary-valued bit streams. The use of SCS's for communications relies on the robustness of the synchronization to perturbations in the drive signal. As a step toward further understanding the inherent robustness, we establish an analogy between synchronization in chaotic systems, nonlinear observers for deterministic systems, and state estimation in probabilistic systems. This analogy exists because SCS's can be viewed as performing the role of a nonlinear state space observer. To calibrate the robustness of the Lorenz SCS as a nonlinear state estimator, we compare the performance of the Lorenz SCS to an extended Kalman filter for providing state estimates when the measurement consists of a single noisy transmitter component. >

Global adaptive output-feedback control of nonlinear systems. II. Nonlinear parameterization

Abstract: For pt.I, see ibid., p.17-32 (1993). The problem of designing global output-feedback robust stabilizing controls for a class of single-input single-output minimum-phase uncertain nonlinear systems with known and constant relative degree is addressed. They are assumed to be linear with respect to the input and nonlinear with respect to an unknown constant parameter vector. The nonlinearities depend on the output only. The nonlinearities may be uncertain and are only required to be bounded by known smooth functions. The order of the robust compensator is equal to the relative degree minus one and is static when the relative degree is one. A self-tuning version of the robust control capable of achieving set point regulation is developed in which the control gains are tuned by an output-feedback adaptive algorithm. When the parameter vector enters linearly, the self-tuning regulator does not require the knowledge of parameter bounds and guarantees set point regulation for the same class of systems considered in Part I. >

Robust Control: Systems With Uncertain Physical Parameters

Abstract: Contents: Examples for Modelling of Plants with Uncertain Parameters.- Control System Structures.- Analysis and Design.- Classical Stability Tests Applied to Uncertain Polynomials.- Testing Sets.- Value Set Construction.- The Stability Radius.- Single-Loop Feedback Structures.- Gamma-Stability.- Robustness of Sampled-Data Control Systems.- Parameter Space Design.- Design by Optimizing a Vector Performance Index.- The Four-Wheel Car Steering Model.- Polynomials and Polynomial Equations.

General-purpose sliding-mode controller for DC/DC converter applications

Abstract: A general-purpose sliding-mode controller is described, which can be applied to most DC-DC power converter topologies. It has the same circuit complexity as standard current-mode controllers, but provides extreme robustness and speed of response against supply, load, and parameter variations. Moreover, contrary to other sliding-mode techniques, the proposed solution features constant switching frequency in the steady state, synchronization to external triggers, and absence of steady-state errors in the output voltage. >

Validation of A-Posteriori Error Estimators by Numerical Approach

Abstract: : A numerical methodology which determines the quality (or robustness) of a-posteriori error estimators is described. The methodology accounts precisely for the factors which affect the quality of error estimators for finite-element solutions of linear elliptic problems, namely, the local geometry of the grid and the structure of the solution. The methodology can be employed to check the robustness of any estimator for the complex grids which are used in engineering computations.

Non-identifier-based high-gain adaptive control

Abstract: High-gain stabilizability.- Almost strict positive realness.- Universal adaptive stabilization.- Universal adaptive tracking.- Robustness.- Performance.- Exponential stability of the terminal system.

An adaptive input shaping control scheme for vibration suppression in slewing flexible structures

Abstract: The application of an input precompensation scheme for vibration suppression in slewing flexible structures, with particular application to flexible-link robotic manipulator systems, is considered. The control from such input shaping schemes corresponds to a feedforward term that convolves in real time the desired reference input with a sequence of impulses and produces a vibration-free output. The robustness of such an algorithm with respect to modal frequency variations is not satisfactory but can be improved by convolving the input with a longer sequence of impulses, the tradeoff being a decrease in the transient response speed. An adaptive precompensation scheme that can be implemented by combining a frequency domain identification scheme, used to estimate the modal frequencies online, with a subsequent scheme for adjusting the spacing between the impulses is proposed. The combined adaptive input shaping scheme provides the most rapid slew that results in a vibration-free output. Experimental results for a single flexible link are presented to verify the technique. >

Sliding mode and classical controllers in magnetic levitation systems

Abstract: An experimental comparison is made between a sliding-mode controller and a classical controller for stabilizing and commanding a magnetic levitation system. The sliding-mode method can be applied to a nonlinear system in the global sense, and the issues of performance and robustness to modeling uncertainties and disturbances can be directly incorporated in the design as tradeoff parameters. >

Genetic algorithms in controller design and tuning

Abstract: A three-phased framework for learning dynamic system control is presented. A genetic algorithm is employed to derive control rules encoded as decision tables. Next, the rules are automatically transformed into comprehensible form by means of inductive machine learning. Finally, a genetic algorithm is applied again to optimize the numerical parameters of the induced rules. The approach is experimentally verified on a benchmark problem of inverted pendulum control, with special emphasis on robustness and reliability. It is also shown that the proposed framework enables exploiting available domain knowledge. In this case, genetic algorithm makes qualitative control rules operational by providing interpretation of symbols in terms of numerical values. >

NE/SQP: A robust algorithm for the nonlinear complementarity problem

Abstract: In this paper, we present a new iterative method for solving the nonlinear complementarity problem. This method, which we call NE/SQP (for Nonsmooth Equations/Successive Quadratic Programming), is a damped Gauss--Newton algorithm applied to solve a certain nonsmooth-equation formulation of the complementarity problem; it is intended to overcome a major deficiency of several previous methods of this type. Unlike these earlier algorithms whose convergence critically depends on a solvability assumption on the subproblems, the NE/SQP method involves solving a sequence of nonnegatively constrained convex quadratic programs of the least-squares type; the latter programs are always solvable and their solution can be obtained by a host of efficient quadratic programming subroutines. Hence, the new method is a robust procedure which, not only is very easy to describe and simple to implement, but also has the potential advantage of being capable of solving problems of very large size. Besides the desirable feature of robustness and ease of implementation, the NE/SQP method retains two fundamental attractions of a typical member in the Gauss--Newton family of algorithms; namely, it is globally and locally quadratically convergent. Besides presenting the detailed description of the NE/SQP method and the associated convergence theory, we also report the numerical results of an extensive computational study which is aimed at demonstrating the practical efficiency of the method for solving a wide variety of realistic nonlinear complementarity problems.

Learning piecewise control strategies in a modular neural network architecture

Abstract: The authors describe a multinetwork, or modular, neural network architecture that learns to perform control tasks using a piecewise control strategy. The architecture's networks compete to learn the training patterns. As a result, a plant's parameter space is adaptively partitioned into a number of regions, and a different network learns a control law in each region. This learning process is described in a probabilistic framework and learning algorithms that perform gradient ascent in a log-likelihood function are discussed. Simulations show that the modular architecture's performance is superior to that of a single network on a multipayload robot motion control task. >

Performance of CDMA mobile communication systems using antenna arrays

Abstract: The use antenna arrays in cellular code division multiple access mobile communications is studied. Techniques to localize each mobile within the cell and to generate tracking adaptive receive (and transmit) beams are addressed. The authors show that such enhancement of the CDMA system results in increased system capacity and improved robustness to power control errors. Preliminary simulation results are presented for capacity and robustness improvements for typical scenarios. >

Robust stability of uncertain time-delay systems and its stabilization by variable structure control

Abstract: In this paper, two main results for uncertain time-delay systems are derived. The first result is the presentation of a new robust stability criterion for uncertain time-delay systems. The second result is the successful application of the concept of variable structure control to the stabilization problem of uncertain time-delay systems. The robustness and stability degree of perturbed systems in the sliding mode are also discussed. Last, some examples are included to illustrate our results.

Sliding-mode controller design for spacecraft attitude tracking maneuvers

Abstract: A robust sliding-mode control law that deals with spacecraft attitude tracking problems is presented. Two important natural properties related to the spacecraft model of motion are discussed. It is shown that by using these properties and the second method of Lyapunov theory, the system stability in the sliding mode can be easily achieved. The success of the sliding-mode controller and its robustness relating to uncertainties are illustrated by an example of multiaxial attitude tracking maneuvers. >

Control of Nonlinear Systems Using Terminal Sliding Modes

Abstract: Many robotic systems would, in the future, be required to operate in environments that are highly unstructured and active, i.e., possessing means of self-actuation. Although a significant volume of results exist in model-based, robust and adaptive control literature, general issues pertinent to the performance of such control systems remain unresolved, e.g., feasibility of implementing high gain switches for control robustness. It is also pointed out that in certain applications, control switching can be very detrimental to the overall system. The primary focus of this paper is development of a new approach to control synthesis for robust robot operations in unstructured environments. To enhance control performance with full model information, we introduce the notion of terminal convergence, and develop control laws based upon a new class of sliding modes, denoted terminal sliders

A new approach to adaptive robust control

Abstract: A new approach is given for the design of adaptive robust control in the frequency domain. Starting with an initial model of a stable plant and a robust stabilizing controller, the new (windsurfer) approach allows the bandwidth of the closed-loop system to be increased progressively through an iterative control-relevant system identification and control design procedure. The method deals with both undermodelling and measurement noise issues. Encouraging results are obtained in the simulations that illustrate the new idea.

Robust Time-Delay Control

Abstract: A method is presented to minimize residual vibration of structures or lightly damped servomechanisms. The method, referred to as the proportional plus multiple delay control, involves the use of multiple time delays in conjunction with a proportional part to cancel the dynamics of the system in a robust fashion. An interesting characteristic of the controller involves addition of a basic single time-delay control unit in cascade to the existing controller, for every additional requirement of robustness

Robust and adaptive supervisory control of discrete event systems

Abstract: Both robust and adaptive supervisory control in discrete-event systems are discussed. It is assumed that the system G to be controlled is not known exactly. It is only known either that it belongs to a set or that it has certain lower and upper bounds. The task of robust supervision is to synthesize a supervisor that realizes a given desired behavior for all possible G. A necessary and sufficient condition for the existence of such a robust supervisor is derived. Based on this condition, a robust supervisory control and observation problem of synthesizing a robust supervisor whose behavior is both legal and acceptable is solved. Adaptive supervision is discussed. As the system progresses, the information on occurrences of events may help to resolve or reduce uncertainties. >

Robust stability analysis of constrained l1‐norm model predictive control

Abstract: Sufficient conditions for robust closed-loop stability of a class of dynamic matrix control (DMC) systems are presented. The l1-norm is used in the objective function of the on-line optimization, thus resulting in a linear programming problem. The ideas of this work, however, are expandable to other DMC-type controllers. The keys to the stability conditions are: to use an end-condition in the moving horizon on-line optimization; to have coefficients of the move suppression term in the objective function of the on-line optimization satisfy certain inequalities; and to express the uncertainty as deviations in the unit pulse response coefficients of the nominal plant. These deviations and disturbances must also satisfy certain inequalities. An off-line tuning procedure for robust stability and performance of a class of DMC controllers is also included, which determines an optimal moving horizon length and optimal values for coefficients of the move suppression term. The applicability of our approach is elucidated through numerical simulations.

Acoustical and Environmental Robustness in Automatic Speech Recognition

Abstract: This dissertation describes a number of algorithms developed to increase the robustness of automatic speech recognition systems with respect to changes in the environment These algorithms attempt to improve the recognition accuracy of speech recognition systems when they are trained and tested in different acoustical environments, and when a desk-top microphone (rather than a close-talking microphone) is used for speech input Without such processing, mismatches between training and testing conditions produce an unacceptable degradation in recognition accuracy Two kinds of environmental variability are introduced by the use of desk-top microphones and different training and testing conditions: additive noise and spectral tilt introduced by linear filtering An important attribute of the novel compensation algorithms described in this thesis is that they provide joint rather than independent compensation for these two types of degradation Acoustical compensation is applied in our algorithms as an additive correction in the cepstral domain This allows a higher degree of integration within SPHINX, the Carnegie Mellon speech recognition system, that uses the cepstrum as its feature vector Therefore, these algorithms can be implemented very efficiently Processing in many of these algorithms is based on instantaneous signal-to-noise ratio (SNR), as the appropriate compensation represents a form of noise suppression at low SNRs and spectral equalization at high SNRs The compensation vectors for additive noise and spectral transformations are estimated by minimizing the differences between speech feature vectors obtained from a “standard” training corpus of speech and feature vectors that represent the current acoustical environment In our work this is accomplished by a minimizing the distortion of vector-quantized cepstra that are produced by the feature extraction module in SPHINX In this dissertation we describe several algorithms including the SNR-Dependent Cepstral Normalization, (SDCN) and the Codeword-Dependent Cepstral Normalization (CDCN) With CDCN, the accuracy of SPHINX when trained on speech recorded with a close-talking microphone and tested on speech recorded with a desk-top microphone is essentially the same obtained when the system is trained and tested on speech from the desk-top microphone An algorithm for frequency normalization has also been proposed in which the parameter of the bilinear transformation that is used by the signal-processing stage to produce frequency warping is adjusted for each new speaker and acoustical environment The optimum value of this parameter is again chosen to minimize the vector-quantization distortion between the standard environment and the current one In preliminary studies, use of this frequency normalization produced a moderate additional decrease in the observed error rate