Intelligent Computing for the Management of Changes in Industrial Engineering Modeling Processes

Advancements in engineering modeling have changed the work of engineers during the last two decades. Sophisticated descriptions store information about shape oriented engineering objects and their relationships. Boundary representations of form features constitute shape models. Rules and checks have replaced simple data form of shape model entity attributes. This change of modeling facilitates a next step towards application of computer intelligence at engineering object related decisions. The authors propose a method of intelligent attribute definition for integrated decision assistance environments of modelling systems. This method provides quick and comprehensive assessment of situations for decisions on modification of modeled objects in very complex information environments. The paper starts with an outline of the approach to intelligent decision assistance by the authors. Next, an Internet portal communicated scenario of the proposed modeling is discussed. Following this, multilevel solution for modeling, adding characteristics for engineering objects, and definitions and communications are detailed as essential methods in the proposed modeling. Finally, behaviors for essential classes of modeled objects and an example for the definition of situations and behaviors represent implementation issues

Preliminary Sketch of Possible Fixed Point Transformations for Use in Adaptive Control

In this paper a further step towards a novel approach to adaptive nonlinear control developed at Budapest Tech in the past few years is reported. Its main advantage in comparison with the complicated Lyapunov function based techniques is that it is based on simple geometric considerations on the basis of which the control task can be formulated as a Fixed Point Problem for the solution of which a Contractive Mapping is created that generates an Iterative Cauchy Sequence for Single Input - Single Output (SISO) systems. Consequently it converges to the fixed point that is the solution of the control task. In the formerly developed approaches for monotone increasing or monotone decreasing systems the proper fixed points had only a finite basin of attraction outside of which the iteration might become divergent. The here sketched potential solutions apply a special function built up of the “response function” of the excited system under control and of a few parameters. This function has almost constant value apart from a finite region in which it has a “wrinkle” in the vicinity of the desired solution that is the “proper” fixed point of this function. By the use of an affine approximation of the response function around the solution it is shown that at one of its sides this fixed point is repulsive, while at the opposite side it is attractive. It is shown, too, that at the repulsive side another, so called “false” fixed point is present that is globally attractive, with the exception of the basin of attraction of the “proper” one. This structure is advantageous because a) no divergence can occur in the iteration, b) the convergence to the “false” value can easily be detected, and c) by using some ancillary tricks in the most of the cases the solution can be kicked from the wrong fixed point into the basin of attraction of the “proper one”. In the paper preliminary calculations are presented.N/

Robust Fixed Point Transformations in Adaptive Control Using Local Basin of Attraction

A further step towards a novel approach to adaptive nonlinear control developed at Budapest Tech in the past few years is reported. This approach obviates the use of the complicated Lyapunov function technique that normally provides global stability of convergence at the costs of both formal and essential restrictions, by applying Cauchy sequences of local, bounded basin of attraction in an iterative control that is free of such restrictions. Its main point is the creation of a robust iterative sequence that only slightly depends on the features of the controlled system and mainly is determined be the control parameters applied. It is shown that as far as its operation is considered the proposed method can be located between the robust Variable Structure / Sliding Mode and the adaptive Slotine-Li control in the case of robots or other Classical Mechanical Systems. The operation of these method is comparatively analyzed for a wheel + connected mass system in which this latter component is “stabilized” along one of the spokes of the wheel in the radial direction by an elastic spring. The robustness of these methods is also investigated againts unknown external disturbances of quite significant amplitudes. The numerical simulations substantiate the superiority of the robust fixed point transformations in the terms of accuracy, simplicity, and smoothness of the control signals applied.N/

Improved Numerical Simulation for a Novel Adaptive Control Using Fractional Order Derivatives

A novel control technique is investigated in the adaptive control of a typical paradigm, an approximately and partially modeled cart plus double pendulum system. In contrast to the traditional approaches that try to build up ”complete” and ”permanent” system models it develops ”temporal” and ”partial” ones that are valid only in the actual dynamic environment of the system, that is only within some ”spatio-temporal vicinity” of the actual observations. This technique was investigated for various physical systems via ”preliminary” simulations integrating by the simplest 1st order finite element approach for the time domain. In 2004 INRIA issued its SCILAB 3.0 and its improved numerical simulation tool ”Scicos” making it possible to generate ”professional”, ”convenient”, and accurate simulations. The basic principles of the adaptive control, the typical tools available in Scicos, and others developed by the authors, as well as the improved simulation results and conclusions are presented in the contribution

Simple Kinematic Design for Evading the Forced Oscillation of a Car-Wheel Suspension System

An adaptive control damping the forced vibration of a car while passing along a bumpy road is investigated. It is based on a simple kinematic description of the desired behavior of the damped system. A modified PID controller containing an approximation of Caputo’s fractional derivative suppresses the high-frequency components related to the bumps and dips, while the low frequency part of passing hills/valleys are strictly traced. Neither a complete dynamic model of the car nor ’a priori’ information on the surface of the road is needed. The adaptive control realizes this kinematic design in spite of the existence of dynamically coupled, excitable internal degrees of freedom. The method is investigated via Scicos-based simulation in the case of a paradigm. It was found that both adaptivity and fractional order derivatives are essential parts of the control that can keep the vibration of the load at bay without directly controlling its motion

Adaptive nonlinear vibration damping inspired by the concept of fractional derivatives

In this paper a simple nonlinear, adaptive approach inspired by the CRONE method is presented for vibration control. It replaces the fractional derivatives with time-invariant Green functions. Being completed by a nonlinear feedback term it makes the positive definite weighted moving average of the square of the error converge to zero in the kinematic design of the desired damping the realization of which is guaranteed by the controller's adaptive nature. The burden of designing a sophisticated linear controller is evaded. The applicability of the approach is illustrated via simulations for a damped linear oscillator under external excitation at its resonance frequency. The adaptive loop simply successively maps the observed system behavior to the desired one without exerting any effort to identify the reasons of the differences. It is expected to be useful for solving even more complicated vibration damping problems with unmodeled and uncontrolled internal degrees of freedom.N/

Centralized and Decentralized Applications of a Novel Adaptive Control

An adaptive control based on the combination of a novel branch of Soft Computing and fractional order derivatives was applied to control two incompletely modeled, nonlinear, coupled dynamic systems. Each of them contained one internal degree of freedom neither directly modeled/observed nor actuated. As alternatives the decentralized and the centralized control approaches were considered. In each case, as a starting point, a simple, incomplete dynamic model predicting the state-propagation of the modeled axes was applied. In the centralized approach this model contained all the observable and controllable joints. In the decentralized approach two similar initial models were applied for the two coupled subsystems separately. The controllers were restricted to the observation of the generalized coordinates modeled by them. It was expected that both approaches had to be efficient and successful. Simulation examples are resented for the control of two double pendulum-cart systems coupled by a spring and two bumpers modeled by a quasi-singular potential. It was found that both approaches were able to “learn” and to manage this control task with a very similar efficiency. In both cases the application of near integer order derivatives means serious factor of stabilization and elimination of undesirable fluctuations. Since in many technical fields the application of simple decentralized controllers is desirable the present approach seems to be promising and deserves further attention and research.N/

Scicos Based Investigation of an Adaptive Vibration Damping Technique Using Fractional Order Derivatives

Detailed investigation of a simple nonlinear, active, adaptive approach of controlling the oscillation of a car proceeding on a bumpy road is presented. Its key idea is a frequency dependent control of the strictness of a traditional PID controller by applying fractional order derivatives in a simple kinematic design without any respect to the dynamic model of the system. The adaptive part of the controller relieves the designer of dealing with the system’s dynamics within the frames of some linear control, and guarantees the implementation of this design. The operation of the approach is illustrated by the use of INRIA’s scientific co-simulator Scicos for a rough model of a car. Well interpretable trends were revealed regarding the effect of the variation of the order of derivation, and that of the sampling time of the adaptive loop. These results seem to be promising for actively damping the vibration of systems having unmodeled, uncontrolled internal degrees of freedom.N/

Adaptive nonlinear vibration control based on causal time-invariant green functions and on a novel branch of soft computing

In this paper a simple nonlinear, adaptive approach inspired by the fractional derivatives based CRONE control is presented for vibration damping. Its key idea is replacement of the fractional derivatives with the mathematically less restricted concept of time-invariant Green functions. Instead of the traditional PID feedback terms it applies positive definite weighted moving average of the square of the error plus a nonlinear term making the error converge to zero. In this way simple kinematic design of the desired damping becomes possible. The adaptive part of the controller guarantees the realization of this kinematic design without making it necessary to the designer to have an accurate and complete dynamic model of the system to be controlled or to design sophisticated linear controller. The applicability of the approach is illustrated via simulations for a paradigm consisting of a pair of coupled damper linear oscillators under external excitation. One of the oscillators is not modeled by the controller. The adaptive loop successively maps the observed system behavior to the desired one without exerting any effort to identify the reasons of the differences. The approach was found be useful for solving vibration damping problems with unmodeled and uncontrolled internal degrees of freedom.N/

Adaptive reduction of the order of derivation in the control of a hydraulic differential cylinder

Servo valve controlled hydraulic differential cylinders are non-linear, strongly coupled multivariable electromechanical tools applicable for driving e.g. manipulators. When the piston has finite but considerable velocity with respect to the cylinder the system’s behavior can be “linearized” because the viscous friction i.e. the main source of disturbance is smooth function of this velocity and causes linear damping. When this velocity is in the vicinity of zero the effect of adhesion is the dominating disturbance force that abruptly changes direction depending on the sign of this velocity. Furthermore, at zero relative velocity adhesion can compensate arbitrary forces within certain limits keeping the piston fixed. In the paper a concise application of the Stribeck model of friction and adhesion is reported in an adaptive control in which varying fractional order derivatives are used to reduce the hectic behavior of friction in the case of “critical” trajectories that asymptotically converge to a fixed position and zero velocity. Simulation results made by INRIA’s Scilab are presented. It is concluded that the combined application of the two adaptive techniques reported accurate control can be achieved without knowing the accurate model of the piston-cylinder system.N/