Physical model-based inversion in control systems design using bond graph representation Part 1: Theory

This paper presents a new concept for calculating of the bond graph observer gains based on a graphical approach that investigates the Lyapunov Second Method in order to conclude about the observer stability and to search for the adequate gains that stabilize the observer. This new observer is used in the mode identification procedure. In fact, the observer’s residues allow the differentiation between the current mode and the other system modes. In order to guarantee the efficiency of the mode identification procedure, a new bond graph approach is proposed. It concerns the discernibility between the modes in bond graph language. First, it deals with the R-discernibility that introduces the definition of the discernibility through the structural parity residual then returns to a simple calculation of some matrices’ ranks in bond graph language. Second, another bond graph technique is applied to define the discernibility throughout the equivalency between the realizations.

<div class="htmlview paragraph">A series of examples, involving normal mode representations of a flexible railcar and various suspension models, is presented illustrating the use of bond graph techniques for assembling a structural dynamic system model from component models. Bond graph techniques are related to other methods for achieving the same goal, and the unique features of bond graph techniques are pointed out. Not only does the bond graph provide a graphical representation of the organized system equations, but also it allows the use of ENPORT programs for automating the process of manipulating the component relations into an explicit-state space format suitable for simulation or analysis. Nonlinear and active systems which interact with structural dynamic components are readily handled using bond graph techniques.</div>

Electric Power Steering (EPS) systems have many merits over traditional hydraulic power steering systems in fuel economy, variable assist capabilities and favorable road feeling by virtue of adjustment assist characteristic with adopting assist motor in replacement of hydraulic pump. This paper aims at modeling the mechanical parts, the assist motor and electronic control unit by bond graph technique and simulating system dynamic performance regarding vehicle maneuverability and stability and driver’s steering feel by Matlab/Simulink. The simulation results provide that the bond graph EPS model can reflect stability and dynamic steering characteristic in effect.

Various methods are available to compute kinematics and dynamics in the case of spatial mechanisms. These methods are cumbersome and laborious for large and multibody spatial mechanisms. The bond graph technique is a powerful alternative tool for modeling. A four-link closed-chain 3R2S (3Revolute 2Spherical) spatial mechanism stands out among the other four-link closed-chain spatial mechanisms due to its ability to be used in a number of applications. The main aim of this paper is to compute the inverse kinematics of the mechanism using the bond graph structure of the system. In this paper, modeling of a four-link closed-chain 3R2S spatial mechanism has been conducted using a multibond graph approach. Inverse kinematics of the spatial mechanism, under various applications, has been directly obtained from the bond graph modeling. MATLAB coding for simulation has been done directly from the multibond graph without explicitly deriving system equations. The simulation results have been analyzed and discussed using various plots.

Modeling of musculoskeletal structure and function using a modular bond graph approach

Modelling and simulation of the multi-scroll chaotic attractors using bond graph technique

A program for handling multiple phases of the design cycle in process control system design

PurposeDrawing on Simons's levers of control (LoC) framework, the primary aim of this study is to advance an understanding of the balance between empowerment and constraint in a non-profit UK organisation. In particular, this study examines the antecedents and manifestations of LoC (im)balance, in relation to employees' level of engagement with the control systems in place.Design/methodology/approachFor this study, 27 semi-structured interviews were conducted with different organisational members, from directors to non-managerial staff, to gain an in-depth appreciation of the main differences between managerial intentions in the design of management control systems (MCS) and employee perceptions regarding the role of such systems.FindingsThis research reveals that suppression of interactive systems and internal inconsistencies between different types of controls hinder the balance between empowerment and constraint. This imbalance is then found to have important consequences for employee buy-in, in some cases, defeating the purposes of control.Research limitations/implicationsThis study enhances our understanding of the gap between the design of control systems and the employee perceptions of it in an unusual organisational setting (non-profit and bringing together clinical and non-clinical staff and operations).Originality/valueThe study of MCS and its role in organisations has long been the focus of both academic and practitioner research. Yet, while extant literature focused on management's perspective on MCS, few studies have explored employees' attitudes and behaviours that accompany the implementation of control. What is more, little is known about the specific uses and behavioural outcomes of MCS in the context of non-profit organisations. Drawing on Simons's LoC framework, this paper addresses these gaps in the literature and investigates the balance between control and empowerment of employees in a UK non-profit organisation with significant clinical remit.

Control systems are pervasive in our lives. Our homes have environmental controls. The appliances we use, such as the washing machine, microwave, etc. carry embedded controllers in them. We fly in airplanes and drive automobiles that extensively use control systems. The industrial plants that produce consumer goods run on process control systems. The recent drive toward automation has increased our reliance on control systems technology. This book discusses control systems design from a model-based perspective for dynamic system models of single-input single-output type. The emphasis in this book is on understanding and applying the techniques that enable the design of effective control systems in multiple engineering disciplines. The book covers both time-domain and the frequency-domain design methods, as well as controller design for both continuous-time and discrete-time systems. MATLAB© and its Control Systems Toolbox are extensively used for design. Technical topics discussed in the book include: • Mathematical models of physical systems • Analysis of transfer function and state variable models • Control systems design objectives • Control system design with root locus • Control system design in the state-space • Control system design of sampled-data systems • Compensator design with frequency response methods

Control systems are pervasive in our lives. Our homes have environmental controls. The appliances we use, such as the washing machine, microwave, etc. carry embedded controllers in them. We fly in airplanes and drive automobiles that extensively use control systems. The industrial plants that produce consumer goods run on process control systems. The recent drive toward automation has increased our reliance on control systems technology. This book discusses control systems design from a model-based perspective for dynamic system models of single-input single-output type. The emphasis in this book is on understanding and applying the techniques that enable the design of effective control systems in multiple engineering disciplines. The book covers both time-domain and the frequency-domain design methods, as well as controller design for both continuous-time and discrete-time systems. MATLAB© and its Control Systems Toolbox are extensively used for design. Technical topics discussed in the book include: • Mathematical models of physical systems • Analysis of transfer function and state variable models • Control systems design objectives • Control system design with root locus • Control system design in the state-space • Control system design of sampled-data systems • Compensator design with frequency response methods

Manufacturing planning and control systems (MPC) design or redesign in the current dynamic industrial environment is a complex process and must be based on a true understanding of the business needs of a particular enterprise and the physical facilities and resources available to satisfy those needs. Interdomain relationships between various elements, both within and outside the system, must be considered in this context; a necessary requirement for any integrated systems design. Many past efforts in the field seem to lack this approach and as a result changes in the business needs are difficult, if not impossible, to incorporate in the current MPC systems without a major redesign. This chapter outlines the major design issues in this context and proposes a methodology to develop an integrated system's model for implementa­ tion. The methodology starts with an analysis of the business needs and considers the coordination and communications requirements between various disparate units and domains of an organization. To aid the design process, the methodology uses many well-known tools and methods in its various stages; their functions and usefulness are discussed. The chapter gives an example to show how the methodology can be used to develop a MPC system in real life .

This article describes the design of a linear observer–linear controller-based robust output feedback scheme for output reference trajectory tracking tasks in the case of nonlinear, multivariable, nonholonomic underactuated mobile manipulators. The proposed linear feedback scheme is based on the use of a classical linear feedback controller and suitably extended, high-gain, linear Generalized Proportional Integral (GPI) observers, thus aiding the linear feedback controllers to provide an accurate simultaneous estimation of each flat output associated phase variables and of the exogenous and perturbation inputs. This information is used in the proposed feedback controller in (a) approximate, yet close, cancelations, as lumped unstructured time-varying terms, of the influence of the highly coupled nonlinearities, and (b) the devising of proper linear output feedback control laws based on the approximate estimates of the string of phase variables associated with the flat outputs simultaneously provided by the disturbance observers. Simulations reveal the effectiveness of the proposed approach.

A method is described for using nonlinear programing in the computer-aided design of airplane control systems. It is assumed that the quality of such systems depends on many criteria. These criteria are included in the constraints vector (instead of attempting to combine them into a single scalar criterion, as is usually done), and the design proceeds through a sequence of nonlinear programing solutions in which the designer varies the specification of sets of requirements levels. The method is applied to design of a lateral stability augmentation system (SAS) for a fighter airplane, in which the requirements vector is chosen from the official handling-qualities specifications. Results are shown for several simple SAS configurations designed to obtain desirable handling qualities over all design flight conditions with minimum feedback gains. The choice of the final design for each case is not unique but depends on the designer's decision as to which achievable set of requirements levels represents the best for that system. Results indicate that constant gain systems can substantially exceed the highest required levels of handling qualities in all design flight conditions of the example considered. The role of the designer as a decision maker, interacting with the computer program, is discussed. Advantages of this type of designer-computer interaction are emphasized. Desirable extensions of the method are indicated.

10 - Robust design of intelligent control systems to mitigate earthquake-induced vibrations under uncertain conditions

Nonlinear inverse dynamic models can be utilized in various parts of advanced model-based control system design: reference trajectory optimization, feedforward control and feedback linearization. In this paper, a new synthesis approach for nonlinear inverse dynamic models of satellites with flexible structures is presented. For satellite configurations with unstable zero dynamics, a stable inverse model approximation is proposed which has been successfully applied to robots with flexible bodies. This inverse modeling approach is part of the newly developed DLR Space Systems Library for objectoriented modeling and simulation of satellites and launchers in a detailed space environment. For satellites with flexible structures, the library provides models for normal simulation mode and the necessary tools to directly generate approximate inverse models. In this paper, trajectory optimization is shown to be an important use case for inverse dynamic models. By inversion based reformulation of the trajectory optimization problem, the optimal reference motion of the control system can be determined in a reliable and efficient way.