This chapter presents a general overview of previously developed methodologies for modelling, simulation and control of flexible manipulators. A selection of currently available flexible manipulator experimental systems in various research laboratories and outside laboratory environments are introduced and their features and design merits described. A structured overview of common applications and future research prospects and applications of flexible and hybrid manipulators are provided.

This chapter presents a dynamics modelling approach for flexible robotic manipulators. The driving motivation for this chapter is to understand the dynamics of such systems from a control point of view. A general framework is presented that provides an adequate basis for analysis and control of flexible manipulators aimed at terrestrial or orbital applications. To this end, the generalized coordinates chosen to describe the elastic deformation are based on the Ritz approximation, and the approach to arrive at the dynamics model of a single flexible link is the principle of virtual powers, or Jourdain's principle, leading to a Lagrangian description for the elastic deformation and a Eulerian description for the rigid-body motion. A rigid flexible-rigid body is modelled. The evolution to the multi-link case is then natural considering the topology of a serial link manipulator. Two procedures are presented, the first is the O(N³) composite inertia method and the second is the O(N) articulated body method.

This chapter presents numerical approaches based on finite difference (FD) and finite element (FE) techniques for dynamic simulation of single-link flexible manipulator systems. A finite-dimensional simulation of the flexible manipulator system is developed using an FD discretisation of the dynamic equation of motion of the manipulator. A methodology is then presented for obtaining the dynamic model of a lightweight flexible manipulator using FE/Lagrangian technique. Structural damping, hub inertia and payload are incorporated in the dynamic model, which is then represented in a state-space form. Simulation results characterising the dynamic behaviour of the manipulator are presented and discussed for both FD and FE methods. A comparative study of the FD and the FE methods of dynamic modelling of flexible manipulators on the basis of computational accuracy, efficiency and demand are then considered. The performance of the algorithms is assessed with experimental results in time and frequency domains.

This chapter deals with the development and validation of tools for simulation of flexible space robotic systems using Symofros, a modelling and simulation software program that was developed at the Robotics Section of the Canadian Space Agency. The first part of the chapter describes general modelling issues, Symofros' soft ware architecture, and advanced modelling techniques for flexible arms. The second part presents an experimental validation of the flexible-link model used in Symofros. Additionally, an experimental approach for the end-point detection of flexible links will be discussed. The third part introduces the special purpose dextrous manipulator (SPDM) test verification facility, which is used to emulate the contact dynamic effects arising during pay load insertion and extraction tasks of the SPDM on-board the International Space Station (ISS) based on hardware-in-the-loop simulation. Furthermore, an on-board training simulator that is used by astronauts to evaluate their ability to operate the robotic arm on-board the ISS will be introduced.

This chapter provides an overview of the use of real-time command shaping to limit vibration inflexible robotic systems. Smoothing of commands to reduce system vibration is an old idea. However, command shaping did not come into widespread use until inexpensive digital controllers were available to implement the techniques in real time. Shaped commands can address multiple resonant frequencies and can be designed to be very robust to system modelling errors. An array of examples illustrate the effect that these command shaping methods have on the performance of flexible systems.

While several control schemes have been proposed for force and position control of rigid robot manipulators, only a few related to flexible manipulators have been published so far. In this chapter the main force and position control strategies for flexible manipulators are surveyed and two different approaches are illustrated in depth. One achieves force and position regulation in an indirect way, by computing the joint and deflection variables in the presence of an external contact via a suit able closed-loop inverse kinematics scheme. The other exploits singular perturbation techniques to design force and position control schemes similar to those adopted for rigid robot manipulators, with an additional control action used to stabilise the fast dynamics related to link flexibility. A planar two-link flexible manipulator in contact with a compliant surface is considered, and simulation studies demonstrating the performance of the control techniques are presented and discussed.

It is well known that conventional robot manipulators made of rigid links incorporate strongly coupled dynamics, and this situation is the source of many control problems. This difficulty is more pronounced when considering the control of flexible link manipulators. Taking into account the physical properties of flexible manipulators and their inherent vibratory behaviour it is proposed in this chapter to consider the control problem in the multivariable frequency domain. Such an approach is first introduced for analysing the coupling of a mixed rigid-flexible two-dimensional (2D) manipulator. The approach is then extended to the case of a 2D flexible manipulator. Following these analyses, a figure of merit to quantify the interaction between links is introduced, and the resultant designs for obtaining row and column dominance of both 2D manipulators are presented. Finally, an approach involving the manipulator Jacobian is proposed to define the control law. Finite element analysis is used in all cases to simulate the manipulators, and the models are experimentally validated.

The aim of this chapter is to show the effectiveness of soft computing in the design of adaptive controllers for a single-link, flexible manipulator. The first part utilizes fuzzy logic (FL) and genetic algorithms (GAs) in the design of an offline modular neural network controller while the second part combines fuzzy logic and GAs in the construction of online proportional derivative (PD), proportional, integral (PI) and proportional, integral, derivative (PID)-type FL controllers. Experimental results, demonstrating the effectiveness of the methods for an experimental single-link, flexible manipulator are presented and discussed.

Dynamic modelling and control of manipulators involving both rigid and flexible links are presented in this chapter. Various modelling approaches are discussed, and as an example, the equations of motion of a rigid-flexible two-link manipulator are derived using Hamilton s principle. Discretisation of the governing equations and the effects of coupling between rigid and flexible degrees of freedom are examined. The response to an impact with a rigid surface is studied to investigate the effect of link flexibility on the dynamic response. Various control strategies used in rigid-flexible manipulators are reviewed. As an example, the performance of a non-model-based independent joint proportional, derivative (PD) control is demonstrated. Trajectory tracking and various implementation issues are also discussed.

This chapter presents the development of SCEFMAS (Simulation and Control Environment for Flexible MAnipulator Systems) software package. This is a user-friendly interactive software environment based on Matlab and associated tool boxes. The environment incorporates a finite difference (FD) simulation algorithm of a constrained planar single-link flexible manipulator system for analysis, simulation, modelling of dynamic behaviour of the system. The package also incorporates a range of control techniques, including open-loop control such as filtered command, Gaussian-shaped and command shaping, collocated and non-collocated closed-loop control methods of fixed and adaptive types, and intelligent soft computing control techniques. The environment allows the user to set-up the system by providing its physical parameters and to select the controller type through an interactive graphical user interface (GUI). Data analyses can be performed in time and frequency domains on the controller and system input and outputs signals. The environment is suitable as an education package as well as for research purposes for investigating and developing various simulations, modelling and controller designs for flexible manipulator systems.