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Engineering - Control Engineering | Theory of Robot Control

Theory of Robot Control


Canudas de Wit, Carlos, Siciliano, Bruno, Bastin, Georges (Eds.)

Softcover reprint of the original 1st ed. 1996, XVI, 392 pp. 31 figs.

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  • The most important results from current research within a single unified framework
  • The result of a close co-operative project by the Zodiac, a group of twelve researchers from France, Italy and Belgium
The advent of new high-speed microprocessor technology together with the need for high-performance robots created substantial and realistic place for control theory in the field of robotics. Since the beginning of the 80's, robotics and control theory have greatly benefited from a mutual fertiliza­ tion. On one hand, robot models (inherently highly nonlinear) have been used as good case studies for exemplifying general concepts of analysis and design of advanced control theory; on the other hand, robot manipulator by using new control algorithms. Fur­ performance has been improved thermore, many interesting robotics problems, e. g. , in mobile robots, have brought new control theory research lines and given rise to the development of new controllers (time-varying and nonlinear). Robots in control are more than a simple case study. They represent a natural source of inspiration and a great pedagogical tool for research and teaching in control theory. Several advanced control algorithms have been developed for different types of robots (rigid, flexible and mobile), based either on existing control techniques, e. g. , feedback linearization and adaptive control, or on new control techniques that have been developed on purpose. Most of those results, although widely spread, are nowadays rather dispersed in different journals and conference proceedings. The purpose of this book is to collect some of the most fundamental and current results on theory of robot control in a unified framework, by editing, improving and completing previous works in the area.

Content Level » Research

Keywords » Normal - control - control theory - differential geometry - feedback - identification - modeling - motion control - reading - robot - stability - stabilization

Related subjects » Control Engineering - Robotics

Table of contents 

I Rigid manipulators.- 1 Modelling and identification.- 1.1 Kinematic modelling.- 1.1.1 Direct kinematics.- 1.1.2 Inverse kinematics.- 1.1.3 Differential kinematics.- 1.2 Dynamic modelling.- 1.2.1 Lagrange formulation.- 1.2.2 Newton-Euler formulation.- 1.2.3 Model computation.- 1.3 Identification of kinematic parameters.- 1.3.1 Model for identification.- 1.3.2 Kinematic calibration.- 1.3.3 Parameter identifiability.- 1.4 Identification of dynamic parameters.- 1.4.1 Use of dynamic model.- 1.4.2 Use of energy model.- 1.5 Further reading.- References.- 2 Joint space control.- 2.1 Dynamic model properties.- 2.2 Regulation.- 2.2.1 PD control.- 2.2.2 PID control.- 2.2.3 PD control with gravity compensation.- 2.3 Tracking control.- 2.3.1 Inverse dynamics control.- 2.3.2 Lyapunov-based control.- 2.3.3 Passivity-based control.- 2.4 Robust control.- 2.4.1 Constant bounded disturbance: integral action.- 2.4.2 Model parameter uncertainty: robust control.- 2.5 Adaptive control.- 2.5.1 Adaptive gravity compensation.- 2.5.2 Adaptive inverse dynamics control.- 2.5.3 Adaptive passivity-based control.- 2.6 Further reading.- References.- 3 Task space control.- 3.1 Kinematic control.- 3.1.1 Differential kinematics inversion.- 3.1.2 Inverse kinematics algorithms.- 3.1.3 Extension to acceleration resolution.- 3.2 Direct task space control.- 3.2.1 Regulation.- 3.2.2 Tracking control.- 3.3 Further reading.- References.- 4 Motion and force control.- 4.1 Impedance control.- 4.1.1 Task space dynamic model.- 4.1.2 Inverse dynamics control.- 4.1.3 PD control.- 4.2 Parallel control.- 4.2.1 Inverse dynamics control.- 4.2.2 PID control.- 4.3 Hybrid force/motion control.- 4.3.1 Constrained dynamics.- 4.3.2 Inverse dynamics control.- 4.3.3 Hybrid task specification and control.- 4.4 Further reading.- References.- II Flexible manipulators.- 5 Elastic joints.- 5.1 Modelling.- 5.1.1 Dynamic model properties.- 5.1.2 Reduced models.- 5.1.3 Singularly perturbed model.- 5.2 Regulation.- 5.2.1 Single link.- 5.2.2 PD control using only motor variables.- 5.3 Tracking control.- 5.3.1 Static state feedback.- 5.3.2 Two-time scale control.- 5.3.3 Dynamic state feedback.- 5.3.4 Nonlinear regulation.- 5.4 Further reading.- References.- 6 Flexible links.- 6.1 Modelling of a single-link arm.- 6.1.1 Euler-Bernoulli beam equations.- 6.1.2 Constrained and unconstrained modal analysis.- 6.1.3 Finite-dimensional models.- 6.2 Modelling of multilink manipulators.- 6.2.1 Direct kinematics.- 6.2.2 Lagrangian dynamics.- 6.2.3 Dynamic model properties.- 6.3 Regulation.- 6.3.1 Joint PD control.- 6.3.2 Vibration damping control.- 6.4 Joint tracking control.- 6.4.1 Inversion control.- 6.4.2 Two-time scale control.- 6.5 End-effector tracking control.- 6.5.1 Frequency domain inversion.- 6.5.2 Nonlinear regulation.- 6.6 Further reading.- References.- III Mobile robots.- 7 Modelling and structural properties.- 7.1 Robot description.- 7.1.1 Conventional wheels.- 7.1.2 Swedish wheel.- 7.2 Restrictions on robot mobility.- 7.3 Three-wheel robots.- 7.3.1 Type (3,0) robot with Swedish wheels.- 7.3.2 Type (3,0) robot with castor wheels.- 7.3.3 Type (2,0) robot.- 7.3.4 Type (2,1) robot.- 7.3.5 Type (1,1) robot.- 7.3.6 Type (1,2) robot.- 7.4 Posture kinematic model.- 7.4.1 Generic models of wheeled robots.- 7.4.2 Mobility, steerability and manoeuvrability.- 7.4.3 Irreducibility.- 7.4.4 Controllability and stabilizability.- 7.5 Configuration kinematic model.- 7.6 Configuration dynamic model.- 7.6.1 Model derivation.- 7.6.2 Actuator configuration.- 7.7 Posture dynamic model.- 7.8 Further reading.- References.- 8 Feedback linearization.- 8.1 Feedback control problems.- 8.1.1 Posture tracking.- 8.1.2 Point tracking.- 8.1.3 Velocity and torque control.- 8.2 Static state feedback.- 8.2.1 Omnidirectional robots.- 8.2.2 Restricted mobility robots.- 8.3 Dynamic state feedback.- 8.3.1 Dynamic extension algorithm.- 8.3.2 Differential flatness.- 8.3.3 Avoiding singularities.- 8.3.4 Solving the posture tracking problem.- 8.3.5 Avoiding singularities for Type (2,0) robots.- 8.4 Further reading.- References.- 9 Nonlinear feedback control.- 9.1 Unicycle robot.- 9.1.1 Model transformations.- 9.1.2 Linear approximation.- 9.1.3 Smooth state feedback stabilization.- 9.2 Posture tracking.- 9.2.1 Linear feedback control.- 9.2.2 Nonlinear feedback control.- 9.3 Path following.- 9.3.1 Linear feedback control.- 9.3.2 Nonlinear feedback control.- 9.4 Posture stabilization.- 9.4.1 Smooth time-varying control.- 9.4.2 Piecewise continuous control.- 9.4.3 Time-varying piecewise continuous control.- 9.5 Further reading.- References.- A Control background.- A.1 Lyapunov theory.- A. 1.1 Autonomous systems.- A.1.2 Nonautonomous systems.- A.1.3 Practical stability.- A.2 Singular perturbation theory.- A.3 Differential geometry theory.- A.3.1 Normal form.- A.3.2 Feedback linearization.- A.3.3 Stabilization of feedback linearizable systems.- A.4 Input-output.- A.4.1 Function spaces and operators.- A.4.2 Passivity.- A.4.3 Robot manipulators as passive systems.- A.4.4 Kalman-Yakubovich-Popov lemma.- A.5 Further reading.- References.

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