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The purpose of this thesis is to present a comprehensive and practical approach for the time-optimal motion planning and control of a general purpose industrial manipulator. In particular, the case of point-to-point path unconstrained motions is considered, with special emphasis towards strategies suitable for efficient on-line implementations. From a dynamic model description of the plant, and using an advanced graphical robotics simulation environment, the control algorithms are formulated. Experimental work is then conducted to verify the proposed algorithms, by interfacing the industrial manipulator to the master controller, implemented on a personal computer. The full rigid-body non-linear dynamics of the open-chain manipulator have been accommodated into the modelling, analysis and design of the control algorithms. For path unconstrained motions, this leads to a model-based regulating strategy between set points, which combines conventional trajectory planning and subsequent control tracking stages into one. Theoretical insights into these two robot motion disciplines are presented, and some are experimentally demonstrated on a CRS A251 industrial arm. A critical evaluation of current approaches which yield optimal trajectory planning and control of robot manipulators is undertaken, leading to the design of a control solution which is shown to be a combination of Pontryagin's Maximum Principle and state-space methods of design. However, in a real world setting, consideration of the relationship between optimal control and on-line viability highlights the need to approximate manipulator dynamics by a piecewise linear and decoupled function, hence rendering a near-time-optimal solution in feedback form. The on-line implementation of the proposed controller is presented together with a comparison between simulation and experimental results. Furthermore, these are compared with measurements from the industrial controller. It is shown that the model-based near-optimal-time feedback control algorithms allow faster manipulator motions, with an average speed-up of 14%, clearly outperforming current industrial controller practices in terms of increased productivity. This result was obtained by setting an acceptable absolute error limit on the target location of the joint (position and velocity) to within [2.0E-02 rad, 8.7E-03 rad/s], when the joint was regarded at rest.

Methods for resolving kinematic redundancies of manipulators by the effect on joint torque are examined. When the generalized inverse is formulated in terms of accelerations and incorporated into the dynamics, the effect of redundancy resolution on joint torque can be directly reflected. One method chooses the joint acceleration null-space vector to minimize joint torque in a least squares sense; when the least squares is weighted by allowable torque range, the joint torques tend to be kept within their limits. Contrasting methods employing only the pseudoinverse with and without weighting by the inertia matrix are presented. The results show an unexpected stability problem during long trajectories for the null-space methods and for the inertia-weighted pseudoinverse method, but rarely for the unweighted pseudoinverse method. Evidently a whiplash action develops over time that thrusts the endpoint off the intended path, and extremely high torques are required to overcome these natural movement dynamics.

Robot arms require actuators that are powerful, precise and safe. The safety concern is amplified when these robots work closely with people in collaborative applications. This thesis investigates the design and implementation of hybrid pneumatic-electric actuators (HPEA) for use in robot arms, particularly those intended for collaborative applications. The initial focus was on improving the control of an existing single HPEA-driven rotary joint. The torque is produced by four pneumatic cylinders connected in parallel with a small DC motor. The DC motor is directly connected to the output shaft. A cascaded control system is designed that consists of an outer position control loop and an inner pressure control loop. The pressure controller is based on a novel inverse valve model. High precision position tracking control is achieved due to the combination of the model-based pressure controller, model-based position controller, adaptive friction compensator and offline payload estimator. Experiments are performed with the actuator prototype rotating a link and payload with a rotational inertia equivalent to a linear actuator moving a 573 kg mass. Averaged over five tests, a root-mean-square error of 0.024° and a steady-state error (SSE) of 0.0045° are achieved for a fast multi-cycloidal trajectory. This SSE is almost ten times smaller than the best value reported for previous HPEAs. An offline payload estimation algorithm is used to improve the control system’s robustness. The superior safety of the HPEA is shown by modeling and simulating a constrained robot-head impact, and comparing the result with equivalent electric and pneumatic actuators. This research produced two journal papers. Since HPEAs are redundant actuators that combine the large force, low bandwidth characteristics of pneumatic actuators with the large bandwidth, small force characteristics of electric actuators, the effect of using optimization-based input allocation for HPEAs was studied. The goal was to improve the HPEA’s performance by distributing the required input (force or torque) between the redundant actuators in accordance with each actuator’s advantages and limitations. Three novel model-predictive control (MPC) approaches are designed to solve the position tracking and input allocation problems using convex optimization. The approaches are simulated on a HPEA-driven system and compared to a conventional linear controller without active input allocation. The first MPC approach uses a model that includes the dynamics of the payload and pneumatics; and performs the motion control using a single loop. The latter methods simplify the MPC law by separating the position and pressure controllers. Although the linear controller is the most computationally efficient, it is inferior to the MPC-based controllers in position tracking and force allocation performance. The third MPC-based controller design demonstrated the best position tracking with root mean square errors of 46%, 20%, and 55% smaller than the other three approaches. It also demonstrated sufficient speed for real-time operation. This research produced one journal paper. The research continued with the design and implementation of a two degree-of-freedom HPEA-driven arm. A HPEA-driven “elbow” joint is designed and added to the existing “shoulder” joint. The force from a single pneumatic cylinder is converted into torque using a 4-bar linkage. To eliminate backlash and keep the weight of the arm low, a 2nd smaller DC motor is directly connected to the joint. The kinematic and kinetic models of the new arm, as well as the geometry of the new elbow joint are studied. The resulting joint design is implemented, tested and controlled. This joint could achieve a SSE of 0.0045° in spite of its nonlinear joint geometry. The arm is experimentally tested for simultaneous tracking control of the two joints, and for end-effector position tracking in Cartesian space. The end-effector is able to follow a circular trajectory in pneumatic mode with position errors below 0.005 m. / Thesis / Doctor of Philosophy (PhD) / Robots that work with, or near, humans require greater safety considerations than other robots. A significant concern is collisions between the robot and humans that may happen when sensors or software fails. An actuator for robots that combines the inherent safety of pneumatic actuators with the accuracy of electric actuators, termed a “hybrid pneumatic electric actuator” (HPEA), is investigated. The design, instrumentation, modelling, and control of HPEAs are studied theoretically and experimentally. The proposed actuator could achieve high position control accuracy in a variety of experiments, with steady state error of less than 0.0045 degrees. Simulated impacts with a human head also showed that a HPEA-driven robot arm can achieve a 52% lower impact force, compared to an arm driven by conventional electric actuators. The HPEA design and control experiments are performed on a single HPEA-driven joint and extended to an arm consisting of two HPEA-driven revolute joints.

Le travail présenté dans cette thèse concerne la modélisation et la commande robuste en force de robots manipulateurs industriels à articulations flexibles utilisés pour le procédé FSW. Afin de réduire les temps de calcul et l'occupation de la mémoire, une approche basée sur la méthode par intervalle est proposée en vue de la simplification des modèles dynamiques des robots industriels, et contribue à identifier les paramètres d'inertie qui sont négligeables. Des études de cas sur trois types de trajectoires de test et l’analyse des couples moteurs ont démontré l'efficacité et les bonnes performances de la méthode de simplification. Ensuite, la modélisation dynamique et l'identification des paramètres du procédé FSW ont été effectuées. Les paramètres des modèles linéaires et non-linéaires de forces axiales sont identifiés. Sur la base de la modélisation du procédé FSW qui considère simultanément la cinématique du système complet, le modèle de déplacement du robot rigide, les flexibilités des articulations et le modèle dynamique de la force axiale, un contrôleur robuste en force est obtenu par la méthode de réglage fréquentielle. En outre, un simulateur du procédé FSW robotique est développé et les résultats de simulation montrent les bonnes performances du contrôleur en force. L'oscillation de la force axiale dans le procédé FSW peut être simulée en utilisant un modèle de perturbation de la position verticale de référence. / The work presented in this thesis focuses on the modeling and robust force control of flexible joints industrial robot manipulators used for FSW process. In order to reduce computation time and memory occupation, a novel interval-based approach for dynamic model simplification of industrial robots is proposed, which applies to arbitrary trajectories of whole robot workspace and contributes to obtaining negligible inertia parameters. Cases studies have been carried out on three kinds of test trajectories and torques analysis of robot dynamic equation, demonstrating the effectiveness and good performance of the simplification method. Then, the dynamic modeling and identification of robotic FSW process is performed, and the parameters of linear and nonlinear dynamic axial force process models are identified by using the plunge depth and its derivative. On the basis of the modeling of robotic FSW process which simultaneously considers the complete kinematics, the rigid robot displacement model, the joint flexibility and the dynamic axial force process model, a robust force controller can be obtained by using the frequency response approach. Besides, a simulator of robotic FSW process is developed and simulation results show good performance of the force controller. The oscillation of axial force in FSW process can be simulated when a disturbance model of initial vertical reference position is proposed and used in the simulation.