Nonlinear control of co-operating hydraulic manipulators
Bibliographic record
Abstract
This thesis presents the design, analysis, and numerical and experimental evaluation of nonlinear controllers for co-operation among several hydraulic robots operating in the presence of significant system uncertainties, non-linearities and friction. The designed controllers allow hydraulically driven manipulators to (i) co-operatively handle a rigid object (payload) following a given trajectory, (ii) share the payload and (iii) maintain an acceptable internal force on the object. \nA general description of the kinematic and dynamic relations for a hydraulically actuated multi-manipulator system is presented first. The entire mathematical model incorporates object dynamics, robot dynamics, hydraulic actuator functions and friction dynamics. For the purpose of simulations, a detailed numerical simulation program of such a system is also developed, in which two three-link planar robot manipulators resembling the Magnum hydraulic manipulators manufactured by ISE, interact with each other through manipulating a common object. \nThe regulating control problem is studied next, in which the desired position of the object and the corresponding desired link displacement change step-wise. Initially, a controller is designed based on a backstepping technique, assuming that full knowledge of the dynamics and kinematics of the system is available. The assumption is then relaxed and the control system is analyzed. Based on the analysis, the controller is then modified to account for the uncertainty of the payload, robot dynamic parameters and hydraulic functions. \nNext, the regulating controller is extended to a tracking controller, which allows the object to follow a given trajectory and is robust against parameter uncertainties. Additionally, an observer is added to the controller to avoid the need of acceleration feedback. \nTo investigate the effect of friction force, the above controllers are examined by introducing the most recent and complete LuGre friction model into the system dynamics. The tracking controller is then redesigned to compensate the effect of friction. Observers are designed to observe the immeasurable friction states. Based on the observed friction states and estimated friction parameters, an appropriate friction compensation scheme is designed which does not directly use velocity in order to avoid the need of acceleration feedback by the controller. \nFinally, the problem of âexplosion of termsâ coming from the backstepping method is solved by using the concept of dynamic surface control in which a low pass filter is integrated to avoid model differentiation. \nSimulations are carried out for analysis of the control system and verification of the developed controllers. Experimental examinations are performed on an available hydraulic system consisting of two single-axis hydraulic actuators.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".