This paper proposes a novel adaptive feedback sliding mode control for parallel kinematic manipulators (PKMs), built on the conventional model-based sliding mode control. This structure was chosen for its robustness towards uncertainties and external disturbances. The contribution of this research is the inclusion of a feedforward term based on the dynamic model of the PKM in the control design. This feedforward term compensates for high nonlinear dynamics, as well as avoids measurement noise in control inputs. Additionally, the fixed feedback gains of the sliding mode controller are redesigned as adaptive gains, which provide better correction actions for larger tracking errors. A stability analysis of the proposed control solution, based on Lyapunov’s method, is provided. The effectiveness of the proposed controller is demonstrated through its application to a Gough-Stewart platform (MISTRAL parallel robot) in various real-time experimental scenarios. The proposed approach is compared with various controllers demonstrating its superiority. It ensures nominal root mean square tracking errors of (i) about$22\,\mu m$in joint space, and (ii) about$27\,\mu m$in traveling plate Cartesian position. Note to Practitioners—This paper was motivated by the problem of robustness towards uncertainties and operating conditions for PKMs and especially in industry. The literature contains some control solutions to deal with these issues by designing robust or adaptive nonlinear controllers. Indeed, despite their success, for the first type, large uncertainties may degrade the tracking performance and the robustness is not always guaranteed. Adaptive controllers can be more robust, but their tuning can be difficult and especially in the case of real-time estimation of dynamic parameters. In this paper, a new robust-based sliding mode control with adaptive feedback gains is proposed to ensure the robustness towards uncertainties and external disturbances. The idea is to design adaptive feedback gains for a model-based sliding mode control, resulting in an improved robustness, while ensuring an easy tuning of its parameters. The proposed solution is validated through real-time experiments on an industrial parallel robot, and compared with some model-based controllers. The obtained results show clearly the benefits of the proposed control design and its effectiveness and robustness. In future work, the proposed controller can be endowed with a real-time estimation of the dynamic parameters, as well as, a redesign based on the super-twisting algorithm.

Redundancy resolution of redundantly actuated cable-driven parallel robots (CDPRs) requires the computation of feasible and continuous cable tension distributions along a trajectory. This paper focuses on n-DOF CDPRs driven by n + 2 cables, since, for n = 6, these redundantly actuated CDPRs are relevant in many applications. The set of feasible cable tensions of n-DOF (n + 2)-cable CDPRs is a 2-D convex polygon. An algorithm that determines the vertices of this polygon in a clockwise or counterclockwise order is first introduced. This algorithm is efficient and can deal with infeasibility. It is then pointed out that straightforward modifications of this algorithm allow the determination of various (optimal) cable tension distributions. A self-contained and versatile tension distribution algorithm is thereby obtained. Moreover, the worst-case maximum number of iterations of this algorithm is established. Based on this result, its computational cost is analyzed in detail, showing that the algorithm is efficient and real-time compatible even in the worst case. Finally, experiments on two six-degree-of-freedom eight-cable CDPR prototypes are reported.

This paper deals with the control of a 6-DOF cable-suspended parallel robot (CSPR) able to perform tasks such as pick-and-place trajectories over a large workspace. In order to maximize the ratio between the robot workspace and its overall dimensions, actuation redundancy can be used. The control of such a redundantly actuated CSPR turns to be challenging as a realtime embeddable algorithm for distributing the cable tensions should be used, together with a suitable control scheme. This paper proposes a computationally efficient tension distribution algorithm implemented within a dual-space feedforward scheme in order to properly control the moving platform. Experimentations are performed on a large 6-DOF CSPR prototype equipped with 8 actuators.

Cable-driven parallel robots (CDPR) are efficient manipulators able to carry heavy payloads across large workspaces. Therefore, the dynamic parameters such as the mobile platform mass and center of mass location may considerably vary. Without any adaption, the erroneous parametric estimate results in mismatch terms added to the closed-loop system, which may decrease the robot performances. In this paper, we introduce an adaptive dual-space motion control scheme for CDPR. The proposed method aims at increasing the robot tracking performances, while keeping all the cable tensed despite uncertainties and changes in the robot dynamic parameters. Reel-time experimental tests, performed on a large redundantly actuated CDPR prototype, validate the efficiency of the proposed control scheme. These results are compared to those obtained with a non-adaptive dual-space feedforward control scheme.

As a part of an ongoing project, in this paper we introduce the first version of a system which has a novel methodology for Cine (as in cinema) MRI based control of a cardiac robot for beating heart surgeries. The system uses the preoperative planning approach that we developed earlier, and integrates it to the intraoperative algorithms for controlling a robot and tracking some specific landmarks of a highly dynamical surgical field. In particular, our late studies presented herein aim to demonstrate the feasibility of integrating appropriate computational tools to achieve the volumetric image guidance for minimally invasive surgeries in the beating heart. We conceive of the system as practicable for in vitro experiments upon the completion of the first physical prototype, which may pave the way for expansion of the approach for other complex surgeries as well.