Dynamic Decoupling Based Robust Synchronous Control for a Hydraulic Parallel Manipulator

Abstract

In this paper, a novel dynamic decoupling-based robust synchronous control scheme is proposed for the high-precision motion trajectory tracking control of a hydraulic parallel manipulator. The presented controller is derived by effectively integrating joint disturbance rejection technique with a cross-coupling control (CCC) approach. The parallel manipulator is first considered as a multi-axis system with modeling uncertainties and strong nonlinear coupling dynamics. For each axis, two extended state observers are synthesized to estimate and reject both the matched uncertainties and unmatched uncertainties (e.g., external disturbances and unmodeled nonlinearities), and then the decoupled dynamic model of the system in joint space can be established. A synchronization error is developed to represent the coordination degree of multiple actuators and then coupled with the position error to form a coupling position error. Subsequently, based on the system decoupled dynamic model, a synchronous controller with the feedback of coupling position error is carried out to coordinate the motions of actuators by combining the CCC strategy with robust control via backstepping method. The proposed controller can theoretically guarantee the simultaneous convergence of both position tracking errors and synchronization errors. The stability of the system is verified via the Lyapunov method. The comparative experiment results are obtained to verify the high tracking performance nature of the proposed control strategy. INDEX TERMS Hydraulic parallel manipulator, extended state observer, decoupled dynamic model, cross-coupling approach, robust synchronous control.

Software/Hardware-Based Hierarchical Finite-Time Sliding-Mode Control With Input Saturation for an Omnidirectional Autonomous Mobile Robot

“…It is also known that sliding-mode (adaptive) control can satisfactorily deal with a class of the trajectory tracking for nonlinear dynamic and complex systems (e.g., air management of PEM fuel cell systems [30], NPC converters [31], event-triggering dissipative control [32], an interior permanent magnet synchronous motor drive [33], doublependulum overhead cranes [34], a hydraulic parallel manipulator [35]). However, to reach the task assignment in a specific time interval becomes a challenge.…”

Stabilization of Robots With a Regulator Containing the Sigmoid Mapping

“…Authors analyze proportional derivative sliding model regulators of overhead cranes and inverted pendulums in [24]- [26], and [27]. In [28]- [30], and [31], authors addressed robust sliding model regulators of parallel manipulators and quadrotors. Authors discussed regulators for stabilization of multiple converters in [32], [33], and [34].…”

“…The aforementioned research is divided in two big groups where [16]- [19], [21], [22], [24]- [26], [29], [32]- [34] are focused on the stabilization of nonlinear models subject to nonlinear uncertainties, and [9]- [15], [20], [23], [27], [28], [30], [31] are focused on the stabilization of nonlinear models subject to external perturbations. It is important to note that in most of the cases the nonlinear uncertainties or external perturbations are unknown.…”

“…There are other two issues in a regulator that could limit its performance: a) when boundedness of the regulator law terms is not ensured, and b) when chattering of the signum mapping is increased. The mentioned issues are solved in our regulator as following: a) taking into account that the sigmoid mapping is used in a neural network to ensure its boundedness [16]- [19], we use the sigmoid mapping to ensure boundedness of the regulator law terms, b) taking into account that the saturation mapping is used to reduce its chattering without ensuring its stabilization [28]- [31], we reduce the chattering by the usage of the saturation mapping while we ensure the stabilization.…”

Active Disturbance Rejection Position Synchronous Control of Dual-Hydraulic Actuators with Unknown Dead-Zones

“…Furthermore, modern control theories have provided many efficient control methods, such as robust control (RC), sliding mode control (SMC), and adaptive control (AC). A novel dynamic decoupling-based robust synchronous control scheme is proposed to solve the high-precision motion trajectory tracking control of a parallel hydraulic manipulator with the matching uncertainties and unmatched uncertainties [14]. The control strategy, including a global sliding mode control method and the cross-coupling technology, was introduced to achieve high-precision motion for a multi-axis servo system [15].…”