Abstract
This study investigates the coordinated control problem of Euler–Lagrange systems with model uncertainties in environments containing obstacles when escorting a target. Using an outer–inner loop control structure, a null-space-based behavioral (NSB) control architecture was proposed in the outer loop considering obstacles. This architecture generates the desired velocity for the inner loop. The adaptive proportional derivative sliding mode control (APD-SMC) law was applied to the inner loop to ensure fast convergence and robustness. All the robots were distributed around the target evenly and escorted the target at a specified distance while avoiding obstacles in a p − dimensional space (where p ≥ 2 is a positive integer). Stability and convergence analyses were conducted rigorously using a Lyapunov-based approach. The simulation results of three scenarios verified the effectiveness and high-precision performance of the proposed control algorithm compared to that of the adaptive sliding mode control (ASMC) in both two-dimensional and three-dimensional space. It is shown that all the robots can move into appropriate positions on the surface of a sphere/circle during an escort mission and reconfigure the formation automatically when an obstacle avoidance mission is active.
Highlights
In recent years, the control of multirobot systems has attracted a considerable amount of attention as these systems can overcome the main limitations associated with using a single robot
adaptive proportional derivative sliding mode control (APD-Sliding mode control (SMC)) was employed in the inner loop for multiple Euler–Lagrange systems to compensate for unknown disturbances, parameter uncertainties, etc
The coordinated control of multiple Euler–Lagrange systems for escorting missions was investigated in the presence of model uncertainty, disturbances, and obstacles
Summary
The control of multirobot systems has attracted a considerable amount of attention as these systems can overcome the main limitations associated with using a single robot. Motivated by the requirement for a simple controller that has strong robustness to model uncertainties, external disturbances, parameter uncertainties, and unknown nonlinear dynamics, we proposed a robust hierarchical controller scheme of multiple Euler–Lagrange systems for an escort mission with obstacle avoidance. The PD control part was based only on the tracking errors and tracking velocity errors, and it is model-free and intensive to model uncertainties; the SMC part has strong robustness for the external disturbances and unknown nonlinear dynamics; the adaptive control part was utilized to estimate the unknown system parameters so that the need for large control gains of PD-SMC was avoided Both the position control and the behavioral control method were proven to be stable by Lyapunov theory for nonconflicting tasks, while for conflicting tasks, it was shown that conflicts will not occur.
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