An innovative cascade control strategy is presented in this work, based on sliding mode control (SMC) for trajectory tracking of the formation of mobile robots. The proposed strategy was compared with five alternative control approaches: PID control, inverse dynamics, and other SMC-based structures. The objective was to evaluate the most effective control technique by analyzing the integral of squared error (ISE) index. Additionally, robustness tests were carried out by varying the parameters of the dynamic model of the mobile robot and analyzing the response of the controllers to perturbations in the modeling. The results show that the PD-SMCV controller provides the best performance in trajectory tracking and robustness against disturbances, demonstrating significant superiority over the evaluated methods for maintaining a stable mobile robot formation under dynamic conditions.

The proposed work presents a Sliding Mode Controller (SMC) for trajectory tracking of a TurtleBot3 Burger mobile robot based on sliding mode. Trajectory tracking is performed in congested environments; therefore, an obstacle avoidance strategy is presented to prevent the robot from colliding with obstacles. A clear and detailed methodology is developed for the design of the SMC controller with a PID sliding surface for trajectory tracking that can be extrapolated to position control and posture control. The discontinuous part of the SMC is used to ensure that the robot tends to the desired reference whenever an obstacle appears. The stability analysis of the proposed controller is presented, and the experimental results are shown, demonstrating the good performance of the controller.

This paper presents an experimental comparison between model-based and model-free trajectory-tracking control strategies applied to an omnidirectional mobile robot platform. Classical model-based controllers, including Proportional-Integral-Derivative (PID), Generic Model Control (GMC), and Sliding Mode Control (SMC), are evaluated against a Model-Free Control (MFC) strategy based on an intelligent Proportional–Integral–Derivative (iPID) regulator. An empirical integrator-with-delay model is identified from experimental data and used to design model-based controllers. All strategies were implemented on the Festo Robotino platform under comparable operating conditions and evaluated using circular, lemniscate, and square trajectories. Controller performance is assessed using the Integral of Squared Error (ISE), the settling time ($T_s$), and the control effort quantified by the Integral of Squared Control Output (ISCO). Experimental results show that the model-free controller provides the best overall tracking performance, achieving tracking error reductions of approximately $25\%$ to $90\%$ compared with the evaluated model-based controllers, while maintaining a competitive control effort. The study provides a unified experimental benchmark comparing model-based and model-free control paradigms on the Robotino platform, highlighting the practical advantages of model-free control for robotic systems affected by uncertainties and nonlinearities.

This article proposes a distributed formation control strategy for mobile robots (using TurtleBot3 Burger platforms) based on teleoperation using artificial forces and mechanical impedance modeling. The proposed control law is structured in cascade, consisting of an external loop responsible for maintaining the formation and an internal loop dedicated to obstacle avoidance. Bilateral teleoperation is enabled by integrating the Novint Falcon haptic device, which allows the human operator to issue velocity commands to the formation and receive force feedback based on the robots’ physical interactions with congested environments. This strategy improves remote perception of the environment and promotes safe and collaborative navigation, validated through experiments in real-world environments.

This paper proposes a novel dual-layer learning-based cascade architecture, termed LAMDA-LAMDA, for cooperative formation control of aerial manipulators. The strategy integrates two hierarchical LAMDA controllers: an inner loop that performs velocity-level dynamic compensation and disturbance attenuation, and an outer loop that regulates formation shape and centroid tracking. Unlike conventional model-dependent approaches, the proposed control law does not require explicit knowledge of the aerial manipulator dynamics, which are characterized by strong nonlinear coupling between the hexacopter platform and the onboard manipulator. A Lyapunov-based stability analysis guarantees asymptotic convergence of both velocity and formation errors under bounded uncertainties. The controller is benchmarked against four reference schemes: Kinematic-SMC, SMC with Inverse Dynamics (SMC-ID), SMC-SMC cascade, SMC-LAMDA, and LAMDA-LAMDA cascade, considering abrupt reference changes and severe parametric disturbances affecting inertia, Coriolis, and gravitational terms. Quantitative results show that LAMDA-LAMDA achieves the lowest tracking errors, with average ISE = 0.702 and IAE = 1.652, corresponding to improvements of 35.3% and 32.1% over the best model-based alternative. Additionally, the proposed scheme generates smooth control actions while preserving robustness, highlighting its suitability for cooperative aerial manipulation under dynamic uncertainty.

In this paper, four control strategies are developed and evaluated for the trajectory-tracking of a two-degree-of-freedom SCARA-type robotic manipulator: (i) a proportional-derivative controller (PD), (ii) a proportional-derivative controller with friction compensation (PD + G), (iii) an inverse-dynamics controller and (iv) a sliding-mode controller with a dynamic model (SMCD). These controllers are implemented in a dynamic model of a manipulator robot, and their performance is assessed based on trajectory-tracking accuracy and robustness against disturbances. Robustness tests are conducted by varying the parameters of the dynamic model of the robot. The performance of each controller is analyzed using the Integral Squared Error (ISE) and the Integral of Time-weighted Squared Error (ITSE) indexes to compare their effectiveness. This study offers a comprehensive evaluation of each control strategy, demonstrating that the SMCD achieves the optimal balance between accuracy and disturbance robustness.