This paper investigates the implementation of feedback linearization for the control of a planar two-link robotic manipulator, with the objective of achieving precise and robust trajectory tracking. The nonlinear dynamic model of the manipulator is systematically derived using the Euler-Lagrange formalism, capturing the full complexity of its coupled dynamics. Based on this model, a nonlinear control law is designed to cancel the system’s intrinsic nonlinearities and impose a desired linear behavior.The proposed controller guarantees rapid convergence of tracking errors, stability of the closed-loop system, and robustness against modeling inaccuracies and dynamic interactions between the links. Through numerical simulations, the effectiveness of the approach is demonstrated, showing high tracking fidelity even in the presence of parameter uncertainties and external disturbances.

This paper presents the design of a Terminal Sliding Mode Controller (TSMC) for trajectory tracking of an upper limb rehabilitation exoskeleton. Addressing dynamic uncertainties and disturbances inherent in human-robot interaction, the TSMC ensures finite-time convergence of tracking errors, providing fast, precise, and robust performance. The nonlinear dynamic model of the exoskeleton is derived using the Euler-Lagrange formulation, focusing on planar shoulder and elbow motions. Simulation results demonstrate the effectiveness of the proposed controller in significantly reducing tracking errors in joint angles and velocities, while effectively mitigating the chattering phenomenon. This work lays the foundation for robust control solutions tailored to the demanding requirements of functional robotic rehabilitation.

The present paper gives an optimal tuning procedure for design of Proportional Integral Derivative (PID) controllers for an incremental linear actuator. Estimation of the optimal PID controller parameters: kp, kiand kdis carried out by minimizing performance criteria following ISE, IAE, ITAE and ITSE for a setpoint tracking problem. Results of the simulations for dynamic position response reveals using the ISE fitness function to search the parameters of the PID controller by genetic algorithm provides enhanced performance for the set-point tracking and of the temporal performance in terms of response time and rise time.

In this paper, the Dahlin Deadbeat Internal Model Control strategy is applied to control the discrete systems with time delay. This time delays in the system can result in instability, poor performance, and even system failure. We apply DDIMC on a neonatal incubator system to control temperature and humidity. We obtained good results in terms of stability, setpoint tracking and in terms of the rapidity of the system's responses.