In order to solve the trajectory tracking task in a wheeled mobile robot (WMR), a dynamic three-level controller is presented in this paper. The controller considers the mechanical structure, actuators, and power stage subsystems. Such a controller is designed as follows: At the high level is a dynamic control for the WMR (differential drive type). At the medium level is a PI current control for the actuators (DC motors). Lastly, at the low level is a differential flatness-based control for the power stage (DC/DC Buck power converters). The feasibility, robustness, and performance in closed-loop of the proposed controller are validated on a DDWMR prototype through Matlab-Simulink, the real-time interface ControlDesk, and a DS1104 board. The obtained results are experimentally assessed with a hierarchical tracking controller, recently reported in literature, that was also designed on the basis of the mechanical structure, actuators, and power stage subsystems. Although both controllers are robust when parametric disturbances are taken into account, the dynamic three-level tracking controller presented in this paper is better than the hierarchical tracking controller reported in literature.

This paper presents the design of an adaptive controller that solves the synchronization control problem of two identical Nwachioma chaotic systems in a master-slave configuration. The closed-loop stability is guaranteed by means of a Lyapunov-like analysis. With the aim of verifying the feasibility and performance of the proposed approach, a comparison with an active control algorithm is developed at the numerical simulation level. Based on such results, the master-slave Nwachioma chaotic system in closed-loop with adaptive control is now being experimentally tested by using two personal computers and two low-cost Arduino UNO boards. The experimental results not only show the good performance of the adaptive control but also that Arduino UNO boards are an excellent option for the experimental setup.

The interaction between the anti-apoptotic Bcl-2 protein and its antagonist Bax is essential to the regulation of the mitochondrial pathway of apoptosis. For this work, we built models by homology of Bcl-2 full-sequence length in monomeric form (apo-Bcl-2) and in complex with the BH3 domain of Bax (holo-Bcl-2). The Bcl-2 protein was analyzed with its transmembrane domain anchored to a lipidic bilayer of DPPC, imitating physiological conditions. We performed molecular dynamics (MD) simulations using the GROMACS program. Conformational changes showed that the flexible loop domain (FLD) tends to fold on itself and move towards the main core. Furthermore, the BH3 peptide of pro-apoptotic protein Bax, showed an allosteric stabilizing effect on FLD upon being bound to the hydrophobic cleft of the anti-apoptotic protein Bcl-2, causing a reduction in its structural flexibility. However, FLD is distal from the main core of Bcl-2. Principal component analysis (PCA) showed a weak correlation between FLD residues and BH3 peptide from Bax. Upon MD simulations, several new contacts appeared between FLD and some α-helices of the core of Bcl-2, which contribute to maintaining the stability of Bcl-2. This knowledge sheds light on the behavior of Bcl-2 in the cell's native environment. Communicated by Ramaswamy H. Sarma

This paper presents the design of a control strategy based on exact feedback linearization and dynamic stabilization for the mathematical model of a benchmark Quanser platform emulating the elevation, pitch, and travel motions of a three-degree-of-freedom (3-DOF) tandem helicopter. The orientation dynamics of the aerial vehicle are described by a set of highly coupled, inherently unstable nonlinear differential equations. Unlike conventional feedback linearization approaches, the core contribution of this work lies in a strategic subsystem decoupling technique combined with a symmetric input transformation and a formal proof of exact linearizability. Once the exact linear canonical representation is derived, optimal Linear Quadratic Regulator (LQR) control gains are synthesized directly within the transformed coordinates. Subsequently, a trajectory tracking scheme is developed for each degree of freedom, simulating aggressive trajectory changes that emulate obstacle-avoidance maneuvers during a mission. Numerical simulations in MATLAB/Simulink demonstrate that the proposed control scheme achieves precise tracking and rapid stabilization while strictly adhering to the physical angular bounds of the experimental platform and operational actuator constraints.