Information and Control ICIC International c ⃝2011 ISSN

Abstract. This paper suggests a real-time implementation method for software-in-theloop (SIL) simulation for control systems, primarily for control education. The SIL simulation is carried out by using a PC for the controllers, a PC for the plant, an open network, and a general-purpose computer-aided control system design (CACSD) package. Specially, Ethernet network is investigated in terms of control issues such as sampling interval, network-induced time-delay, use with many I/O points and data synchronization. A performance evaluation of software-in-th

Diclofenac impairs autophagic flux via oxidative stress and lysosomal dysfunction: Implications for hepatotoxicity

Treatment with nonsteroidal anti-inflammatory drugs (NSAIDs) is associated with various side effects, including cardiovascular and hepatic disorders. Studies suggest that mitochondrial damage and oxidative stress are important mediators of toxicity, yet the underlying mechanisms are poorly understood. In this study, we identified that some NSAIDs, including diclofenac, inhibit autophagic flux in hepatocytes. Further detailed studies demonstrated that diclofenac induced a reactive oxygen species (ROS)-dependent increase in lysosomal pH, attenuated cathepsin activity and blocked autophagosome-lysosome fusion. The reactivation of lysosomal function by treatment with clioquinol or transfection with the transcription factor EB restored lysosomal pH and thus autophagic flux. The production of mitochondrial ROS is critical for this process since scavenging ROS reversed lysosomal dysfunction and activated autophagic flux. The compromised lysosomal activity induced by diclofenac also inhibited the fusion with and degradation of mitochondria by mitophagy. Diclofenac-induced cell death and hepatotoxicity were effectively protected by rapamycin. Thus, we demonstrated that diclofenac induces the intracellular ROS production and lysosomal dysfunction that lead to the suppression of autophagy. Impaired autophagy fails to maintain mitochondrial integrity and aggravates the cellular ROS burden, which leads to diclofenac-induced hepatotoxicity.Y

Position Control of Brushless DC Motor using Adaptive Sliding mode Control with Time-delay Control

1

Improved Robustness of Reinforcement Learning Based on Uncertainty and Disturbance Estimator

This paper proposes a method to improve the robustness of RLs based on model-free uncertainty and disturbance estimator (RL-based UDE). In the real environment, instead of using optimal trajectory and control techniques to perform complex tasks, it learns through RL and supplements robustness by using uncertainty and disturbance estimator (UDE). From UDE, the robotics system can be improved the stability by appropriately canceling the uncertainty and disturbance without efforts to obtain model information; hence the UDE can compensate for the performance degradation of RL when system is non-stationary. In addition, the performance can be improved by reducing the sensor noise from low-pass filter of UDE. It is shown through an experiment that the proposed RL-based UDE provides robustness.1

A Reinforcement Learning-based Adaptive Time-Delay Control and Its Application to Robot Manipulators

This study proposes an innovative reinforcement learning-based time-delay control (RL-TDC) scheme to provide more intelligent, timely, and aggressive control efforts than the existing simple-structured adaptive time-delay controls (ATDCs) that are well-known for achieving good tracking performances in practical applications. The proposed control scheme adopts a state-of-the-art RL algorithm called soft actor critic (SAC) with which the inertia gain matrix of the timedelay control is adjusted toward maximizing the expected return obtained from tracking errors over all the future time periods. By learning the dynamics of the robot manipulator with a data-driven approach, and capturing its intractable and complicated phenomena, the proposed RL-TDC is trained to effectively suppress the inherent time delay estimation (TDE) errors arising from time delay control, thereby ensuring the best tracking performance within the given control capacity limits. As expected, it is demonstrated through simulation with a robot manipulator that the proposed RL-TDC avoids conservative small control actions when large ones are required, for maximizing the tracking performance. It is observed that the stability condition is fully exploited to provide more effective control actions.1

Efficient Path Generation and Tracking Control for Autonomous Vehicles

1

Adaptive Model-Free Control With Nonsingular Terminal Sliding-Mode for Application to Robot Manipulators

An adaptive model-free control with nonsingular terminal sliding-mode (AMC-NTSM) is proposed for high precision motion control of robot manipulators. The proposed AMC-NTSM employs one-sample delayed measurements to cancel nonlinearities and uncertainties of manipulators and to subsequently obtain sufficiently simple models for easy control design. In order to maintain high gain controls even when the joint angles are close to the reference target values and accordingly achieve high precision and fast response control, a nonlinear sliding variable is also adopted instead of a linear one, asymptotically stabilizing controls by guaranteeing even a finite-time convergence. In addition, sliding variables are reflected on control inputs to support fast convergence while achieving uniform ultimate boundedness of tracking errors. The control gains of the proposed AMC-NTSM are adaptively adjusted over time according to the magnitude of the sliding variable. Such adaptive control gains become high for fast convergence or low for settling down to steady motion with better convergence precision, when necessary. The switching gains of the proposed AMC-NTSM are also adaptive to acceleration such that inherent time delay estimation (TDE) errors can be suppressed effectively regardless of their magnitudes. The simulation and experiment show that the proposed AMC-NTSM has good tracking performance.11Ysciescopu

Diclofenac: A Nonsteroidal Anti-Inflammatory Drug Inducing Cancer Cell Death by Inhibiting Microtubule Polymerization and Autophagy Flux

Diclofenac, a nonsteroidal anti-inflammatory drug (NSAID) used to treat inflammatory diseases induces cellular toxicity by increasing the production of reactive oxygen species (ROS) and impairing autophagic flux. In this study, we investigated whether diclofenac induces cancer cell death and the mechanism by which diclofenac causes cell death. We observed that diclofenac induces mitotic arrest with a half-maximal effective concentration of 170 μM and cell death with a half-maximal lethal dose of 200 µM during 18-h incubation in HeLa cells. Cellular microtubule imaging and in vitro tubulin polymerization assays demonstrated that treatment with diclofenac elicits microtubule destabilization. Autophagy relies on microtubule-mediated transport and the fusion of autophagic vesicles. We observed that diclofenac inhibits both phagophore movement, an early step of autophagy, and the fusion of autophagosomes and lysosomes, a late step of autophagy. Diclofenac also induces the fragmentation of mitochondria and the Golgi during cell death. We found that diclofenac induces cell death further in combination with 5-fuorouracil, a DNA replication inhibitor than in single treatment in cancer cells. Pancreatic cancer cells, which have high basal autophagy, are particularly sensitive to cell death by diclofenac. Our study suggests that microtubule destabilization by diclofenac induces cancer cell death via compromised spindle assembly checkpoints and increased ROS through impaired autophagy flux. Diclofenac may be a candidate therapeutic drug in certain type of cancers by inhibiting microtubule-mediated cellular events in combination with clinically utilized nucleoside metabolic inhibitors, including 5-fluorouracil, to block cancer cell proliferation