The purpose of controlling the vehicle handling is to ensure that the vehicle is in a safe condition and following its desire path. Vehicle yaw rate is controlled in order to achieve a good vehicle handling. In this paper, the optimal Composite Nonlinear Feedback (CNF) control technique is proposed for an Active Front Steering (AFS) system for improving the vehicle yaw rate response. The model used in order to validate the performance of controller is nonlinear vehicle model with 7 degree-of-freedom (DOF) and a bicycle model is implemented for the purpose of designing the controller. In designing an optimal CNF controller, the parameter estimation of linear and nonlinear gain becomes very important to produce the best output response. An intelligent algorithm is designed to minimize the time consumed to get the best parameter. To design an optimal method, Multi Objective Particle Swarm Optimization (MOPSO) is utilized to optimize the CNF controller performance. As a result, transient performance of the yaw rate has improved with the increased speed of in tracking and searching of the best optimized parameter estimation for the linear and the nonlinear gain of CNF controller. � 2015 Penerbit UTM Press. All rights reserved.

This paper presents a new control scheme based on model reference command shaping (MRCS) for an overhead crane, with double-pendulum mechanism effects. The approach has an advantage in achieving an accurate trolley positioning, with low hook and payload oscillations, under various desired trolley positions and parameter uncertainties, without the requirement for measurement or estimation of system parameters. These are challenging in practice. The previously developed MRCS algorithm is improved in order to reduce its design complexity, as well as to ensure that it can be augmented with a feedback controller so that a concurrent controller tuning can be realised. The combined MRCS and feedback controller is used to achieve both, precise trolley positioning, and low hook and payload oscillations. To evaluate the effectiveness and the robustness of the approach, simulations and experiments using a nonlinear model and a laboratory double-pendulum crane are carried out. Under various desired positions and parameter uncertainties that involve varying the cable lengths (payload hoisting) and the payload mass variations, the superiority of the proposed approach is confirmed by achieving higher hook and payload oscillation reductions when compared with a recently proposed feedback controller. In addition, the desired trolley positions are achieved with smoother responses. � 2020 Elsevier Ltd

Background: Hepatocellular carcinoma (HCC) is a common cancer that is frequently diagnosed at an advanced stage. Transarterial chemoembolisation (TACE) is an effective palliative treatment for patients who are not eligible for curative treatment. The two main methods for performing TACE are conventional (c-TACE) or with drug eluting beads (DEB-TACE). We sought to compare survival rates and tumour response between patients undergoing c-TACE and DEB-TACE at our centre. Materials and Methods: A retrospective cohort study of patients undergoing either treatment was carried out from January 2009 to December 2014. Tumour response to the procedures was evaluated according to the modified Response Evaluation Criteria in Solid Tumors (mRECIST). Kaplan-Meier analysis was used to assess and compare the overall survival in the two groups. Results: A total of 79 patients were analysed (34 had c-TACE, 45 had DEB-TACE) with a median follow-up of 11.8 months. A total of 20 patients in the c-TACE group (80%) and 12 patients in the DEB-TACE group (44%) died during the follow up period. The median survival durations in the c-TACE and DEB-TACE groups were 4.9 � 3.2 months and 8.3 � 2.0 months respectively (p=0.008). There was no statistically significant difference noted among the two groups with respect to mRECIST criteria. Conclusions: DEB-TACE demonstrated a significant improvement in overall survival rates for patients with unresectable HCC when compared to c-TACE. It is a safe and promising approach and should potentially be considered as a standard of care in the management of unresectable HCC.

This paper proposes an input shaping technique for efficient payload swing control of a tower crane with cable length variations. Artificial neural network is utilized to design a zero vibration derivative shaper that can be updated according to different cable lengths as the natural frequency and damping ratio of the system changes. Unlike the conventional input shapers that are designed based on a fixed frequency, the proposed technique can predict and update the optimal shaper parameters according to the new cable length and natural frequency. Performance of the proposed technique is evaluated by conducting experiments on a laboratory tower crane with cable length variations and under simultaneous tangential and radial crane motions. The shaper is shown to be robust and provides low payload oscillation with up to 40% variations in the natural frequency. With a 40% decrease in the natural frequency, the superiority of the artificial neural network–zero vibration derivative shaper is confirmed by achieving at least a 50% reduction in the overall and residual payload oscillations when compared to the robust zero vibration derivative and extra insensitive shapers designed based on the average operating frequency. It is envisaged that the proposed shaper can be further utilized for control of tower cranes with more parameter uncertainties.