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Psychiatric disorders are now widely recognized as a major contributor to the global burden of disease. It has been described that there is an increased risk of adverse effects when more than one psychotropic drug is prescribed. Knowledge of the pattern of utilization of drugs in the general population can be achieved through the conduct of drug utilization studies. The present study has therefore been conducted to observe the pattern of drug use in psychiatry patients in a tertiary care hospital. Aim and Objective: To assess the epidemiology of various psychiatric illnesses among the study population To assess the Prescribing Pattern of drugs in Psychiatric Illness. To assess the drug-drug interactions in the prescription using MICROMEDEX. Methodology: A retrospective descriptive observational study was performed in a tertiary care hospital. A total of 100 prescriptions were collected from MRD. Results: The study reported that 66% of patients were males and 34% were females. The average number of drugs and psychotropic drugs per prescription is six and four respectively. Around 61.98% of drugs in the prescription are psychotropic drugs, among that 40.17% of benzodiazepines are majorly used, followed by 34.27% of antipsychotics. Almost 95 prescriptions had a minimum of one drug-drug interaction. The average number of psychotropics per prescription was higher than in studies. The average number of drugs per prescription was 5.84, which lead to polypharmacy. Conclusion: Using WHO indicators prescription analysis was done and it showed some deviation from the standard value which can be improved. Polypharmacy was noted in this study. Most of the drug is prescribed in the brand name which should be avoided.

We design a reduced attitude controller for reorienting the spin axis of a gyroscope in a geometric control framework. The proposed controller preserves the inherent gyroscopic stability associated with a spinning axis-symmetric rigid body. The equations of motion are derived in two frames: a non-spinning frame to show the gyroscopic stability, and a body-fixed spinning frame for deriving the controller. The proposed controller is designed such that it retains the gyroscopic stability structure in the closed loop and renders the desired equilibrium almost-globally asymptotically stable. Due to the time-critical nature of the control input, in particular its sensitivity with respect to delays/neglected dynamics, the controller is extended to incorporate the effect of actuator dynamics for practical implementation. Thereafter, a comparison in performance is shown between the proposed controller and a conventional reduced attitude geometric controller with numerical simulation. The controller is validated experimentally on a spinning tricopter.

This paper provides a real time on-board algorithm for a biplane-quadrotor to iteratively learn a forward transition maneuver via repeated flight trials. The maneuver is controlled by regulating the pitch angle and propeller thrust according to feedforward control laws that are parameterized by polynomials. Based on a nominal model with simplified aerodynamics, the optimal coefficients of the polynomials are chosen through simulation such that the maneuver is completed with specified terminal conditions on altitude and air speed. In order to compensate for modeling errors, repeated flight trials are performed by updating the feedforward control paramters according to an iterative learning algorithm until the maneuver is perfected. A geometric attitude controller, valid for all flight modes is employed in order to track the pitch angle according to the feedforward law. Further, a high-fidelity thrust model of the propeller for varying advance-ratio and orientation angle is obtained from wind tunnel data which is captured using a neural network model. This facilitates accurate application of feedforward thrust for varying flow conditions during transition. Experimental flight trials are performed to demonstrate the robustness and rapid convergence of the proposed learning algorithm.

This paper highlights the significance of the rotor dynamics in control design for small-scale aerobatic helicopters, and proposes two singularity free robust attitude tracking controllers based on the available states for feedback. 1. The first, employs the angular velocity and the flap angle states (a variable that is not easy to measure) and uses a backstepping technique to design a robust compensator (BRC) to \textbf{\textit{actively}} suppress the disturbance induced tracking error. 2. The second exploits the inherent damping present in the helicopter dynamics leading to a structure preserving, \textbf{\textit{passively}} robust controller (SPR), which is free of angular velocity and flap angle feedback. The BRC controller is designed to be robust in the presence of two types of uncertainties: structured and unstructured. The structured disturbance is due to uncertainty in the rotor parameters, and the unstructured perturbation is modeled as an exogenous torque acting on the fuselage. The performance of the controller is demonstrated in the presence of both types of disturbances through numerical simulations. In contrast, the SPR tracking controller is derived such that the tracking error dynamics inherits the natural damping characteristic of the helicopter. The SPR controller is shown to be almost globally asymptotically stable and its performance is evaluated experimentally by performing aggressive flip maneuvers. Throughout the study, a nonlinear coupled rotor-fuselage helicopter model with first order flap dynamics is used.