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The aim of the current study is proposing a novel framework to attain the optimum value of a flexible arm manipulator parameters for payload launching missions.

The proposed scheme is based on optimal control approach and combines direct and indirect search methods while considering the actuator capacity.

Three nonlinear parameter-optimization problems will be solved to illustrate how the proposed algorithm can be exploited. Employing variational based nonlinear optimal control within the suggested framework, the answer of these problems is highly intertwined to the solution of a set of differential equations with split boundary values. To solve the obtained boundary value problem (BVP), the related solver of MATLAB® software, bvp6c, will be employed. The achieved simulation results support the worth of the developed procedure.

For the first time, the optimal parameters of a flexible link robot for object launching are found in the current research. In addition, the actuator saturation limits are considered which enhances the applicability of the suggested method in the real world applications.

Trajectory tracking is a common problem in the field of mobile robots which has attracted a lot of attention in the past two decades. Therefore, besides the search for new controllers to achieve a better performance, improvement and optimization of existing control rules are necessary. Trajectory tracking control laws usually contain constant gains which affect greatly the robot’s performance.

In this paper, a method based on neural networks is introduced to automatically upgrade the gains of a well-known trajectory tracking controller of wheeled mobile robots. The suggested method speeds up the convergence rate of the main controller.

Simulations and experiments are performed to assess the ability of the suggested scheme. The obtained results show the effectiveness of the proposed method.

In this paper, a method based on neural networks is introduced to automatically upgrade the gains of a well-known trajectory tracking controller of wheeled mobile robots. The suggested method speeds up the convergence rate of the main controller.

This paper aims to deal with the development of a novel lower limb exoskeleton to assist disabled people in stair ascending.

For this purpose, a novel design of a mixture of motors and cables has been proposed for users to wear them easily and show the application of the system in stair climbing.

One of the prominences of this study is the provided robot design where four joints are actuated with only two motors; each motor actuates either the knees or ankles. Another advantage of the designed system is that with motors placed in a backpack, the knee braces can be worn under clothes to be concealed. Finally, the system performance is evaluated using electromyography (EMG) signals showing 28 per cent reduction in energy consumption of related muscles.

This investigation deals with the development of a novel lower limb exoskeleton to assist disabled people in stair ascending.

The purpose of this paper is to focus on an online closed-loop (CL) approach for performing dynamic object manipulation (DOM) by a flexible link manipulator.

Toward above goal, a neural network and optimal control are integrated in a closed-loop structure, to achieve a robust control for online DOM applications. Additionally, an elegant novel numerical solution method will be developed which can handle the split boundary value problem resulted from DOM mission requirements for a wide range of boundary conditions.

The obtained simulation results reveal the effectiveness of both proposed innovative numerical solution technique and control structure for online object manipulation purposes using flexible manipulators.

The object manipulation problem has previously been studied, however, for the first time its accomplishment by flexible link manipulators was addressed just in offline form considering an open-loop control structure (Tarvirdizadeh and Yousefi-Koma, 2012). As an extension of Tarvirdizadeh and Yousefi-Koma (2012), the current research, consequently, focusses on a numerical solution and a CL approach for performing DOM by a flexible link manipulator.

The purpose of this paper is to propose an efficient and straightforward approach for system identification of a rotating single link flexible manipulator (RSLFM). Also, the achieved results are experimentally validated through identification procedure.

The proposed system identification approach is applied to a RSLFM with a tip mass. At first, the dynamic model of the system is derived using Lagrange method. Then, an efficient method is developed for identification of such a system. This method facilitates the nonlinear complicated identification problem of the RSLFM to a simplified root finding problem.

The main advantage of the developed method is to convert a complicated system identification process to a simple nonlinear equation solution. This approach uses small-size input/output data set and requires a short-time interval of data acquisition, which gives important advantages in lower computational load and lower execution time. The investigated approach is studied on experimental system identification of a single link flexible manipulator. To demonstrate this fact, the developed method is successfully applied in identification of two other mechanical systems; the inverted pendulum on a cart and the ball and beam apparatus.

In this work, the proposed identification approach has been originally applied to a RSLFM and two other mechanical examples. All obtained identification results show the performance and applicability of the developed method clearly. This approach is not restricted in using state space or transfer function. It has significant superiority in comparison with other known approaches including autoregressive with exogenous input (ARX) and Box-Jenkins (BJ).

The purpose of this paper is to develop a nonlinear control system for flight trajectory control of flapping Micro Aerial Vehicles (MAVs), subjected to wind.

In the dynamic study and fabrication of the MAV, biomimetic principles are considered as the best inspiration for the MAV's flight as well as design constraints. The blade element theory, which is a two‐dimensional quasi‐steady state method, is modified to consider the effect of MAV's translational and rotational velocity. A quaternion‐based dynamic wrench method is then developed for the dynamic system.

The flapping flight dynamics is highly nonlinear and the system is under‐actuated, so any linear control strategy fails to meet any desired maneuver for trajectory tracking. In this study, a controller with quaternion‐based feedback linearization method is designed for the dynamical averaged system. It is shown that the original system is bonded to a stable limit cycle with desired amplitude and the controller inputs are bounded.

The effectiveness of a synthesized controller is proved for the cruse and the Cuban‐8 maneuver.

The authors' major contribution is developing feedback linearization quaternion‐based controller and deriving some essential mathematics for implementing quaternion model in the synthesis of controller. A piezoelectric‐actuated wing model is developed for the control system. Results of cursing and turning modes of the flight indicate the stability of the flight. Finally, an appropriate controller is designed for the Cuban‐8 maneuver so that the MAV would follow the trajectory with a bounded fluctuation.

Wearables are gaining prominence in the health-care industry and their use is growing. The elderly and other patients can use these wearables to monitor their vitals at home and have them sent to their doctors for feedback. Many studies are being conducted to improve wearable health-care monitoring systems to obtain clinically relevant diagnoses. The accuracy of this system is limited by several challenges, such as motion artifacts (MA), power line interference, false detection and acquiring vitals using dry electrodes. This paper aims to focus on wearable health-care monitoring systems in the literature and provides the effect of MA on the wearable system. Also presents the problems faced while tracking the vitals of users.

MA is a major concern and certainly needs to be suppressed. An analysis of the causes and effects of MA on wearable monitoring systems is conducted. Also, a study from the literature on motion artifact detection and reduction is carried out and presented here. The benefits of a machine learning algorithm in a wearable monitoring system are also presented. Finally, distinct applications of the wearable monitoring system have been explored.

According to the study reduction of MA and multiple sensor data fusion increases the accuracy of wearable monitoring systems.

This study also presents the outlines of design modification of dry/non-contact electrodes to minimize the MA. Also, discussed few approaches to design an efficient wearable health-care monitoring system.