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Nowadays, running is said to be one of the common activities that be practiced by various people especially athletes. Back then, there were some researchers report that most of the injuries among athletes involves lower hip bodies. It is due to some factors such as body and foot posture during running activity, selection shoe and style of running. Hence, this research is about to design and develop an insole monitoring system using ESP 32 development board and FSR sensor for the purpose of force distribution detection on runner’s foot. The development of smart insole is to countermeasure the risk of injury to the athletes. This system includes (ESP 32) development board which act as a microcontroller that interfaced with a Wi-Fi module and force sensing resistance (FSR) sensor to detect the force distribution of runner’s foot in (kg) unit. The system able to detect the foot force distribution acts by the runner and transmits the output data of the FSR sensor through the application which called Blynk. The experiments had done through two methods which are jogging and running. The force monitoring data was obtained through the Blynk Application via Wi-Fi. The design and development of insole monitoring system has successfully done and implemented on the runner.

This paper presents a study on the conceptual design of an exoskeleton suit for post-stroke rehabilitation. A lower-limb exoskeleton suit is proposed to facilitate the post-stroke patients in the restoration of their gait motion. The aim of this study is to design and analyze the mechanical properties and strength via the finite element method (FEM). The exoskeleton suit is capable to assist the victims of post-stroke patients from sitting to stand-up positions and vice versa. The design aspect takes the basis of the human anatomy of Asian people with an average mass of 80 kg. The most effective and optimum design of the exo-suit model is evaluated through FEM static stress analysis using CATIA and ANSYS. Results proved that the proposed design is able to fully support the aforementioned average mass with the maximum Von-Mises stress of 9.5887e7 N/m2 (Standing Position) and 160.16e6 N/m2 (Bent Knee Position) of which did not exceed the yield strength of 180e6 N/m2

Most smart material based actuators (smart actuators) are known for their prominent characteristics of a high resolution of positioning, high bandwidth, and the ease of integration in miniaturized systems. However, their applications are restricted by the inherent hysteresis nonlinearity. This paper presents a new nonlinear discrete control design to improve hysteresis compensation in the smart actuators particularly in the piezoelectric based actuators. The control development takes the prescribed performance control framework as the basis and fuses it into a new modified Bouc-Wen (MBW) model. Through the theoretical analysis, it is shown that the designed control law guarantees the stability of the closed-loop system. Finally, the efficacy of the control framework is verified via a real case application where a linear piezoelectric actuated positioning system (PEA stage) is used as the testbed. The experimental results confirm that the formulated control scheme has the capacity for improving the output-tracking performance in the PEA stage.

Most smart material based actuators (smart actuators) are known for their prominent characteristics of high resolution of positioning, high bandwidth, and the ease of integration in miniaturized systems. However, their applications are restricted by the inherent hysteresis nonlinearity. This paper presents a new modified Bouc-Wen (MBW) model which has a rate-dependent property. Then the proposed model is directly used in developing a robust adaptive control in order to eliminate the hysteresis effects. Finally, the efficacy of the designed control framework is verified via a real case where a giant magnetostrictive actuator (GMA) is used as the testbed.

Hard nonlinearity or hysteresis effect is the main obstacle in most smart material based actuators which makes their optimal usage impossible. Thus, it is essential to develop a comprehensive strategy for modeling and control in order to mitigate this hysteresis nonlinearity. This paper investigates the viability of the differential equations based models towards hysteresis characterization and control fusion strategy in order to solve the tracking problem in the piezoelectric-based actuators. The analytical and simulation results suggest that this category of model is simple to use and has clear physical meanings. More importantly, it is established that only Bouc-Wen (BW) model has the ability to be synthesized directly into the control design. Finally, a control strategy is devised based on BW model and is experimentally verified in the discrete-time domain.

This paper devoted for the implementation of a learning algorithm, utilized Artificial Neural Network (ANN), to predict the passive joint angular positioning for 3R under-actuated serial robot. Under-actuated system has less number of actuators than the degrees of freedom; therefore, the estimating or modelling of its behaviour is difficult with many uncertainties. Thus, to overcome the disadvantages of several methods reported in literatures. A specific ANN model has been designed and trained to learn a desired set of joint angular positions for the passive joint from a given set of input torques and angular positions for the active joints over a certain period of time. ANN proposes from being free model technique. Consequently, data from sensors fixed on each joints were collected experimentally and provided for the developed ANN model. The learning algorithm can directly determine the position of its passive joint, and can, therefore, completely eliminate the need for any system modelling. Hence, this method could be generalized for the prediction of under-actuated systems behaviour. Results show a successful implementation of the learning algorithm in predicting the behaviour for 3R underactuated robot.

The ankle-foot of human body is a multi-joint structure that accommodates complex foot motion. Abnormality to the ankle-foot due to injury or disease can result in abnormal gait motion. In such cases, physiotherapist has to assist hemiplegic patients (ankle dorsiflexor muscles with lack of dorsiflexion assist moment) in rehabilitation therapy by using gait training in parallel bars. Physiotherapist has to support hemiplegic patient to position foot and also supports their stand balance. This prolongs multiple task puts extra burden to physiotherapist which gives side effect such as muscular strain or bone fracture while doing the task. Consequently, the motion of the foot patients did not follow the normal gait pattern. Therefore, there is a need to develop an effective ankle foot orthosis (AFO) to solve the long issue-problem. This research was undertake to embark on the modeling and designing of new ankle foot orthosis (AFO) using active control system which later could be used to help patients with ankle dorsiflexor muscles problem. The work was carried out in four stages involving modeling and simulation of DC motor, algorithm development, design and fabrication of the orthosis and finally, evalaution of the product and its functions. The orthosis was tested on healthy volunteer and the results show that the objective to develop and fabricate a new type of robust ankle foot orthosis which can control movement has been achieved successfully.

This paper demonstrates, theoretically and experimentally, the feasibility of utilizing Shape Memory Alloy (SMA) as an actuator in controlling the flexural vibrations of a flexible cantilevered beam. The shape memory alloy used in this study is merely a straight wire which is made of nickel titanium alloy called Nitinol. Acting as tendons, these SMAs undergo phase transformation, to the austenitic phase, producing significant forces and displacement capabilities as well as low power consumption. This actuator unit is composed of a SMA wire attached to a spring in series. After being set-up with a load cell the transfer functions of the actuator are measured. Considering the uncertainty of the actuator unit performance the H-infinity optimal controllers are designed and installed into the control system. By integrating the thermal and dynamic characteristics of the SMA into beam dynamical model the composite beam-actuators system can now be developed. The robust stability performance of the designed controller is evaluated through vibrational test on the cantilever and the result is shown to be adequately attenuated.

Hysteresis is a fundamental problem in most smart material-based actuators. This phenomenon limits the performance of systems driven by these actuators. This paper presents a control fusion strategy for hysteretic piezoelectric-based actuators which are described by Bouc-Wen model. A discrete prescribed performance control algorithm is developed and fused into the BW model. To verify the effectiveness of the modelling and control methods, experiments are made on a commercial piezoelectric actuator product. It is shown that the proposed controller guarantees not only the asymptotic stability but also transient performance.

The behaviour of skin is still not well understood and characterising skin properties is always challenging due to its complex biological structure. Nevertheless, this paper highlights the success of determining skin material parameters using Ogden's model and finite element (FE) simulation. The approach involved integrating experiment, FE modelling and inverse-FE analysis. Data from in vivo experiments were used to develop 2D hyperelastic finite element models based on Ogden's constitutive equation and systematic case studies were constructed. By iteratively varying several material parameters and values, FE simulations were performed to simulate the skin deformation according to the actual experimental set up. The results were compared to the experiments' and the best match curve constitutes the material parameters. The current results show that the Ogden's coefficient and exponent for the subject was estimated to be μ = 10 Pa and α = 40 respectively. Further analyses using other models such as Mooney-Rivlin and Neo-Hookean could be carried out for comparison. Nevertheless, this study has contributed to the knowledge about skin behaviour.

This paper presents initial study of new control PID-Active Force Control (PIDAFC) in controlling twin rotor multi-input multi-output System (TRMS). The objective is to control the TRMS response in order to obey the desired output and rejecting external disturbances. To control the TRMS was challenging since the rotor interact badly at the beam between yaw and pitch. For this reason, it considers as multi input and multi output (MIMO) with nonlinear behavior. The new approach using PID-AFC integrate with neural network and fuzzy logic was proposed to compensate the disturbance occur on TRMS. AFC scheme refer as based controller was used to estimate the disturbance torque while neural network and fuzzy logic act as an optimization device. In initial stage PID-AFC can still be used in minimize the tracking error and rejecting the disturbances. The proposed approach is exhibited through the simulation.

Dynamic Ankle Foot Orthosis (DAFO) is a revolutionary of the Ankle Foot Orthosis, which is an equipment used to control the motion and position of ankles. It is designed to correct deformities for patients who require treatment of disorders related to muscles and nerves functional failure. Unfortunately, the current designs of DAFO are limited only for patients who can move ankles by their own. This drives for new researches with the aim to develop an innovative development of powered DAFO and currently many researches are still in progress. This paper proposes a new type of DAFO model, which was fabricated locally and assesses its design parameters and functions using computer simulation and numerical analyses. The proposed DAFO was modeled in 3-dimensional using SOLIDWORKS 2010 and several simulations and analyses were carried out to evaluate the current design. Finite element analysis was conducted to determine deformation and stress distribution for DAFO made of two types of materials, which are Acrylonitrile Butadiene Styrene (ABS) and Polypropylene (PP). The failure and factor of safety (FOS) of the proposed model were evaluated under specified boundary conditions and load applied for static and motion condition. Results from this study show that the model functions well and do not fail during testing. The results from the motion analysis show that the DAFO moves according to the design specification. This proves that the material used is the right choice and the current design is acceptable. The current study also proves that computational simulation could be a useful and practical tool in aiding product design. Moreover, it saves time and cost compared to laboratory and destructive testing. Therefore, it can be concluded that the current study has successfully utilized computational analysis and simulation tools in developing the proposed DAFO.

This paper presents a study on control architecture improvement of a MM3A microrobotic system (MM3A) in terms of high precision capability using a hybrid control strategy viz. PD control scheme integrated with intelligent Active Force Control (AFC) and Fuzzy Logic (FL). The dynamic model of the MM3A is derived using Recursive Newton-Euler method. The simulation was carried out using MATLAB, Simulink. Three control schemes were utilized in this study namely, proportional-derivative (PD) controller, PD-AFC-Crude Approximation, and PD-AFC-Fuzzy Logic estimator in order to test the system performance and robustness. Based on the simulation results, it is proven that the proposed scheme has outstanding performance compared to the classical control scheme. Using AFC-FL strategy, the MM3A was able to achieve its desired performance excellently. Incorporating neural networks into the system tightens the errors and reduces the time taken for the robot to achieve its desired response.

Distracted driving has emerged as a factor of road accidents. Hence, the detection increase of drivers' cognitive workload has been a vital issue for establishing safety support systems. Studies on the estimation of driver's mental workload have been performed using various devices. However, an applicable and a sensitive device is still vague. One of the promising devices available is using blood pulse wave. The purpose of this study is to develop a driver's distraction detection method through blood pulse wave analysis. This paper focus on how to determine the threshold of drivers' distraction. Based on the experiments that were conducted on driving simulator, we did some suggestions regarding the effects of cognitive workload that been imposed to drivers to driver's blood pulse wave

The development of Neural-network (NN) technology stemmed from the desire to create an artificial system that could perform “intelligent” tasks similar to those performed by the human brain. In this paper the performance of NN to the structural optimization concept of frame structure is presented. The optimum set of frame designs is obtained using Finite Element (FE) software where stress and displacement constraints has been chosen as the optimum criteria. The optimized data then used to train the NN through Back Propagation Neural-network technique (BPNN) to identify the capability of this strategy to predict the exact data. Three case studies were performed with different complexity of structural configuration. Result indicates the Neural-network capable of predicting the exact solution with proper training but this ability depends on the complexity of the frame structural optimization itself.