Performance and stability of fly-inspired, saccade-based hybrid control

In a way analogous to human vision, the fruit fly Drosophila melanogaster and many other flying insects generate smooth and saccadic movements to stabilize and shift their gaze in flight, respectively. It has been hypothesized that this combination of continuous and discrete movements benefits both flight stability and performance, particularly at high frequencies or speeds. Here we develop a hybrid control system model to explore the effects of saccades on the yaw stabilization reflex of D. melanogaster. Inspired from experimental data, the model includes a first order plant, a Proportional-Integral (PI) continuous controller, and a saccadic reset system that fires based on the integrated error of the continuous controller. We explore the gain, delay and switching threshold parameter space to quantify the optimum regions for stability and performance. We show that the addition of saccades to a continuous controller provides benefits to both stability and performance across a range of frequencies. Our model suggests that Drosophila operate near its optimal switching threshold for its experimental gain set. We also show that based on experimental data, D. melanogaster operates in a region that trades off performance and stability. This trade-off increases flight robustness to compensate for environmental uncertainties such as wing damage.

HYBRID CONTROL SYSTEM IN BIONIC LEG USING MYOWARE SENSOR

A bionic robot leg (BRL) is a contrivance used to supersede a loss component of the lower limb due to amputation or congenital disability. Hybrid control of BRL is opted to obtain the maximum performance of BRL equipped with precise forms of kineticism and expeditious response by truncating the error and maximum overshoot and reducing time settle. This research aims to create a BRL innovation product for persons with disabilities at the Bali Puspadi Foundation. The novelty of this BRL is the implementation of the algorithm as outlined in the hybrid control system in the Arduino support package. The BRL utilizes a MyoWare sensor and an Arduino Mega 2560 microcontroller equipped with Matlab/Simulink R2020a programming software. The sensor is utilized to read the angular movement of the DC motor between 0 - 60° degrees and vice versa, following the concept of the gate cycle. The results obtained from the hybrid control simulation are 0.0713% on maximum overshoot, 0.0415% on steady-state error, and 1.292s on system time settle. Furthermore, the results obtained from the hybrid controller experiment are 0.627% on maximum overshoot, 0.257% on steady-state error, and 0.8s on system time settle.

Improved hand prostheses control for transradial amputees based on hybrid of voice recognition and electromyography

The control of prostheses and their complexities is one of the greatest challenges limiting wide amputees’ use of upper limb prostheses. The main challenges include the difficulty of extracting signals for controlling the prostheses, limited number of degrees of freedom (DoF), and cost-prohibitive for complex controlling systems. In this study, a real-time hybrid control system, based on electromyography (EMG) and voice commands (VC) is designed to render the prosthesis more dexterous with the ability to accomplish amputee’s daily activities proficiently. The voice and EMG systems were combined in three proposed hybrid strategies, each strategy had different number of movements depending on the combination protocol between voice and EMG control systems. Furthermore, the designed control system might serve a large number of amputees with different amputation levels, and since it has a reasonable cost and be easy to use. The performance of the proposed control system, based on hybrid strategies, was tested by intact-limbed and amputee participants for controlling the HANDi hand. The results showed that the proposed hybrid control system was robust, feasible, with an accuracy of 94%, 98%, and 99% for Strategies 1, 2, and 3, respectively. It was possible to specify the grip force applied to the prosthetic hand within three gripping forces. The amputees participated in this study preferred combination Strategy 3 where the voice and EMG are working concurrently, with an accuracy of 99%.

A hybrid control system for investigating a high level of decision in IoT

<span lang="IN">In the modern world, the search started for cheap and efficient operating system sources has begun can converted to civilian ends</span><span>.</span><span lang="IN"> Internet of Things (IoT) is one of the most realistic applications for remote control and remote management using a wide network.</span><span lang="EN">In this paper, a control system is designed and built to manage and control traffic lights and street lighting systems, as well as turning on/off generators in a small virtual environment.</span><span> This was implemented by designing and building a hybrid electronic circuit that combines the closed-circuit control system and the open circuit system. The closed circuit regulates the system according to the desired condition without operator interaction; while the open circuit operates on demand. This type of a hybrid control system demonstrated its high flexibility by controlling devices and its high efficiency compared to the closed circuit and the open circuit system independently. It also helps reduce the number of maintenance guys and energy consumption as well as the cost.</span>

Design of Omnidirectional Robot Using Hybrid Brain Computer Interface

The paper presents a Brain-Computer Interface (BCI) controller for a semiautonomous three-wheeled omnidirectional robot capable of processing real-time commands. The kinematical model of the omni-directional robot and the software architecture of the overall hybrid system with motion control algorithm are presented. The system design, acquisition of the electroencephalography (EEG) signal, recognition processing technology and implementation are the main focus. Signals are recorded and processed by a program called OpenVibe. Preprocessed signals are cleaned by EEGLAB and used to train OpenVibe classifiers to accurately identify the expected signals produced by the users. Once identified, the controller converts the signal into input commands {forward, left, right, rotate, stop}, which are written in the Python syntax and delivered to the robot system. The robot has three degrees of freedom (DoF) allowing it to traverse its environment in any direction and orientation. The sensor system provides feedback allowing for the semi-autonomous control to avoid obstacles. Overall, this paper demonstrates the architecture of the hybrid control system for omni-directional robot using BCI. The developed system integrates the EEG signal to control the motion of the robot and the experimental results show the system performance and effectiveness of possessing the user’s EEG signals.

Hybrid Electromagnetic Shunt Damper for Vibration Control

It has been shown that shunting electromagnetic devices with electrical networks can be used to damp vibrations. These absorbers have however limitations that restrict the control performance, i.e., the total damping of the system and robustness versus parameter variations. On the other hand, the electromagnetic devices are widely used in active control techniques as an actuator. The major difficulty that arises in practical implementation of these techniques is the power consumption required for conditioners and control units. In this study, robust hybrid control system is designed to combine the passive electromagnetic shunt damper with an active control in order to improve the performance with low power consumption. Two different active control laws, based on an active voltage source and an active current source, are proposed and compared. The control law of the active voltage source is the direct velocity feedback. However, the control law of the active current source is a revisited direct velocity feedback. The method of maximum damping, i.e., maximizing the exponential time-decay rate of the response subjected to the external impulse forcing function, is employed to optimize the parameters of the passive and the hybrid control systems. The advantage of using the hybrid control configuration in comparison with purely active control system is also investigated in terms of the power consumption. Besides these assets, it is demonstrated that the hybrid control system can tolerate a much higher level of uncertainty than the purely passive control systems.