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The purpose of this paper is to develop a real‐time simulation environment for the validation of controller for an autonomous small‐scale helicopter.

The real‐time simulation platform is developed based on the nonlinear model of a series of small‐scale helicopters. Dynamics of small‐scale helicopter is analyzed through simulation. The controller is designed based on the extracted linear model.

The model‐based linear controller can be effectively designed and tested using real‐time simulation platform. The hover controller is demonstrated to be robust against wind disturbance.

To use the real‐time simulation environment to test and validate controllers for small‐scale helicopters, basic helicopter parameters need to be measured, calculated or estimated.

The real‐time simulation environment can be used generically to test and validate controllers for small‐scale helicopters.

The paper presents the design and development of a low‐cost hardware in the loop simulation environment using xPC target critical for validating controllers for small‐scale helicopters.

The paper aims to achieve translational shaking tests on a 6-DOF hydraulic parallel manipulator. Shaking tests are commonly performed on shaking tables, which are generally used for small motion ranges and are usually financially costly. The research is required to generate shaking motions in three translational directions for a specimen for shaking tests, but it also needs to produce 6-degree of freedom (DOF) motions with large motion ranges.

A hydraulic 6-DOF (degree of freedom) parallel manipulator is applied to achieve this goal. The link-space control is adopted for the manipulator, and PID controller and feed-forward controller are used for each loop of the system. A hybrid reference signal generator is proposed by using a shaking controller, which is developed to convert the shaking motion into position signal. The converted result is directly added to the pose signal. The whole real-time control system is realized by using MATLAB xPC Target.

The developed method is verified on the hydraulic 6-DOF parallel manipulator with specimen. Experiments show very promising results that the proposed technology is really applicable to perform translational shaking tests on the hydraulic parallel manipulator.

A simple yet efficient solution is proposed that allows shaking tests in three translational directions performed on the hydraulic 6-DOF parallel manipulator with wide motion ranges. The paper presents a state-of-the-art related to the applications of parallel robots in several fields of technology.

The purpose of this paper is to propose a software engineering procedure for real-time software development and verification of an autonomous underwater robotic system. High performance and robust software are one of the requirements of autonomous systems design. A simple error in the software can easily lead to a catastrophic failure in a complex system. Then, a systematic procedure is presented for this purpose.

This paper utilizes software engineering tools and hardware-inthe-loop (HIL) simulations for real-time system design of an autonomous underwater robot.

In this paper, the architecture of the system is extracted. Then, using software engineering techniques a suitable structure for control software is presented. Considering the desirable targets of the robot, suitable algorithms and functions are developed. After the development stage, proving the real-time performance of the software is disclosed.

A suitable approach for analyzing the real-time performance is presented. This approach is implemented using HIL simulations. The developed structure is applicable to other autonomous systems.

This paper aims to increase the safety of the robots’ operation by developing a novel method for real-time implementation of velocity scaling and obstacle avoidance as the two widely accepted safety increasing concepts.

A fuzzy version of dynamic movement primitive (DMP) framework is proposed as a real-time trajectory generator with imbedded velocity scaling capability. Time constant of the DMP system is determined by a fuzzy system which makes decisions based on the distance from obstacle to the robot’s workspace and its velocity projection toward the workspace. Moreover, a combination of the DMP framework with a human-like steering mechanism and a novel configuration of virtual impedances is proposed for real-time obstacle avoidance.

The results confirm the effectiveness of the proposed method in real-time implementation of the velocity scaling and obstacle avoidance concepts in different cases of single and multiple stationary obstacles as well as moving obstacles.

As the provided experiments indicate, the proposed method can effectively increase the real-time safety of the robots’ operations. This is achieved by developing a simple method with low computational loads.

This paper proposes a novel method for real-time implementation of velocity scaling and obstacle avoidance concepts. This method eliminates the need for modification of original DMP formulation. The velocity scaling concept is implemented by using a fuzzy system to adjust the DMP’s time constant. Furthermore, the novel impedance configuration makes it possible to obtain a non-oscillatory convergence to the desired path, in all degrees of freedom.

The purpose of this paper is to develop accurate model and simulation of mechanical power transmission within roller‐screw electromechanical actuators with special attention to friction, compliance and inertia effects. Also, to propose non‐intrusive experiments for the identification of model parameters with an integrator or system‐oriented view.

At system design level, the actuation models need to reproduce with confidence the energy losses and the main dynamic effects. The adopted modelling methodology is based on non‐intrusive measurements taken on a standard actuator test‐bench. The actuator model is first structured with respect to the bond‐graph formalism that allows a clear identification of the considered effects and associated causalities for model implementation. Various approaches are then combined, mixing blocked or moving load, position or torque control and time or frequency domains analysis. The friction representation model is suggested using a step‐by‐step approach that covers a wide domain of operation. The model is validated under varying torque and speed conditions.

A structured model is introduced with support of the bond‐graph formalism. Combining blocked/moving load and time/frequency domain experiments allows the development of progressive model identification. An advanced friction representation model is proposed including the effects of speed, transmitted force, quadrant of operation and roller‐screw preload.

Mechanical transmission energy losses and dynamics are modelled in a system‐oriented view without massive need to confidential design parameters. Not only speed but also load and operation quadrant effects are reproduced by the proposed friction model. The non‐intrusive experimental procedure is made consistent with use of a standard actuator test‐bench.

The purpose of this paper is to describe a project which seeks to develop a new generation of powered prostheses based on lightweight, uniquely tuned, energy‐storing elastic elements in series with optimal actuator systems that will significantly reduce the peak power requirement of the motor and the total system energy requirement while providing the amputee 100 percent of required “push‐off” power and ankle sagittal plane range‐of‐motion comparable to able‐bodied gait.

This paper presents the design, power, and energy‐efficiency analyses, and the results of a five‐month trial with one trans‐tibial amputee subject as part of the first phase of the Spring Ankle with Regenerative Kinetics project.

The data show that by leveraging uniquely tuned springs and transmission mechanisms, motor power is easily amplified more than four fold and the electric energy requirement is cut in half compared with traditional approaches.

This paper describes an energy efficient, powered transtibial prosthesis currently unavailable commercially. Motor power and energy requirements are reduced with use of a unique design that employs regenerative kinetics.

Examines some of the recent technical developments that are leading to a wider use of powerful methods in medical microscopy.

Reviews some of the microscopic techniques relevant to medicine, then looks at hardware developments in microscopes, filters and cameras.

Highly sophisticated techniques such as time‐resolved fluorescence measurements are now incorporated in turnkey instruments, using picosecond diode lasers for accurate measurement of fluorescent lifetimes. Advances in optical fibre coating technology in the telecoms field have led to improved filters for fluorescence microscopy, and imaging allows the detection of non‐visible wavelengths and very low light levels. Many microscopes are modular, so that users can upgrade to further capabilities at will. Automatic medical diagnosis software is coming onto the market.

Highlights the hardware and software developments that are enabling powerful microscopic methodologies to enter into general use.

This paper aims to study a parameter tuning method for the active disturbance rejection control (ADRC) to improve the anti-interference ability and position tracking of the performance of the servo system, and to ensure the stability and accuracy of practical applications.

This study proposes a parameter self-tuning method for ADRC based on an improved glowworm swarm optimization algorithm. The algorithm is improved by using sine and cosine local optimization operators and an adaptive mutation strategy. The improved algorithm is then used for parameter tuning of the ADRC to improve the anti-interference ability of the control system and ensure the accuracy of the controller parameters.

The authors designed an optimization model based on MATLAB, selected examples of simulation and experimental research and compared it with the standard glowworm swarm optimization algorithm, particle swarm algorithm and artificial bee colony algorithm. The results show that the response time of using the improved glowworm swarm optimization algorithm to optimize the auto-disturbance rejection control is short; there is no overshoot; the tracking process is relatively stable; the anti-interference ability is strong; and the optimization effect is better.

The innovation of this study is to improve the glowworm swarm optimization algorithm, propose a sine and cosine, local optimization operator, expand the firefly search space and introduce a new adaptive mutation strategy to adaptively adjust the mutation probability based on the fitness value, improve the global search ability of the algorithm and use the improved algorithm to adjust the parameters of the active disturbance rejection controller.

The purpose of this paper is to design a third-order linear active disturbance rejection controller (LADRC) to improve the response characteristics and robustness of the electrohydraulic servo system.

The LADRC was designed by replacing the nonlinear functions in each part of ADRC with linear functions or linear combinations, and the parameters of each part of the LADRC were connected with their bandwidth through the pole configuration method to reduce the required tuning parameters, and used an improved grey wolf optimizer to tune the LADRC parameters.

The anti-interference control simulation and experiment on the LADRC, ADRC and proportion integration differentiation (PID) were carried out to test the robustness, anti-interference ability and superiority of the designed LADRC. The simulation and experiment results showed that the LADRC control and anti-interference control had excellent performance, and because of its simple structure and fewer parameters, LADRC was easier to implement and had a better control effect and anti-interference.

For the problems of parameter perturbation, unknown interference and inaccurate model in the electrohydraulic position servo system, the designed third-order LADRC has good tracking accuracy and anti-interference, has few parameters and is conducive to promotion.

Considering the complexity of dynamic and friction modeling, this paper aims to develop an adaptive trajectory tracking control scheme for robot manipulators in a universal unmodeled method, avoiding complicated modeling processes.

An augmented neural network (NN) constituted of radial basis function neural networks (RBFNNs) and additional sigmoid-jump activation function (SJF) neurons is introduced to approximate complicated dynamics of the system: the RBFNNs estimate the continuous dynamic term and SJF neurons handle the discontinuous friction torques. Moreover, the control algorithm is designed based on Barrier Lyapunov Function (BLF) to constrain output error.

Lyapunov stability analysis demonstrates the exponential stability of the closed-loop system and guarantees the tracking errors within predefined boundaries. The introduction of SJFs alleviates the limitation of RBFNNs on discontinuous function approximation. Owing to the fast learning speed of RBFNNs and jump response of SJFs, this modified NN approximator can reconstruct the system model accurately at a low compute cost, and thereby better tracking performance can be obtained. Experiments conducted on a manipulator verify the improvement and superiority of the proposed scheme in tracking performance and uncertainty compensation compared to a standard NN control scheme.

An enhanced NN approximator constituted of RBFNN and additional SJF neurons is presented which can compensate the continuous dynamic and discontinuous friction simultaneously. This control algorithm has potential usages in high-performance robots with unknown dynamic and variable friction. Furthermore, it is the first time to combine the augmented NN approximator with BLF. After more exact model compensation, a smaller tracking error is realized and a more stringent constraint of output error can be implemented. The proposed control scheme is applicable to some constraint occasion like an exoskeleton and surgical robot.