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The main purpose of the paper is to develop model basing on the modified and properly‐adopted Fermi‐Dirac equation which combines proper accuracy with adequate simplicity as well as to show how steady state and transient curves resulting from this model can be applied for solving design task.

The standard Fermi‐Dirac equation was modified and extended. Full performance cycle for the SMA actuator was characterized by double‐valued function describing the actuator activation and the actuator deactivation. All these functions and parameters can be easily determined by analysis of measurement data or with use of Hooke‐Jeeves optimization algorithm.

SMA linear actuator can be used in mechatronic systems as a special non‐standard drive when ultra‐light mass and very simple mechanical construction of power feed system is required. The proposed steady‐state and transient performance curves as well as operation diagram constitute sufficient base for effective designing SMA drive systems.

The greatest disadvantage of a SMA actuator is long time of deactivation resulting from slow self‐cooling process. As far as efficiency is concerned as essential factor for choosing the most suitable linear actuator, there is no sense to take into account a linear SMA actuator because of its very low efficiency.

Designer can use performance curve which determines proper length of SMA actuator and range of its motion. The proposed model can be implemented in SMA drive control unit for controlling position of the actuator.

Similarities between change of martensitic phase during transition process and probability P of electron energy level distribution described by the Fermi‐Dirac two‐variable equation were taken into account. Such an approach seems to express in the most suitable way the physical nature of m‐a transition. The authors decided to extend concept (proposed in Jayender et al.) and to adopt the Fermi‐Dirac equation for describing behaviour of a SMA linear actuator.

The purpose of this paper is to develop lightweight actuators in order to replace conventional hydraulic/pneumatic actuators and to apply the actuation system to a small flying vehicle.

A new type of control surface using a piezo‐composite actuator for a small flying vehicle has been designed and manufactured. The piezo‐composite actuator is composed of a piezoelectric ceramic layer, a carbon/epoxy layer and glass/epoxy layers. Through this, the miniaturization and weight reduction of the actuation systems for flying vehicle can be achieved. A simple model of the control surface has been manufactured and evaluated through experiments.

The performance test results showed that the developed actuator can produce stable angle of attack independent of the applied loading. A radio controller for the actuator was developed to control the motions wirelessly. It was found that the piezo‐composite actuator and its integrated controller system have a possibility to be used not only as a small flying vehicle but also as a control surface actuator of a small unmanned flying robot through the miniaturization of power supply and control system.

The paper describes the procedures of designing and manufacturing smart structure application of the piezo‐composite actuator with performance evaluation and comparison method. It is expected that piezo‐composite actuator can be used as a small flying vehicle control surface actuator through the miniaturization of power supply and control system with the use of the integrated radio controller MIPAD.

This paper presents an optimal design method of number and placements of piezoelectric patch actuators in active vibration control of a plate. Eigenvalue distribution of energy correlative matrix of control input force is applied to determine optimal number of the required actuators. Genetic algorithms (GAs) using active vibration control effects, which are taken as the objective function, are adopted to search optimal placements of actuators. The results show that disturbance exerted on a plate is a key factor of determining optimal number and placements of actuators in active structural vibration control, and a global and efficient optimization solution of multiple actuator placements can be obtained using GAs.

Series elastic actuators provide many benefits in force control of robots in unconstrained environments. These benefits include high force fidelity, extremely low impedance, low friction, and good force control bandwidth. Series elastic actuators employ a novel mechanical design architecture which goes against the common machine design principal of “stiffer is better”. A compliant element is placed between the gear train and driven load to intentionally reduce the stiffness of the actuator. A position sensor measures the deflection, and the force output is accurately calculated using Hooke’s Law (F = Kx). A control loop then servos the actuator to the desired output force. The resulting actuator has inherent shock tolerance, high force fidelity and extremely low impedance. These characteristics are desirable in many applications including legged robots, exoskeletons for human performance amplification, robotic arms, haptic interfaces, and adaptive suspensions.

The purpose of this study is to propose an improved design of PneuNets bending actuator which aims at obtaining larger deflection with the same magnitude of pressure. The PneuNets bending actuator shows potential application in the morphing trailing edge concept.

Finite element method is used to investigate the characteristics of the improved design bending actuator. Multiobjective optimal design of the PneuNets bending actuator is proposed based on the Gauss process regression models.

The maximum deflection is obtained when the height of the beams is smaller than half the height of the chambers. The spacing between chambers (beam length) has little effect on the deflection. Larger spacing could be used to reduce the actuator weight.

With the same pressure magnitude, the deflection of the improved design bending actuator is much larger than that of the baseline configuration. PneuNets bending actuator could increase the continuity of the aerodynamic surface compared to other actuators.

The purpose of this study is to develop a magnetic resonance imaging (MRI)-safe iron-free electrical actuator for MR-guided surgical interventions.

The paper deals with the design of an MRI compatible electrical actuator. Three-dimensional electromagnetic and thermal analytical models have been developed to design the actuator. These models have been validated through 3D finite element (FE) computations. The analytical models have been inserted in an optimization procedure that uses genetic algorithms to find the optimal parameters of the actuator.

The analytical models are very fast and precise compared to the FE models. The computation time is 0.1 s for the electromagnetic analytical model and 3 min for the FE one. The optimized actuator does not perturb imaging sequence even if supplied with a current 10 times higher than its rated one. Indeed, the actuator’s magnetic field generated in the imaging area does not exceed 1 ppm of the B₀ field generated by the MRI scanner. The actuator can perform up to 25 biopsy cycles without any risk to the actuator or the patient since he maximum temperature rise of the actuator is about 20°C. The actuator is compact and lightweight compared to its pneumatic counterpart.

The MRI compatible actuator uses the B₀ field generated by scanner as inductor. The design procedure uses magneto-thermal coupled models that can be adapted to the design of a variety actuation systems working in MRI environment.

To provide high torques needed to move a robot’s links, electric actuators are followed by a transmission system with a high transmission rate. For instance, gear ratios of 100:1 are often used in the joints of a robotic manipulator. This results into an actuator with large mechanical impedance (also known as nonback-drivable actuator). This in turn generates high contact forces when collision of the robotic mechanism occur and can cause humans’ injury. Another disadvantage of electric actuators is that they can exhibit overheating when constant torques have to be provided. Comparing to electric actuators, pneumatic actuators have promising properties for robotic applications, due to their low weight, simple mechanical design, low cost and good power-to-weight ratio. Electropneumatically actuated robots usually have better friction properties. Moreover, because of low mechanical impedance, pneumatic robots can provide moderate interaction forces which is important for robotic surgery and rehabilitation tasks. Pneumatic actuators are also well suited for exoskeleton robots. Actuation in exoskeletons should have a fast and accurate response. While electric motors come against high mechanical impedance and the risk of causing injuries, pneumatic actuators exhibit forces and torques which stay within moderate variation ranges. Besides, unlike direct current electric motors, pneumatic actuators have an improved weight-to-power ratio and avoid overheating problems.

The aim of this paper is to analyze a nonlinear optimal control method for electropneumatically actuated robots. A two-link robotic exoskeleton with electropneumatic actuators is considered as a case study. The associated nonlinear and multivariable state-space model is formulated and its differential flatness properties are proven. The dynamic model of the electropneumatic robot is linearized at each sampling instance with the use of first-order Taylor series expansion and through the computation of the associated Jacobian matrices. Within each sampling period, the time-varying linearization point is defined by the present value of the robot’s state vector and by the last sampled value of the control inputs vector. An H-infinity controller is designed for the linearized model of the robot aiming at solving the related optimal control problem under model uncertainties and external perturbations. An algebraic Riccati equation is solved at each time-step of the control method to obtain the stabilizing feedback gains of the H-infinity controller. Through Lyapunov stability analysis, it is proven that the robot’s control scheme satisfies the H-infinity tracking performance conditions which indicate the robustness properties of the control method. Moreover, global asymptotic stability is proven for the control loop. The method achieves fast convergence of the robot’s state variables to the associated reference trajectories, and despite strong nonlinearities in the robot’s dynamics, it keeps moderate the variations of the control inputs.

In this paper, a novel solution has been proposed for the nonlinear optimal control problem of robotic exoskeletons with electropneumatic actuators. As a case study, the dynamic model of a two-link lower-limb robotic exoskeleton with electropneumatic actuators has been considered. The dynamic model of this robotic system undergoes first approximate linearization at each iteration of the control algorithm around a temporary operating point. Within each sampling period, this linearization point is defined by the present value of the robot’s state vector and by the last sampled value of the control inputs vector. The linearization process relies on first-order Taylor series expansion and on the computation of the associated Jacobian matrices. The modeling error which is due to the truncation of higher-order terms from the Taylor series is considered to be a perturbation which is asymptotically compensated by the robustness of the control algorithm. To stabilize the dynamics of the electropneumatically actuated robot and to achieve precise tracking of reference setpoints, an H-infinity (optimal) feedback controller is designed. Actually, the proposed H-infinity controller for the model of the two-link electropneumatically actuated exoskeleton achieves the solution of the associated optimal control problem under model uncertainty and external disturbances. This controller implements a min-max differential game taking place between: (i) the control inputs which try to minimize a cost function which comprises a quadratic term of the state vector’s tracking error and (ii) the model uncertainty and perturbation inputs which try to maximize this cost function. To select the stabilizing feedback gains of this H-infinity controller, an algebraic Riccati equation is being repetitively solved at each time-step of the control method. The global stability properties of the H-infinity control scheme are proven through Lyapunov analysis.

Pneumatic actuators are characterized by high nonlinearities which are due to air compressibility, thermodynamics and valves behavior and thus pneumatic robots require elaborated nonlinear control schemes to ensure their fast and precise positioning. Among the control methods which have been applied to pneumatic robots, one can distinguish differential geometric approaches (Lie algebra-based control, differential flatness theory-based control, nonlinear model predictive control [NMPC], sliding-mode control, backstepping control and multiple models-based fuzzy control). Treating nonlinearities and fault tolerance issues in the control problem of robotic manipulators with electropneumatic actuators has been a nontrivial task.

The novelty of the proposed control method is outlined as follows: preceding results on the use of H-infinity control to nonlinear dynamical systems were limited to the case of affine-in-the-input systems with drift-only dynamics. These results considered that the control inputs gain matrix is not dependent on the values of the system’s state vector. Moreover, in these approaches the linearization was performed around points of the desirable trajectory, whereas in the present paper’s control method the linearization points are related with the value of the state vector at each sampling instance as well as with the last sampled value of the control inputs vector. The Riccati equation which has been proposed for computing the feedback gains of the controller is novel, so is the presented global stability proof through Lyapunov analysis. This paper’s scientific contribution is summarized as follows: (i) the presented nonlinear optimal control method has improved or equally satisfactory performance when compared against other nonlinear control schemes that one can consider for the dynamic model of robots with electropneumatic actuators (such as Lie algebra-based control, differential flatness theory-based control, nonlinear model-based predictive control, sliding-mode control and backstepping control), (ii) it achieves fast and accurate tracking of all reference setpoints, (iii) despite strong nonlinearities in the dynamic model of the robot, it keeps moderate the variations of the control inputs and (iv) unlike the aforementioned alternative control approaches, this paper’s method is the only one that achieves solution of the optimal control problem for electropneumatic robots.

The use of electropneumatic actuation in robots exhibits certain advantages. These can be the improved weight-to-power ratio, the lower mechanical impedance and the avoidance of overheating. At the same time, precise positioning and accurate execution of tasks by electropneumatic robots requires the application of elaborated nonlinear control methods. In this paper, a new nonlinear optimal control method has been developed for electropneumatically actuated robots and has been specifically applied to the dynamic model of a two-link robotic exoskeleton. The benefit from using this paper’s results in industrial and biomedical applications is apparent.

A comparison of the proposed nonlinear optimal (H-infinity) control method against other linear and nonlinear control schemes for electropneumatically actuated robots shows the following: (1) Unlike global linearization-based control approaches, such as Lie algebra-based control and differential flatness theory-based control, the optimal control approach does not rely on complicated transformations (diffeomorphisms) of the system’s state variables. Besides, the computed control inputs are applied directly on the initial nonlinear model of the electropneumatic robot and not on its linearized equivalent. The inverse transformations which are met in global linearization-based control are avoided and consequently one does not come against the related singularity problems. (2) Unlike model predictive control (MPC) and NMPC, the proposed control method is of proven global stability. It is known that MPC is a linear control approach that if applied to the nonlinear dynamics of the electropneumatic robot, the stability of the control loop will be lost. Besides, in NMPC the convergence of its iterative search for an optimum depends on initialization and parameter values selection and consequently the global stability of this control method cannot be always assured. (3) Unlike sliding-mode control and backstepping control, the proposed optimal control method does not require the state-space description of the system to be found in a specific form. About sliding-mode control, it is known that when the controlled system is not found in the input-output linearized form the definition of the sliding surface can be an intuitive procedure. About backstepping control, it is known that it cannot be directly applied to a dynamical system if the related state-space model is not found in the triangular (backstepping integral) form. (4) Unlike PID control, the proposed nonlinear optimal control method is of proven global stability, the selection of the controller’s parameters does not rely on a heuristic tuning procedure, and the stability of the control loop is assured in the case of changes of operating points. (5) Unlike multiple local models-based control, the nonlinear optimal control method uses only one linearization point and needs the solution of only one Riccati equation so as to compute the stabilizing feedback gains of the controller. Consequently, in terms of computation load the proposed control method for the electropneumatic actuator’s dynamics is much more efficient.

The purpose of the paper is to present an innovation-based new actuator/surface fault detection and isolation (FDI) method, which is sensitive to the changes in the innovation mean of the Kalman filter (KF) and the KF tuning method for the case of actuator/surface failure.

The multiple system noise scale factors (MSNSFs) are used in this method as the monitoring statistics. MSNSFs are determined to make it possible to perform the actuator/surface FDI operations simultaneously.

The introduced FDI algorithm can detect and isolate the loss of effectiveness type actuator/surface faults in real time. The proposed KF tuning method works effectively against actuator/surface fault. The actuator/surface fault detection, isolation and filter tuning are achieved by just using a simple modification over the conventional KF.

The MSNSF-based actuator/surface fault detection, isolation and filter tuning algorithms are investigated together for the first time. The actuator/surface FDI operations are performed simultaneously.

Soft actuators using pneumatic-chamber (PneuNet)-based designs have been of interest in the area of soft robotics with scope of application in the area of biomedical assistance and smart agriculture. Researchers have attempted to investigate multiple chambers in parallel to examine their deformation characteristics. However, there is a lacuna for investigation of the deformation characteristics of four parallel chambered soft actuators. The purpose of this study is to comprehensively investigate the different possible actuation scenarios and the resulting bending/deformation behaviours.

Therefore, in this study, a four-chambered PneuNet actuator is numerically investigated to evaluate the effects of pressurization scenarios and pressure levels on its performance, operating reaching and working volume.

The results of this study revealed that two-adjacent chamber equal pressurization and three-chamber pressurizations result in increased bending. However, two-opposite chamber pressurization reduces the bending angle with pressure levels in the lower pressure chamber. The maximum bending angle of 97° was achieved for single-chamber pressurization of 300 kPa. The two-adjacent chamber unequal pressurization can achieve a sweeping motion in the actuator along with bending. The working volume and reaching capability analysis revealed that the actuator can reach around 71% of the dimensional operating space.

The results provide fundamental guidance on the output nature of motion which can be obtained under different pressurization scenarios using the four-chambered design soft actuator, thereby making it a practical guide for implementation for useful applications.

The comprehensive pressurization scenarios and pressure level variations reported in this study will serve as fundamental operating guidelines for any practical implementation of the four-chambered PneuNet actuator.

The purpose of this paper is to design a soft robot for performing detection, by using a hybrid drive to reach the target point faster and enable the robot to perform the detection task at a relatively fast speed.

The soft robot is driven by a mixture of motors and pneumatic pressure, in which the pneumatic pressure is used to drive the soft actuator to bend and the motors to drive the soft robot forward. The careful design of the actuator is based on a finite element simulation using ABAQUS, which combines a constant curvature differential model and the D-H method to analyze the motion space of the soft actuator.

The soft robot’s ability to adapt to the environment and cross obstacles has been demonstrated by building prototypes and complex environments such as grass, gravel, sand and pipes.

This design can improve the speed and smoothness of the motion of the soft robot, while retaining the good environmental flexibility of the soft robot. And the soft robot has good environmental adaptability and the ability to cross obstacles. The soft robot proposed in this paper has broad prospects in fields such as pipeline inspection and field exploration.