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Liquid crystal elastomers (LCEs) offer promising prospect in applications such as soft robot actuators due to the fact that they can be chemically doped to have photo-responsive deformation characteristics . With the purpose of accurate control of LCE actuators in soft robot applications, the establishment of a model which quantitatively describes the deformation characteristics of LCE becomes essential. However, current models for LCE are very preliminary, which restricts the implementation of LCE actuators. This paper develops a model to describe the deformation of LCE actuators. First, the deformation process is discussed, which is in nature the macroscopic shape change corresponding to the phase change of LCE. Then, the relationship between the deformation and the temperature of LCE is established according to thermodynamic analysis on the free energy, and the phase transition process. Unknown parameters are determined through parameter identification with experimental data based on the non-linear least-squares method. This model has the advantage that it quantitatively describes the deformation characteristics of LCE without the aid of numerical simulation, and it reflects the physical nature of the deformation of LCE. This model lays a basis for the accurate control of the LCE actuators, which leads to future photo-responsive soft robot applications.

Dielectric Elastomer Actuator (DEA) shows the complex characteristics such as the inherent nonlinearity, intricate electromechanical coupling, time-dependent viscoelastic behavior, etc., which make...

Planar underactuated mechanical systems are unaffected by gravity and therefore widely used in aerospace robots and underwater vehicles. However, the stable control is quite difficult since any position that the system can reach is its equilibrium point where it is linearly uncontrollable. In this paper, considering a planar three-link passive-active-active underactuated manipulator, a novel control approach using intelligent optimization is developed for its asymptotic stability at a target position. In the first stage, we develop controllers for stabilizing one active link at its target angle obtained by inverse kinematic method and the other two links at their transitional angles obtained by the Genetic Algorithm (GA), where the angles need to satisfy the angle constraint. Meanwhile, the GA is also utilized to optimize controllers’ parameters to ensure this stable control. Then in next stage, under the control of the angle constraint, the remaining two links are moved to the target angles simultaneously. Besides, we also improve the optimization criterion to include the control error, control time and input torque, thereby selecting better parameters of the controllers to obtain better control performance. Four simulations are implemented to prove the validity and feasibility of the proposed control and optimization algorithm.

This paper presents a new control strategy based on Fourier transformation and intelligent optimization for a planar Pendubot with a passive second link, which can be treated as a second-order nonholonomic system whose control has been an open and challenging issue. A controller acting within a time corresponding to the frequency of its fundamental harmonic term is designed to realize the system control objective, which is to move the system from its initial position to the target position. By employing Fourier transformation, a general expression of the controller composed of a constant term and harmonic terms is obtained. Next, the constant term is obtained by the angular momentum theorem, and the particle swarm optimization algorithm is employed to obtain the harmonic terms of the controller. A feedback control strategy based on a nonlinear disturbance observer is then applied to overcome the uncertainties/disturbances in the system. Finally, simulation results prove the validity of this control method.

This paper considers the problem of distributed leader-follower formation control for nonholonomic mobile robots only using local interactions among the robots. First, a distributed estimation strategy is presented for each follower robot to estimate the leader’s state. Then the dynamic equations of the formation tracking errors are formulated and a distributed formation control scheme is designed, which yields globally uniformly ultimately bounded stability for the closed-loop systems without requiring persistent excitation conditions. Finally, a simulation example demonstrates the effectiveness of the proposed approach.

This paper proposes a dynamic model for dielectric elastomer actuators (DEAs) based on the long-short term memory (LSTM) deep neural network. The fabrication of the DEA and the framework of the experimental platform are introduced firstly. The behaviors of the DEA are analyzed through several sets of experiments, which shows the DEA has obvious memory behavior (i.e., the hysteresis behavior and creep behavior), where the hysteresis behavior is a symmetry and rate-dependence. Considering that the traditional neural network is difficult to describe the memory property, the LSTM deep neural network is constructed as the dynamic model of the DEA. Then, such neural network is trained according to the experimental data. Finally, the comparation results of the experimental data and the model output verify the effectiveness as well as the generalization ability of the dynamic model.

With the desirable physical performances of high strain and low stiffness, a novel soft sensor based on the dielectric elastomer (DE) material shows great potential in the wearable devices and soft robots. Since the DE material has the complex nonlinear characteristics and the electromechanical coupling, most early works only devoted to the sensor structure design. However, the studies on the mathematical modeling of the DE sensor (DES) are insufficient. In this paper, a mathematical model of the soft sensor based on the DE material is built to describe its sensing property. Because the DES is used to measure the displacement and force simultaneously, it can serve as a soft force and displacement sensor (SFDS). Based on the experimental data, the differential evolution algorithm is employed to identify the undetermined parameters of the developed mathematical model of the SFDS. The result of model validation demonstrates the effectiveness of the model.

With desirable physical performances of impressive actuation strain, high energy density, high degree of electromechanical coupling and high mechanical compliance, dielectric elastomer actuators (DEAs) are widely employed to actuate the soft robots. However, there are many challenges to establish the dynamic models for DEAs, such as their inherent nonlinearity, complex electromechanical coupling, and time-dependent viscoelastic behavior. Moreover, most previous studies concentrated on the planar DEAs, but the studies on DEAs with some other functional shapes are insufficient. In this paper, by investigating a conical DEA with the material of polydimethylsiloxane and considering the influence of inertia, we propose a dynamic model based on the principles of nonequilibrium thermodynamics. This dynamic model can describe the complex motion characteristics of the conical DEA. Based on the experimental data, the differential evolution algorithm is employed to identify the undetermined parameters of the developed dynamic model. The result of the model validation demonstrates the effectiveness of the model.

In this paper, taking the advantage of the properties of Prandtl-Ishlinskii (PI) hysteresis model, an adaptive controller is developed for actuators dominated by unknown hysteresis nonlinearities, which are used in the dynamic systems with the uncertain parameters, where the cascaded plant can be expressed as parameterized form. By employing the construction of the inverse PI model and the adaptive control techniques, the new controller can guarantee the stability and good tracking performance with unknown hysteresis actuator, uncertain system dynamics, and the immeasurable actuator outputs. The simulation results validate the proposed controller and illustrate the performance.

A one-stage control strategy is proposed for planar underactuated manipulators, which have a passive link not located at the first link. The control objective is to control the end-effector from an initial position to a given target position. To achieve the control objective, a general form of controllers for the active links is proposed. To ensure that the system can be stabilized at its target state, parameters of the proposed controllers are calculated using the differential evolution algorithm. Simulations on specific systems are performed to show the validity of the proposed control strategy.

This paper investigates dynamic balance optimization and control of quadruped robots with compliant/flexible joints under perturbing external forces. First, we formulate a constrained dynamic model of compliant/flexible joints for quadruped robots and a reduced-order dynamic model is developed considering the robot interaction with the environment through multiple contacts. A dynamic force distribution approach based on quadratic objective function is proposed for evaluating the optimal contact forces to cope with the external wrench, and fuzzy-based adaptive control of compliant/flexible joints for quadruped robots is proposed to suppress uncertainties in the dynamics of the robot and actuators. The dynamic surface control approaches and fuzzy learning algorithms are combined in the proposed framework. All the signals of the closed-loop system have proven to be uniformly ultimately bounded through Lyapunov synthesis. Simulation experiments were performed for a quadruped robot with compliant/flexible joints. The benefits of its tracking accuracy and robustness indicate that the proposed framework is promising for the robots with payload uncertainties and external disturbances.

The fracture-behaviors of two Ti-Al-Sn-Zr-Mo-Nb-W-Si alloys with different slow-diffusing &beta, stabilizing elements (Mo, W) were investigated through in-situ tensile testing at 650 &deg, C via scanning electron microscopy. These alloys have two phases: the &alpha, phase with hcp-structure (a = 0.295 nm, c = 0.468 nm) and the &beta, phase with bcc-structure (a = 0.332 nm). Three-dimensional atom probe (3DAP) results show that Mo and W mainly dissolve in the &beta, phase, and they tend to cluster near the &alpha, /&beta, phase boundary. Adding more slow-diffusing &beta, stabilizing elements can improve the ultimate tensile strength and elongation of the alloy at 650 &deg, C. During tensile deformation at 650 &deg, C, microvoids mainly initiate at &alpha, interfaces. With increases in the contents of Mo and W, the &beta, phase content increases and the average phase size decreases, which together have excellent accommodative deformation capability and will inhibit the microvoids&rsquo, nucleation along the interface. In addition, the segregation of Mo and W near the &alpha, interface can reduce the diffusion coefficient of the interface and inhibit the growth of microvoids along the interface, which are both helpful to improve the ultimate tensile strength and plasticity.

Robot manipulator control considering parameter uncertainty and velocity estimation is address in this paper. An adaptive controller using state estimation feedback is provided in this paper, which can adapt the dynamic parameters and estimate the velocity with imprecise system model simultaneously. The stability of the proposed controller is discussed and a 2-links robot manipulator is adopted as an example to illustrate and validate the provided control scheme. In the simulation, all the observer performance, parameter adaptation, and the trajectory tracking are validated.

The paper studies the control design of an exoskeleton robot based on electromyography (EMG). An EMG-based motion detection method is proposed to trigger the rehabilitation assistance according to user intention. An adaptive control scheme that compensates for the exoskeleton's dynamics is employed, and it is able to provide assistance tailored to the human user, who is supposed to participate actively in the training process. The experiment results verify the effectiveness of the control method developed in this paper.