Stabilizer design for an under-actuated autonomous underwater vehicle in a descriptor model under unknown time delay and uncertainty

This paper focuses on autonomous underwater vehicle (AUV) stabilization in the nonlinear descriptor model, as well as some AUV limitations such as model uncertainty, singularity, saturation constraint, and time delay. The capability of the descriptor model to show the real model is more reasonable than the standard state-space model. Based on the constructed Lyapunov function method and applying the bilinear matrix inequalities technique, all of the constraints are handled by introducing the new theorem. This theorem aims to design a state feedback with the intent that the closed-loop system be admissible. Here, the results are less conservative than other approaches. This issue has not yet been fully addressed in the literature, especially on AUVs. Theorem achievement is implemented on new AUV descriptor model that is obtained and introduced here. This method covers both neutral and descriptor systems. Also, it can be generalized and applied to conventional AUVs or similar dynamics. Examples and simulation results illustrate the effectiveness of the proposed approach.

Formation Control of Unmanned Vessels with Saturation Constraint and Extended State Observation

This paper addressed the formation control problem of surface unmanned vessels with model uncertainty, parameter perturbation, and unknown environmental disturbances. A formation control method based on the control force saturation constraint and the extended state observer (ESO) was proposed. Compared with the control methods which only consider the disturbances from external environment, the method proposed in this paper took model uncertainties, parameter perturbation, and external environment disturbances as the compound disturbances, and the ESO was used to estimate and compensate for the disturbances, which improved the anti-disturbance performance of the controller. The formation controller was designed with the virtual leader strategy, and backstepping technique was designed with saturation constraint (SC) function to avoid the lack of force of the actuator. The stability of the closed-loop system was analyzed with the Lyapunov method, and it was proved that the whole system is uniformly and ultimately bounded. The tracking error can converge to arbitrarily small by choosing reasonable controller parameters. The comparison and analysis of simulation experiments showed that the controller designed in this paper had strong anti-disturbance and anti-saturation performance to the compound disturbances of vessels and can effectively complete the formation control.

Basic Power Inductor Design

<p>A basic procedure for designing a power inductor is presented. Many papers and textbook chapters offer more sophisticated methods, but it is harder to find a clear outline of a basic design process. Studying and practicing a basic design process is useful for beginners to understand the fundamental tradeoffs in design and to build intuition. For more advanced work, the basic design process is useful as it avoids relying on assumptions that might not be valid with, for example, high-frequency loss effects that are ignored in the development of some more sophisticated methods, or that constrain other methods to narrow, specific cases.</p> <p>Two options are outlined: starting with a saturation constraint, and then checking the core/winding loss balance; or, starting by optimizing the core/winding loss balance, and then checking the saturation constraint.</p>

Basic Power Inductor Design

<p>A basic procedure for designing a power inductor is presented. Many papers and textbook chapters offer more sophisticated methods, but it is harder to find a clear outline of a basic design process. Studying and practicing a basic design process is useful for beginners to understand the fundamental tradeoffs in design and to build intuition. For more advanced work, the basic design process is useful as it avoids relying on assumptions that might not be valid with, for example, high-frequency loss effects that are ignored in the development of some more sophisticated methods, or that constrain other methods to narrow, specific cases.</p> <p>Two options are outlined: starting with a saturation constraint, and then checking the core/winding loss balance; or, starting by optimizing the core/winding loss balance, and then checking the saturation constraint.</p>

Lower limb movement intention recognition for rehabilitation robot aided with projected recurrent neural network

For the lower limb rehabilitation robot, how to better realize intention recognition is the key issue in the practical application. Recognition of the patient’s movement intention is a challenging research work, which needs to be studied from the shallow to the deep. Specifically, it is necessary to ensure that the movement intention of the normal person can be accurately recognized, and then improve the model to realize the recognition of the movement intention of the patients. Therefore, before studying the patient’s movement intention, it is essential to consider the normal person first, which is also for safety considerations. In recent years, a new Hill-based muscle model has been demonstrated to be capable of directly estimating the joint angle intention in an open-loop form. On this basis, by introducing a recurrent neural network (RNN), the whole prediction process can achieve more accuracy in a closed-loop form. However, for the traditional RNN algorithms, the activation function must be convex, which brings some limitations to the solution of practical problems. Especially, when the convergence speed of the traditional RNN model is limited in the practical applications, as the error continues to decrease, the convergence performance of the traditional RNN model will be greatly affected. To this end, a projected recurrent neural network (PRNN) model is proposed, which relaxes the condition of the convex function and can be used in the saturation constraint case. In addition, the corresponding theoretical proof is given, and the PRNN method with saturation constraint has been successfully applied in the experiment of intention recognition of lower limb movement compared with the traditional RNN model.