Explore the vast range of titles available.

Fractional-order calculus and derivative is extended from integral-order calculus and derivative. This paper investigates a nonlinear robust control problem using fractional order and operator theory. In order to improve the tracking performance and antidisturbance ability, operator- and fractional-order-based nonlinear robust control for the spiral counter-flow heat exchanger described by the parallel fractional-order model (PFOM) is proposed. The parallel fractional-order model for the spiral counter-flow heat exchanger was identified by particle swarm optimization (PSO) and the parameters of a fractional-order PID (FOPID) controller were optimized by the PSO. First, the parallel fractional-order mathematical model for a spiral counter-flow heat exchanger plant was identified by PSO. Second, a fractional-order PID controller and operator controller for the spiral heat exchanger were designed under the identified parallel fractional-order mathematical model. Third, the parameters of the operator and fractional-order PID were optimized by PSO. Then, tracking and antidisturbance performance of the control system were analyzed. Finally, comparisons of two control schemes were performed, and the effectiveness illustrated.

Linear sliders are linear actuators using linear motors. It is used in many applications, such as factory lines and linear motor cars. In recent years, the demand for smaller semiconductor devices has been increasing due to the proliferation of smartphones. High-precision positioning of linear motors is needed because manufacturing semiconductor devices uses the stage with linear motors. However, linear motors have nonlinearity due to the position dependence of interlinkage flux. It affects precise positioning. In this study, the nonlinear characteristics due to the position dependence of the flux are expressed as a mathematical model by using a distributed constant magnetic circuit. A method compensating it using an operator-based feedback controller with the obtained mathematical model is proposed. The effectiveness of the proposed method is confirmed by simulating and experimenting with the reference following disturbance elimination.

Recently, the studies of soft actuators have been getting increased attention among various fields. Soft actuators are very safe for fragile objects and have an affinity to humans because they are composed of flexible materials. A miniature flexible actuator is a kind of pneumatically driven soft actuator. It has a bellowed shape and asymmetrical structure. This shape can generate a curling motion in two ways under positive and negative pressures with only one air tube. In the previous article, a control system using adaptive λ-tracking control was proposed. This control gain can become too large as time tends to infinity because the adaptive law exhibits a non-decreasing gain. To solve this problem, the funnel control method is proposed. The adaptive gain of this method not only increases but also decreases; however, the design scheme of the boundary function which is needed to decide on adaptive gain is not proposed here. In this article, an operator-based nonlinear control system’s design and the design scheme of the boundary function using an observer are proposed. Then, the effectiveness of the proposed method is verified by a simulation and an experiment.

The number of actuators of an underactuated robot is less than its degree of freedom. In other words, underactuated robots can be designed with fewer actuators than fully actuated ones. Although an underactuated robot is more complex than a fully actuated robot, it has many advantages, such as energy, material, and space saving. Therefore, it has high research value in both control theory and practical applications. Swing-up is a mechanism with two links, which mimics a gymnast performing a horizontal bar movement. Over the past few decades, many sufficiently robust control techniques have been developed for a fully actuated robot but almost none of them can be directly applicable to an underactuated robot system. The reason is that such control techniques require certain assumptions that are valid only for fully actuated robot systems but not for underactuated ones. In this paper, a control system design method for underactuated robots based on operator theory and an isomorphism scheme is first proposed. Bezout identity is designed using isomorphism. The effectiveness of the design method is confirmed by simulation. The simulation results show that the performances, such as robust stability and response time, of an underactuated robot control system are improved.

The flexible arm easily vibrates due to its thin structural characteristics, which affect the operation accuracy, so reducing the vibration of the flexible arm is a significant issue. Smart materials are very widely used in the research topic of vibration suppression. Considering the hysteresis characteristic of the smart materials, based on previous simulation research, this paper proposes an experimental system design of nonlinear vibration control by using the interactive actuation from shape memory alloy (SMA) for a flexible arm. The experiment system was an interactive actuator–sensor–controller combination. The vibration suppression strategy was integrated with an operator-based vibration controller, a designed integral compensator and the designed n-times feedback loop. In detail, a nonlinear vibration controller based on operator theory was designed to guarantee the robust stability of the flexible arm. An integral compensator based on an estimation mechanism was designed to optimally reduce the displacement of the flexible arm. Obtaining the desired tracking performance of the flexible arm was a further step, by increasing the n-times feedback loop. From the three experimental cases, when the vibration controller was integrated with the designed integral compensator, the vibration displacement of the flexible arm was much reduced compared to that without the integral compensator. Increasing the number of n-times feedback loops improves the tracking performance. The desired vibration control performance can be satisfied when n tends to infinity. The conventional PD controller stabilizes the vibration displacement after the 7th vibration waveform, while the vibration displacement approaches zero after the 4th vibration waveform using the proposed vibration control method, which is proved to be faster and more effective in controlling the flexible arm’s vibration. The experimental cases verify the effectiveness of the proposed interactive actuation vibration control approach. It is observed from the experimental results that the vibration displacement of the flexible arm becomes almost zero within less time and with lower input power, compared with a traditional controller.

In a nonlinear control system, hysteresis exists usually as common characteristics. In addition, external output disturbances like modelling error, machine friction and so on also occur frequently. Both of them are considered to cause instability and unsatisfactory performance. In this paper, a practical nonlinear control system design is proposed so as to achieve the simultaneous control of input hysteresis and output disturbance. The system is based on RCF (right coprime factorization theory). Additionally, the proposed design has been applied to a soft robotic finger system and the results of simulations and practical experiments are exhibited, which show the effectiveness of the proposed system.

Currently, machine learning (ML) methods provide a practical approach to model complex systems. Unlike purely analytical models, ML methods can describe the uncertainties (e.g., hysteresis, temperature effects) that are difficult to deal with, potentially yielding higher-precision dynamics by a learning plant given a high-volume dataset. However, employing learning plants that lack explicit mathematical representations in real-time control remains challenging, namely, the model can be conversely looked at as a mapping from input data to output, and it is difficult to represent the corresponding time relationships in real applications. Hence, an ML and operator-based nonlinear control design is proposed in this paper. In this new framework, the bounded input/output spaces of the learning plant are addressed rather than mathematical dynamic formulation, which is realized by robust right coprime factorization (RRCF). While the stabilized learning plant is explored by RRCF, the desired tracking performance is also considered by an operator-based nonlinear internal model control (IMC) design. Eventually, practical application on a soft robotic finger system is conducted, which indicates the better performance of using the controlled learning plant and the feasibility of the proposed framework.

In this paper, an operator-based voltage control method for TENGs is investigated, achieving output voltage tracking without compensators and uncertainty suppression using robust right coprime factorization. Initially, a comprehensive simulation-capable circuit model for TENGs is developed, integrating their open-circuit voltage and variable capacitance characteristics. This model is implemented to simulate the behavior of TENGs with a rectifier bridge and capacitive load. To address the high-voltage, low-current pulsating nature of TENG outputs, a storage capacitor switching model is designed to effectively transfer the pulsating energy. This switching model is directly connected to a buck converter and operates under a unified control strategy. A complete TENG power management system was established based on this model, incorporating an operator theory-based control strategy. This strategy ensures steady output voltage under varying load conditions without using compensators, thereby reducing disturbances. Simulation results validate the feasibility of the proposed TENG system and the efficacy of the control strategy, providing a robust framework for optimizing TENG energy harvesting and management systems with significant potential for practical applications.