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Summary: Guaranteeing prescribed transient and steady state performance (TSSP) for mechanical systems is of great significance to their motion control, motivating the prescribed performance control (PPC). This study investigates the PPC for uncertain underactuated systems. We consider time‐varying (possibly fast), bounded uncertainty including large mismatched portions, however the bound is unknown. The control design is implemented via constraint‐following, that is, rendering the system to follow a series of servo constraints. We hence impose the prescribed TSSP on the constraint‐following error. An approximation‐free adaptive robust PPC based on a state transformation technique is designed, achieving approximate constraint‐following and guaranteeing the prescribed TSSP to be satisfied. It employs an adaptive law to online estimate the unknown bounds for uncertainty compensation. It does not assume sufficiently small mismatched uncertainties, hence admitting large mismatched uncertainties. The stability of the controlled underactuated systems is sustained by rigorous proofs. By the proposed approach, the PPC of a planar vertical take‐off and landing aircraft is explored, which also illustrates the effectiveness of the approach. [ABSTRACT FROM AUTHOR]

There are various indicators, i.e., Relative Strength Index (RSI) [1] [2], Moving Average Convergence Divergence (MACD) [3] [4] [5] [6], Stochastic Oscillator [7] [8] applications, to determine market movements with buying and selling decisions in computational Finance, but they have drawbacks that induced discrepancies to match against the best trading times at fixed order-triggering boundaries and delay problems. For example, RSI [1] [2]'s 70 and 30 overbuy and oversell are fixed boundaries. Orders can only be triggered when RSI's value exceeds one of these boundaries, its computation only considers past market condition prompting indicators like RSI to trigger orders with delay. In this paper, we proposed a method to reduce these problems with advanced AI technologies to generate indicators' buy and sell signals in the best trading time. Recurrent Neural Network (RNN) [9] has outstanding performance to learn time-series data automatic with long-time sequences but its ordinary RNN units [10] [11] such as Long-Short-Term-Memory(LSTM)[12] are unable to decipher the relationships between time units called context. Hence, researchers have proposed an algorithm based on RNNs' Attention Mechanism [13] [14] allowing RNNs to learn information such as chaotic attributes [15] [16] [17] [18] and Quantum properties [19] [20] [21] contained in time sequences. Chaos Theory [15] [16] and Quantum Finance Theory (QFT) [22] are also proposed to simulate these two features (or attributes?). Quantum Price Level (QPL) [22] [23] is one of the well-formed QFT models to simulate all possible vibration levels to locate price. The system used in this paper consists of two components 1) neural network to predict future data and solve indicators lagging problem, and 2) fuzzy logic to solve fixed order-triggering boundaries problem. Its system design has two main parts 1) Chaotic HLCO Predictor consists of LSTM, Lee-Oscillator and attention mechanism to predict the High, Low, Close and Open, 2) QPL-based Fuzzy Logic Trading Strategy to receive the result and trigger trading signals. This new proposed model has obtained significant results in backtesting previous data and outperformed other traditional indicators to facilitate investment decisions when market changes constantly. Codes are available at https://github.com/JarvisLee0423/ Chaotic Quantum Finance AI Predicted Trading System. [ABSTRACT FROM AUTHOR]

High-voltage and efficient power converter topologies equipped with the simple and practical controller circuits are necessary, especially for integration between the low-power and low-voltage renewable energy sources (RESs) like the photovoltaic (PV) arrays and the grid. These converters can be used widely in electrical vehicles (EVs) or charging stations, aquatic, medical, transportation application and other cases. This study proposes a switched capacitor (SC)-based quadratic boost converter (QBC) structure that provides high-voltage gain at low duty cycles equipped with the fuzzy logic control (FLC) technique. The output gain of the proposed converter is higher than a second-order step-up converter or a conventional QB circuit thanks to the presented switched-capacitor topology and the manipulation of the switches in conventional QBC. By using the second switch to the conventional QBC, the voltage stress across the main power switch will decrease that enhance the reliability and long-life of the converter. Since the SC block acts as an intermediate layer between the QB and load through the capacitors and diodes of this block, the voltage and current stresses of the power switches and diodes on the QB side are less than stresses for semiconductors for classical QB and boost converter. In this study, the proposed QBC and controller system are analyzed mathematically in detail and in MATLAB/SIMULINK environment. A 200 W prototype was developed in the laboratory to validate the proposed converter and computerized analysis. Finally, the theoretical and experimental results were compared and verified. [ABSTRACT FROM AUTHOR]

In this paper, we investigate a class of nonlinear MIMO systems based on prescribed-time sliding mode control (PTSMC). In an effort to extend the concept of fixed-time theory with capability of handling more practical systems, we have developed a PTSMC based on the free-will arbitrary time (FWAT) principle of stability. We propose the FWAT sliding surfaces to improve the convergence of a nonlinear system, what is known as arbitrary convergence in control theory. According to the proposed sliding surface, the states of a system can reach the sliding surfaces (arbitrary reaching phase) within a given time interval and also can hit the origin within a predefined time (arbitrary sliding phase). Using this method, the overall stabilization time can be adjusted freely to suit the needs of the designer. Furthermore, this control method is capable of being implemented independent of any other system parameters. Lyapunov stability theory shows the stability of the proposed control scheme and the designed sliding surfaces. Finally, the efficiency of the proposed approach is demonstrated by performing on two well-known examples such that it verifies the arbitrary convergence of the designed sliding surfaces for various times in spite of revealing the designed control independency of any initial values. [ABSTRACT FROM AUTHOR]

This paper designs an adaptive fractional-order sliding mode controller for an inverted pendulum–cart system. The input force is determined to stabilize the system and adjust the cart position and the pendulum angle to zero. A hierarchical sliding mode control approach with novel fractional-order sliding surfaces, including a fractional-order integral term, an ordinary derivative term, and a proportional term, is chosen to attain this purpose. The control signal is determined to ensure the sliding condition. In order to improve the robustness of the proposed controller against uncertainties in the cart friction coefficient and the pendulum's viscous friction, the controller parameters are adapted according to an appropriate adaptation rule. The adaptation rule is attained using an appropriate Lyapunov-based approach. Numerical simulations confirm the feasibility and efficiency of the proposed control strategy. [ABSTRACT FROM AUTHOR]

This paper presents an adaptive nonparametric evolving fuzzy controller for uncertain nonlinear systems with dead zone. The unknown nonlinear- ities caused by the dead zone are approximated using a nonparametric data clouds-based evolving fuzzy systems (EFSs), based on which the controller is designed via the Backstepping procedure. The data clouds- based EFSs impose the local and global density as the learning schemes to adapt the structure of the controller using the information extracted from nonstationary data streams. The stable parameter adjustment laws with projection operator are derived under the Lyapunov theorem to update the parameters of the controller. To further reduce the in uence of the approximation errors brought by the data clouds-based approxima- tors, a sliding mode control term is designed to augment the controller. The stability of the proposed controller is proven under the Lyapunov synthesis, and its effectiveness is verified by the simulation results. [ABSTRACT FROM AUTHOR]

As a kind of fuel cells, solid oxide fuel cell (SOFC) has been an important research area for researchers. However, SOFC gives a challenging control problem because of their operating constraints, complex nonlinearity, slow dynamics, and load disturbance. In this article, a new enhanced model-free discrete-time adaptive terminal sliding-mode control (EMF-ATSMC) is proposed for the SOFC system with input constraints, aiming to regulate the output voltage under the load disturbance. The referred EMF-ATSMC controller is composed of three components: the pseudo-partial-derivative (PPD) estimator, the discrete-time adaptive terminal sliding-mode control, and the anti-windup compensator. First, an enhanced compact form of dynamic linearization data-driven modelling method is used to simplify the SOFC plant considering the load perturbation, and then, the PPD estimator is designed. The discrete-time adaptive terminal sliding-mode control via anti-windup compensator is developed to improve the control performance and guarantee the controlled system stability, wherein the designed anti-windup compensator is employed to eliminate the magnitude and rate saturations of control input. Moreover, the closed-loop system's stability with the proposed EMF-ATSMC controller is theoretically proved by using the Lyapunov method. Finally, simulation results are given to demonstrate that the proposed EMF-ATSMC controller has excellent dynamic performance and stronger robustness compared with other methods such as improved model-free adaptive constrained control (IMFACC), model-free adaptive control (MFAC), and PID controller. [ABSTRACT FROM AUTHOR]

This paper studies the adaptive limit cycle controller design for shaping stable output oscillations through creating stable limit cycles. For this purpose, a class of time-delay nonlinear systems with multiple time delays and external disturbances is considered. The desirable limit cycle is shaped in the first step by using an extended Lyapunov theorem for stability analysis of positive limit sets. The Lyapunov–Krasovskii theorem is also employed to handle the difficulties raised by multiple time delays. Besides, an adaptive approach is developed to deal with unknown but bounded external disturbances. Unlike the classic approaches, the upper bounds of disturbances are not required to be known in advance. The method is discussed for the second-order system, firstly and then, developed for higher-order systems by the recursive procedure of the backstepping technique. It will be shown that the closed-loop system is practically stable and the phase trajectories of the system converge to an arbitrarily small neighborhood of the target limit cycle. Simulation results are provided to show the effectiveness of the proposed approach. [ABSTRACT FROM AUTHOR]

This paper addresses a tracking control problem with prespecified accuracy for uncertain switching nonlinear systems under arbitrary switching with periodically time-varying parameters. To approximate the unknown nonlinear functions and unknown periodically time-varying parameters, the radial basis function neural network and Fourier series expansion are introduced, respectively. Compared with the previous results of unknown nonlinear switching system approximation, the upper bounds of the approximation errors are considered for the first time. And then, a new adaptive NN control scheme is constructed by using backstepping technique and common Lyapunov function theory. It can be proved that all the signals in the closed-loop system are semi-globally uniformly ultimately bounded and the tracking error converges to the prescribed neighborhood of zero. Two examples are provided to verify the feasibility and advantages of the proposed approach in this paper. [ABSTRACT FROM AUTHOR]

The double-pendulum (DP) phenomenon, effectuated by the fact that the payload configuration and the chain length between the hook and the payload are usually unknown, is a typical issue in actual cranes. This phenomenon is considered in the current study to enhance tracking accuracy and sway regulation for overhead cranes subject to perturbations and multiple frictions. A novel smooth super-twisting algorithm hybridized with the integral sliding mode control (ISMC) is proposed to solve the problems. The closed-loop system's finite time stability has been examined using a strict quadratic Lyapunov function. Compared to an existing modified super-twisting algorithm (MSTC), it has been shown that the proposed algorithm mitigates both the sliding surface overshoot and the initial peaking of the control effort that can be encountered using the MSTC algorithm. Furthermore, simulation experiments and error analysis show improved effectiveness of the proposed technology against the existing MSTC and the conventional ISMC technologies. The paper contribution primarily dwells on devising a novel structure of super-twisting algorithm that ensures the nonlinear perturbed DP overhead crane's desired performance. [ABSTRACT FROM AUTHOR]

In this paper, the finite-time synchronization between two delayed quaternion-valued neural networks (QVNNs) via the periodically intermittent feedback control is studied. Firstly, the finite-time synchronization problem is presented for the first time via the periodically intermittent control approach. Secondly, the upper bounds of the settling time for finite-time synchronization are estimated. Thirdly, a kind of novel controller, state feedback controller, which contains an integral term and delayed term, is proposed. Through these, the problem of finite-time synchronization has been solved very well. Finally, several new conditions ensuring finite-time synchronization of two delayed QVNNs are derived by establishing a new differential inequality and constructing a Lyapunov function. In the end, two numerical examples with simulations show the effectiveness of the derived results and the developed method. [ABSTRACT FROM AUTHOR]

The demand for high-precision motion control method for complex systems has increased in the recent decade. The significant challenge is to achieve robustness despite insufficient knowledge about the disturbances acting on a real-time system. Uncertainty and Disturbance Estimator (UDE) method is a vital approach that takes up the challenge, ensuring stability and robustness. This paper is dedicated to highlighting the research done in the field of UDE controller applied with other well-known control methods implemented on various linear and nonlinear systems. This work aims to control the position of pitch axis of the nonlinear aerodynamic system. The phase portrait analysis of the system has been done, which reveals the trajectory and existence of limit cycle. The obtained time responses are diverging, indicating the regions of instability. The novelty lies in the formulation of UDE based controller aimed to robustify the helicopter subsystem. Closed-loop stability is analyzed to validate the controller design. Simulation results for the pitch-axis control are demonstrated to display the efficacy of UDE-based control design against uncertainty and disturbances. The methodology's efficiency is further demonstrated by comparing the results of UDE control with α -filter with a well-known fuzzy control technique. [ABSTRACT FROM AUTHOR]

This research study aims to enhance the optimization accuracy of the two recently emerged metaheuristics of whale and sine–cosine optimizers by means of the balanced improvements in intensification and diversification phases of the algorithms provided by cellular automata (CA). Stagnation at the early phases of the iterations, which leads to entrapment in local optimum points in the search space, is one of the inherent drawbacks of the metaheuristic algorithms. As a favorable solution alternative to this problem, different types of cellular topologies are implemented into these two algorithms with a view to ameliorating their search mechanisms. Exploitation of the fertile areas in the search domain is maintained by the interaction between the topological neighbors, whereas the improved exploration is resulted from the smooth diffusion of the available population information among the structured neighbors. Numerical experiments have been carried out to assess the optimization performance of the proposed cellular-based algorithms. Optimization benchmark problems comprised of unimodal and multimodal test functions have been applied and numerical results have been compared with those found by some of the state-of-the-art literature optimizers including particle swarm optimization, differential evolution, artificial cooperative search and differential search. Cellular variants have been outperformed by the base algorithms for multimodal benchmark problems of Levy and Penalized1 functions. Then, the proposed cellular algorithms have been applied to two different parameter identification cases in order to test their efficiencies on real-world optimization problems. Extensive performance evaluations on different parameter optimization cases reveal that incorporating the CA concepts on these algorithms not only improves the optimization accuracy but also provides considerable robustness to acquired solutions. [ABSTRACT FROM AUTHOR]

The inverted cart-pendulum (ICP) is a nonlinear underactuated system, which dynamics are representative of many applications. Therefore, the development of ICP control laws is important since these laws are suitable to other systems. Indeed, many nonlinear control strategies have emerged from the control of the ICP. For these reasons, the ICP remains a canonical and fundamental benchmark problem in control theory and robotics that is of interest to the scientific community. Till now, the trial-and-error method is still widely applied for ICP controller tuning as well as the sequential tuning referring to tune the swing-up controller and thereafter, the stabilization controller. Therefore, the aim of this paper is to automate and facilitate the ICP control in one step. Thus, this paper proposes to holistically optimize ICP controllers. The holistic optimization is performed by a simplified Ant Colony Optimization method with a constrained Nelder–Mead algorithm (ACO-NM). Holistic optimization refers to a simultaneous tuning of the swing-up, stabilization and switching mode parameters. A new cost function is designed to minimize swing-up time, achieve high stabilization performance and consider system constraints. The holistic approach optimizes four controller structures, which include controllers that have never been tuned by a specific method besides by the trial-and-error method. Simulation results on a ICP nonlinear model show that ACO-NM in the holistic approach is effective compared to other algorithms. In addition, contrary to the majority of work on the subject, all the optimized controllers are validated experimentally. The simulation and experimental results obtained confirm that the holistic approach is an efficient optimization tool and specifically responds to the need of optimization technique for the potential-well controller structure and for the Q [diagonal of the matrix and the full matrix] in the linear–quadratic regulator (LQR) technique. Moreover, ICP experimental response analysis demonstrates that using the full Q provides greater experimental stabilization performance than using its diagonal terms in the LQR technique. [ABSTRACT FROM AUTHOR]

Summary: This paper studies on generating periodic behaviors through shaping stable limit cycles in multiple‐input‐multiple‐output nonlinear systems. For this purpose, first, limit cycles are shaped with respect to the desired sustained oscillations of the system's outputs. Then, the Lyapunov analyses, which are appropriate for stability analysis of invariant sets, are employed to design the control law and conclude the asymptotic convergence toward the predefined limit cycles. The problem is studied in two cases. In the first case, some assumptions in the mathematical model are assumed that leads to simplification in the design procedure. In the second case, the design procedure is discussed in more general cases. Finally, the validity and performance of the proposed method for shaping limit cycles with different geometric shapes are illustrated by computer simulations for practical and numerical examples. [ABSTRACT FROM AUTHOR]

This paper focuses on the limit cycle control of uncertain nonlinear systems in the presence of both matched and unmatched uncertainties. For this purpose, first, a virtual nonlinear system is constructed which has the desired limit cycle in its phase trajectories. The Lyapunov stability theorem for positive limit sets is utilized to confirm the stability of the created limit cycle in the virtual system. Next, by using a modified nonsingular terminal sliding mode control method, a robust controller is designed to synchronize the trajectories of the actual nonlinear system with the corresponding virtual one in a finite time. It is assumed that the actual system suffers from both matched and unmatched uncertainties and/or unknown external disturbances. A nonlinear terminal sliding surface is designed with the aim of a finite-time disturbance observer to tackle these unknown terms. The finite-time Lyapunov stability theorem is utilized to confirm the stability and robustness of the designed control law. Through simulation results, the finite-time stabilization of the synchronization errors and appropriate performance of the proposed control law are verified. [ABSTRACT FROM AUTHOR]

This paper presents a continuous control strategy based on the differential evolution (DE) algorithm for a planar four-link underactuated manipulator with a passive first joint to realize its position-posture control objective. First, we obtain the coupling equation in integral form between the angle of the passive link and the states (angles and angular velocities) of three active links according to the angular velocity constraint of the system. Then, according to this coupling equation, we construct a Lyapunov function only based on the control targets of three active links, and use the Lyapunov function to design the PD controllers. In addition, these general PD controllers are modified to be the step PD controllers to overcome the sudden change in the initial torques. Next, we use the DE algorithm to optimize the target angles of all links and the design parameters of the step PD controllers, which ensures that the angle of the passive link converges to its target angle when the angles of three active links converge to their target angles. Finally, simulation results demonstrate the effectiveness of the proposed control strategy. [ABSTRACT FROM AUTHOR]

The movement of the aircraft pitch is very important to ensure the passengers and crews are in intrinsically safe and the aircraft achieves its maximum stability.The objective of this study is to provide a solution to the control system that features particularly on the pitch angle motion of aircraft systemin order to have a comfort boarding. Three controllers were developed in these projects which wereproportional integral derivative (PID), fuzzy logic controller (FLC), and linear quadratic regulator (LQR) controllers. These controllers will help improving the pitch angle and achievingthe target reference. By improving the pitch motion angle, the flight will be stabilized and in steady cruise (no jerking effect), hence provides all the passengers withthe comfort zone. Simulation results have been done and analyzed using Matlab software. The simulation results demonstrated LQR and FLC were better than PID in the pitch motion system due to the small error performance. In addition, withstrong external disturbances, a single controller is unable to control the system, thus, the combination of PID and LQR managed to stabilize the aircraft. [ABSTRACT FROM AUTHOR]

An output feedback observer-based dynamic surface controller is presented for attitude tracking problem of the quadrotor unmanned aerial vehicle, which is subject to measurement noise and external disturbances. The dynamics model of the quadrotor unmanned aerial vehicle is firstly introduced with the quaternion representation. Subsequently, a nonlinear augmented observer is introduced for simultaneously estimating the unavailable states and uncertain disturbances from the measurement of system output. The output feedback controller based on the nonlinear augmented observer is designed with the dynamic surface control technique. The Lyapunov stability analysis shows that the attitude tracking performance is ensured and all signals of the closed-loop system remain bounded. Finally, simulative and experimental results are carried out to illustrate, compared with other observer-based controller, the effectiveness of the proposed method is better. [ABSTRACT FROM AUTHOR]

This paper addresses the robust attitude control problem of miniature quadrotors. A simplified linear dynamical model is obtained for each attitude angle, whereas nonlinear dynamics, interaxis coupling, parameter perturbations, and external disturbances are considered as uncertainties. For each channel, a linear time-invariant and decoupled robust controller are proposed based on a linear reduced-order observer and a robust compensator. The observer is applied to estimate the angular velocities, and the robust compensator is introduced for reducing the effects of uncertainties. It is proven that the estimation errors of angular velocities and angular tracking errors can converge to the given neighborhood of the origin in a finite time. Experimental results on the miniature quadrotor are presented to verify the effectiveness of the proposed control approach. Copyright © 2015 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

In this article, we present a preliminary analysis of a heavy-lift airship carrying a payload through a cable-driven parallel robot. With unlimited access to isolated locations around the globe, heavy-lift airship enables affordable and safe delivery of heavy cargo thanks to its vertical takeoff and landing capabilities. By considering the airship and the cable-driven parallel robot as a combined system, the kinematic and dynamic models are developed. The choice of the proposed decentralized control structure is justified by the weak coupling of the two subsystems (i.e. airship and cable-driven parallel robot) which makes it possible to control the above two subsystems independently. A robust sliding mode control, capable of auto-piloting and controlling the airship, is developed. Furthermore, an inverse dynamic controller is applied to the cable-driven parallel robot in order to ensure loading and unloading phase. The feature of the proposed control system is that the coupled dynamics between the airship and the cable-driven parallel robot are explicitly incorporated into control system design, without any simplifying assumption. Numerical simulation results are presented and a stability analysis is provided to confirm the accuracy of our derivations. [ABSTRACT FROM AUTHOR]