Full Controller Research Articles

Exploring the Psychological Effects and Physical Exertion of Using Different Movement Interactions in Casual Exergames That Promote Active Microbreaks: Quasi-Experimental Study.

Prolonged sedentary behavior, such as sitting or reclining, has consistently been identified as a stand-alone risk factor for heightened cardiometabolic risk and overall mortality. Conversely, interrupting sedentary periods by incorporating short, active microbreaks has been shown to mitigate the negative effects of sedentary behavior. Casual exergames, which mix elements of casual gaming with physical activity, are one prospective intervention to reduce sedentary behavior because they require physical exertion. Casual exergames have shown promise in fostering emotional and physical advantages when played in specific circumstances. However, little research exists on how different types of movement interactions impact the psychological effects as well as the physical exertion of playing casual exergames. The primary aim of this work was to explore the psychological effects and physical exertion of playing casual exergames lasting 2 minutes. More precisely, the investigation focused on comparing upper body and full body movement interactions. In addition, the work examined variations in body positions, considering both standing and seated positions during upper body movement interactions. Two casual exergames were developed and investigated through 2 quasi-experimental studies. In study 1, we investigated how players' perceptions of control, exertion, and immersion were affected by using upper body as opposed to full body exergame controllers when playing casual exergames. In study 2, we investigated differences in positive affect, performance, enjoyment, and exertion when playing casual exergames with upper body movement interactions in seated and standing positions. Study 1 showed that perceived control was significantly higher for upper body movement interactions than for full body movement interactions (P=.04), but there were no significant differences regarding perceived exertion (P=.15) or immersion (P=.66). Study 2 showed that positive affect increased significantly for both standing (P=.003) and seated (P=.001) gameplay. The participants in the standing gameplay group showed slightly higher actual exertion; however, there were no differences between the groups in terms of positive affect, perceived exertion, enjoyment, or performance. Casual exergames controlled by upper body movement interactions in seated gameplay can produce similar psychological effects and physical exertion as upper body movement interactions in standing gameplay and full body movement interactions. Therefore, upper body and seated casual exergames should not be overlooked as a suitable microbreak activity.

Adaptive Reactive Synthesis for LTL and LTLf Modulo Theories

Reactive synthesis is the process of generate correct con- trollers from temporal logic specifications. Typically, synthesis is restricted to Boolean specifications in LTL. Recently, a Boolean abstraction technique allows to translate LTLT specifications that contain literals in theories into equi-realizable LTL specifications, but no full synthesis procedure exists yet. In synthesis modulo theories, the system receives valuations of environment variables (from a first-order theory T ) and outputs valuations of system variables from T . In this paper, we address how to syntheize a full controller using a combination of the static Boolean controller obtained from the Booleanized LTL specification together with on-the-fly queries to a solver that produces models of satisfiable existential T formulae. This is the first synthesis method for LTL modulo theories. Additionally, our method can produce adaptive responses which increases explainability and can improve runtime properties like performance. Our approach is applicable to both LTL modulo theories and LTLf modulo theories.

Adaptive Active Disturbance Rejection Control for Vehicle Steer-by-Wire under Communication Time Delays

In this paper, an adaptive active disturbance rejection control is newly designed for precise angular steering position tracking of the uncertain and nonlinear SBW system with time delay communications. The proposed adaptive active disturbance rejection control comprises the following two elements: (1) An adaptive extended state observer and (2) an adaptive state error feedback controller. The adaptive extended state observer with adaptive gains is employed for estimating the unmeasured velocity, acceleration, and compound disturbance which consists of system parameter uncertainties, nonlinearities, exterior disturbances, and time delay in which the observer gains are dynamically adjusted based on the estimation error to enhance estimation performances. Based on the accurate estimations of the adaptive extended state observer, the proposed adaptive full state error feedback controller is equipped with variable gains driven by the tracking error to develop control precision. The integration of the advantages of the adaptive extended state observer and the adaptive full state error feedback controller can improve the dynamic transient and static steady-state effectiveness, respectively. To assess the superior performance of the proposed adaptive active disturbance rejection control, a comparative analysis is conducted between the proposed control scheme and the classical active disturbance rejection control in two different cases. It is worth noting that the active disturbance rejection control serves as a benchmark for evaluating the performance of the proposed control approach. The results from the comparison studies executing two simulated cases validate the superiority of the suggested control, in which estimation, tracking response rate, and steering angle precision are greatly improved by the scheme proposed in this article.

DC-link Voltage Control Using Battery-side Controller in a Hybrid System

This work aims to model the PV-Battery hybrid system as well as design a controller used to stabilize the voltage at the DC-link for the load. It is intended to make the voltage between the battery and PV system stable, or it can be said that the voltage at the load becomes stable. The input system used is battery current and PV current is considered as a disturbance because of its characteristics that cannot be controlled when generating maximum power. Therefore, a full order state feedback controller with integrator is designed to reduce the steady state error. In addition, an algorithm is needed to estimate the PV current and at the same time reduce sensor utilization. This work utilizes Disturbance Observer to estimate these parameters as well as disturbance rejection. To verify the proposed system, there are three scenarios. The first scenario tests the system with constant PV load and current. The second scenario tests the system with varying PV current, and finally tests the system with varying load and current. From the scenarios, the system performed well with output voltage RMSE values equal to 0.003 in the first scenario, 0.4 in the second scenario, and 0.481 in the third scenario.

Full envelope nonlinear flight controller design for a novel electric VTOL (eVTOL) air taxi

AbstractOn-demand urban air transportation gains popularity in recent years with the introduction of the electric VTOL (eVTOL) aircraft concept. There is an emerging interest in short/medium range eVTOL air taxi considering the critical advantages of electric propulsion (i.e. low noise and carbon emission). Using several electric propulsion systems (distributed electric propulsion (DEP)) has further advantages such as improved redundancy. However, flight controller design becomes more challenging due to highly over-actuated and coupled dynamics. This study defines and resolves flight control problems of a novel DEP eVTOL air taxi. The aircraft has a fixed-wing surface to have aerodynamically efficient cruise flight, and uses only tilting electric propulsion units to achieve full envelope flight control via pure thrust vector control. The aircraft does not have conventional control surfaces such as aileron, rudder or elevator. Using pure thrust vector control has some design benefits, but the control problem becomes more challenging due to the over-actuated and highly coupled dynamics (especially in transition flight). A preliminary flight dynamics model is obtained considering the dominant effects at hover and high-speed forward flight. Hover and forward flight models are blended to simulate the transition dynamics. Two central challenges regarding the flight control are significant nonlinearities in aircraft dynamics during the transition and proper allocation of the thrust vector control specifically in limited control authority (actuator saturation). The former challenge is resolved via designing a sensor-based incremental nonlinear dynamic inversion (INDI) controller to have a single/unified controller covering the wide flight envelope. For the latter one, an optimisation-based control allocation (CA) approach is integrated into the INDI controller. CA requires special attention due to the pure thrust vector control’s highly coupled dynamics. The controller shows satisfactory performance and disturbance rejection characteristics. Moreover, the CA plays a vital role in guaranteeing stable flight in case of severe actuator saturation.

Evaluation and Comparison of SEA Torque Controllers in a Unified Framework

Series elastic actuators (SEA) with their inherent compliance offer a safe torque source for robots that are interacting with various environments, including humans. These applications have high requirements for the SEA torque controllers, both in the torque response as well as interaction behavior with its environment. To differentiate state of the art torque controllers, this work introduces a unifying theoretical and experimental framework that compares controllers based on their torque transfer behavior, their apparent impedance behavior, and especially the passivity of the apparent impedance (i.e., their interaction stability) as well as their sensitivity to sensor noise. We compare classical SEA control approaches such as cascaded PID controllers and full state feedback controllers with advanced controllers using disturbance observers, acceleration feedback and adaptation rules. Simulations and experiments demonstrate the trade-off between stable interactions, high bandwidths and low noise levels. Based on these trade-offs, an application-specific controller can be designed and tuned, based on desired interaction with the respective environment.

Stability-assured design of a full state feedback controller for a three-phase grid-connected converter using disk margin analysis

The paper proposes a tuning procedure for a multioscillatory current controller in a three-phase three-wire grid connected converter operating under distorted voltage conditions. The control system should provide high quality sinusoidal currents. This is achieved by implementing internal models of expected disturbances — multioscillatory terms. Tuning of such systems is challenging if the objective is to guarantee a certain level of stability margins. The multiloop disk margin analysis may be a perfect candidate solution. This analysis combined with a global optimization produces controller gains that can be transferred to the physical system. The paper provides the first complete experimental verification of the multioscillatory full state feedback grid current control system with a designer specified stability margin in the form of disk radius.

Learning hybrid locomotion skills-Learn to exploit residual actions and modulate model-based gait control.

This work has developed a hybrid framework that combines machine learning and control approaches for legged robots to achieve new capabilities of balancing against external perturbations. The framework embeds a kernel which is a model-based, full parametric closed-loop and analytical controller as the gait pattern generator. On top of that, a neural network with symmetric partial data augmentation learns to automatically adjust the parameters for the gait kernel, and also generate compensatory actions for all joints, thus significantly augmenting the stability under unexpected perturbations. Seven Neural Network policies with different configurations were optimized to validate the effectiveness and the combined use of the modulation of the kernel parameters and the compensation for the arms and legs using residual actions. The results validated that modulating kernel parameters alongside the residual actions have improved the stability significantly. Furthermore, The performance of the proposed framework was evaluated across a set of challenging simulated scenarios, and demonstrated considerable improvements compared to the baseline in recovering from large external forces (up to 118%). Besides, regarding measurement noise and model inaccuracies, the robustness of the proposed framework has been assessed through simulations, which demonstrated the robustness in the presence of these uncertainties. Furthermore, the trained policies were validated across a set of unseen scenarios and showed the generalization to dynamic walking.

Deep reinforcement learning method for turbofan engine acceleration optimization problem within full flight envelope

In order to solve the multidimensional restricted optimization problem of aeroengine acceleration process and improve the acceleration performance of full envelope, a design method of aeroengine full envelope acceleration controller based on deep reinforcement learning is proposed. Firstly, the thermo-aerodynamic principle of the engine acceleration process is analyzed, and the mathematical analytical model of the multidimensional restricted optimization problem of the turbofan engine acceleration process is established. On this basis, the design method of acceleration controller based on twin delayed deep deterministic policy gradient is studied. The proportional integral controller is designed to pursue the asymptotic stability at the acceleration destination and stable control is achieved through switching. Additionally, the flight envelope is divided into regions by clustering to reduce the span of data changes, so as to enhance the network convergence ability of deep reinforcement learning. Finally, based on the similarity conversion method of equal engine inlet total temperature, the acceleration controller of full flight envelope is realized. The digital simulation results demonstrate that compared with the traditional proportional integral differential controller, the acceleration controller based on twin delayed deep deterministic policy gradient shortens the acceleration time up to 48.33%, and the control effect in a large flight envelope (H=0∼10 km, Ma=0∼1.6) has been verified.

Penerapan Charger Controller type PWM pada Pembangkit Listrik Tenaga Pikohidro

This study aims to design a PWMtype charger controller, to discover the performance of the PWM type controller, todetermine the compatibility of the PWM type charger controller and MPPT, and to analyze the performance of the PWM type chargercontroller in the PLTPH in JLC. The method of analysis of this study uses field data and is tested on the PWM type charger controller andthe MPPT type charger controller. From the data, the two charger controllers are compared. The results showed that the PWM and MPPTcharger controller performed well to cut off the load current when the battery was full, the PWM and MPPT charger controller performedwell to disconnect the load when the battery began to run out. The PWM and MPPT charger controllers have the same charging speed,and the MPPT charger controller has good efficiency in the PLTPH system.

Full Information Control for Switched Neural Networks Subject to Fault and Disturbance.

The article investigates full information control problem for switched neural networks subject to fault and disturbance. First, the main objective is realizing interval stability and zero tracking error under condition that neither of the neuron states' vectors including the plant and reference models is available. Second, the desired full information controller and neural networks' observer are designed to ensure observer-based dynamic error system mean-square exponentially stable with sufficient condition of strict weight H∞ /H- performance levels. Finally, we concentrate on stability analyses and fault tolerance for switched neural networks with fault accompanied by disturbance through linear matrix inequalities (LMIs), Lyapunov function, and average dwell time, discussing it according to different values of fault. Finally, simulation examples are listed to account for the availability and effectiveness of the research methodology.

Gain scheduling control of aero-engine based on mixing polynomial LPV synthesis

Abstract A full envelope LMI-based multi-region linear parameter-varying power controller is designed for a turbofan engine in this paper. According to the characteristics of aero-engine model, three scheduling variables are divided into two groups firstly, and then part of them are partitioned, rather than all scheduling variables are partitioned directly as the usual multi-region LPV control. The polynomial LPV model of aero-engine is established under a specific flight condition. An explicit LPV controller by gridding method based on parameter-dependent Lyapunov function is designed and we propose a method to eliminate the dependence of LPV controller on the derivative of scheduling parameter. The flight envelope of turbofan engine is divided into multiple sub-regions, and a mixing LPV control method with overlapping regions is proposed, which can guarantee stability and performance across the full envelope. Finally, the simulation results on the nonlinear component level model of a twin-spool turbofan engine verify our method.

Recoil suppression of deepwater drilling riser systems via static output feedback control with memory

In the dangerous ocean situations, the deepwater drilling riser needs evacuate emergently to guarantee the safety of the structures. The bottom equipment of the lower marine riser package should be disconnected from the blowout preventer timely. In this case, the recoil response of the riser occurs, which may lead to potential safety risks of the structure. This paper deals with the recoil suppression control problem of a deepwater drilling riser system via static output feedback recoil control scheme with memory. First, for the riser-tensioner system subject to the friction resistance of drilling discharge and the heave motion of platform, a static output feedback recoil controller with both current and delayed output signals of the system is proposed. Then, the existence conditions and design algorithm of the static output feedback recoil controller are derived. The gain matrices of the recoil controller can be obtained by solving linear matrices inequalities. It is found through simulation results that (i) the static output feedback recoil controllers with and without memory are effective to reduce the recoil responses of the riser; and (ii) to design the applicable output feedback recoil controllers, the displacement and velocity signals of the first mass block of the riser are required, and specifically, the velocity signal of the first mass block is indispensable; and (iii) the output feedback recoil controllers with memory provide more implementation options, and practically better than the ones without memory and some existing full state feedback recoil controllers.

"CONTROL OF SHIP FIN STABILIZERS BY A PID CONTROLLER: A NUMERICAL ANALYSIS "

The reduction of ship roll motion is important in order to prevent damage to cargo, to allow the crew to work efficiently and to provide comfort for the passengers. There are passive devices like bilge keels or anti – roll tanks and active devices like gyrostabilizer and stabilizing fins which are commonly used to generate an opposed moment to the wave and wind excitation roll moments in response to the command of a control system. The paper presents numerical results of using a Proportional - Integral – Derivative (PID) controller for damping the roll motion of a fishing boat equipped with a fin stabilizer system and sailing in regular waves. The nonlinear roll equation, which includes B1 type damping and quantic restoring, besides the wave excitation moment and moment generated by fins, was linearized for relative small roll angles. The role of PID controller was to generate the corrective roll moment through the controlled fins in order to stabilize the roll motion. The thresholds for the controller’s gains were determined using the Laplace transform and Routh – Hurwitz criterion. A simple but precise iterative scheme was used for the rapid integration of the system equations of motion in three cases: only proportional (P) component, proportional and derivative (PD) components and full PID controller. The numerical simulations have showed that all the analysed variants achieved roll reduction satisfactorily.

Satellite dish antenna control for distributed mobile telemedicine nodes

<p align="justify"><span>The positioning control of a dish antenna mounted on distributed mobile telemedicine nodes (DMTNs) within Nigeria communicating via NigComSat-1R has been presented. It was desired to improve the transient and steady performance of satellite dish antenna and reduce the effect of delay during satellite communication. In order to overcome this, the equations describing the dynamics of the antenna positioning system were obtained and transformed into state space variable equations. A full state feedback controller was developed with forward path gain and an observer. The proposed controller was introduced into the closed loop of the dish antenna positioning control system. The system was subjected to unit step forcing function in MATLAB/Simulink simulation environment considering three different cases so as to obtain time domain parameters that characterized the transient and steady state response performances. The simulation results obtained revealed that the introduction of the full state feedback controller provided improved position tracking to unit step input with a rise time of 0.42 s, settling time of 1.22 s and overshoot of 4.91%. With the addition of observer, the rise time achieved was 0.39 s, settling time of 1.31 s, and overshoot of 10.7%. The time domain performance comparison of the proposed system with existing systems revealed its superiority over them.</span></p>

Dynamic state feedback controller and observer design for dynamic artificial neural network models

Artificial neural networks are black-box models that can be used to model nonlinear dynamical systems. This article presents a synthesis method for full dynamic state feedback controllers and state and output observers that have guaranteed properties for systems approximated by dynamic artificial neural networks. The resulting control designs are applicable to the practical situation in which the steady-state values for the control input are not known. Dynamic artificial neural networks are written in the standard nonlinear operator form, also known in the literature as the Luré formulation. A generalized form of the Luré formulation is adopted to allow for the representation of deep ℓ-layer networks, ℓ≥1. Sufficient conditions for controller synthesis and observer design are derived in the form of linear matrix inequalities, using a quadratic Lyapunov function. The synthesis method is demonstrated for the control of pH in two tanks in series and a numerical example.

Full State Feedback H-Infinity Controller Design for Nonlinear Systems

Real world systems are inherently nonlinear in nature. Over the last few decades, nonlinear systems are regarded as the most significant issue in control theory. In this work, a nonlinear full state feedback H-infinity controller is proposed for nonlinear systems. The black hole optimization method (BHO) is used as an effective optimization technique to find the optimal parameters for the proposed controller based on the proposed cost function. The suggested controller gain matrix is computed by solving the H-infinity algebraic Riccati equation. As case studies, two types of nonlinear systems are demonstrated to demonstrate the utility of the proposed controller. Finally, simulation findings show that the suggested nonlinear controller improves the stability and performance of nonlinear systems by compensating them and compelling their states to track the reference input asymptotically with a workable and feasible control action.

Modeling and Optimal Control for Rotary Unmanned Aerial Vehicles in Northern Ireland Climate

Rotary Unmanned Aerial Vehicles (RUAVs) suffer in average Northern Irish winters due to heavy wind preventing vital tasks from being performed in the economy, such as search and rescue or civil engineering observations. This work provides enhanced stability of RUAVs under wind disturbances by using metaheuristic algorithms to select optimal controller gains. Previous work demonstrated how Particle Swarm Optimization can be used to tune optimal controllers; this work uses a machine learning algorithm (Genetic Algorithm) to tune the controller. Simulations carried out on Full State Feedback, Full State Compensator and Linear Quadratic Gaussian controllers tuned by a variety of techniques revealed that the Genetic Algorithm outperformed conventional manual tuning by 20% and Particle Swarm Optimization by 17% in performance measured in settling time. The proposed method tunes the feedback gains and Kalman filter by Genetic Algorithm, which outperforms the manually tuned conventional schemes and “GA-Hybrid” approach. The conditions required to employ Reinforcement Learning as an alternative method for RUAV stabilization in future scope is also explored.

Aero-engine on-board model based on big Quick Access Recorder data

With the development of the Full Authority Digital Engine Controller (FADEC) technology, the aero-engine on-board model is widely used in Engine Health Management (EHM) and control. Due to the FADEC’s limited computational capability and storage capacity, the model should not be very intricate; consequently, the interpolation model is widely utilized. Although the interpolation model’s low precision precludes further development of on-board models for EHM and control. To address the trade-off between precision and complexity, a novel on-board modeling method is proposed based on the Nonlinear Autoregressive with Exogenous Inputs Backpropagation neural network (NARX-BPNN) trained using the mini-batch Levenberg–Marquardt (LM) algorithm on large Quick Access Recorder (QAR) data. The NARX model’s features and time delay are chosen by referring to the line interpolation model, which gives interpretability for feature selection. The combination of a shallow neural network and big data training can guarantee the on-board model’s real-time and storage requirements, as well as its generalizability. The mini-batch LM method can avoid both the local optimum problem in the shallow neural network and the storage difficulty associated with massive data while still achieving a rapid convergence rate due to the LM algorithm’s global view. The NARX-BPNN models are compared to an existing line interpolation model using 100 different aero-engines' QAR data. The results reveal that accuracy may be increased by approximately 30% while maintaining superior dynamic performance and anti-noise capacity compared to the line interpolation approach.

Plug-in disturbance observer assisted DC link voltage control of grid-connected converters to improve transient performance without deteriorating grid current quality

Trade-off between DC link voltage dynamics and AC-side current quality in grid-interfacing power converters limits the attainable DC link voltage loop bandwidth for a given desired value of grid-side current total harmonic distortion (THD). It was recently shown that adding a notch filter in series with the typically employed DC link voltage controller of PI or type-II structure releases the above trade-off, yet requires full controller re-design. The paper proposes to replace the notch filter by a plug-in disturbance observer, allowing to increase attainable DC link voltage loop bandwidth for given grid-side current THD without any modification of the existing DC link voltage controller by utilizing a special frequency-selective filter. Simulations and experimental results validate the proposed design methodology.