This paper aims to develop a distributed layered control framework for the navigation, planning, and control of multi-agent quadrupedal robots subject to environments with uncertain obstacles and various disturbances....
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This paper aims to develop a distributed layered control framework for the navigation, planning, and control of multi-agent quadrupedal robots subject to environments with uncertain obstacles and various disturbances. At the highest layer of the proposed layered control, a reference path for all agents is calculated, considering artificial potential fields (APF) under a priori known obstacles. Second, in the middle layer, we employ a distributed nonlinear model predictive control (NMPC) scheme with a one-step delay communication protocol (OSDCP) subject to reduced-order and linear inverted pendulum (LIP) models of agents to ensure the feasibility of the gaits and collision avoidance, addressing the degree of uncertainty in real-time. Finally, low-level nonlinear whole-body controllers (WBCs) impose the full-order locomotion models of agents to track the optimal and reduced-order trajectories. The proposed controller is validated for effectiveness and robustness on up to four A1 quadrupedal robots in simulations and two robots in the experiments.1 Simulations and experimental validations demonstrate that the proposed approach can effectively address the real-time planning and control problem. In particular, multiple A1 robots are shown to navigate various environments, maintaining collision-free distances while being subject to unknown external disturbances such as pushes and rough terrain.
The effectiveness of the various control algorithms for semi-active structural control systems proposed in the literature is highly questionable when dealing with earthquake actions, which never reach a steady state. ...
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The effectiveness of the various control algorithms for semi-active structural control systems proposed in the literature is highly questionable when dealing with earthquake actions, which never reach a steady state. From this perspective, the paper summarizes the results of an experimental activity aimed to compare the effectiveness of four different semi-active control algorithms on a structural mock up representative of a class of structural systems particularly prone to seismic actions. The controlled structure is a near full scale 2-story steel frame, equipped with two semi-active bracing systems including two magnetorheological dampers designed and manufactured in Europe. A set of earthquake records has been applied at the base of the structure, by utilizing a shaking table facility. Experimental results are compared in terms of displacements, absolute accelerations and energy dissipation capability. A further analysis on the percentage incidence of undesired and/or unpredictable operations corresponding to each algorithm gives an insight on some factors affecting the reliability and, in turn, the real effectiveness of semi-active structural control systems.
The tool-workpiece vibration in the precision milling process plays a pivotal role in influencing the surface quality. To solve the machining problem coming with the process vibration, the active vibration control mod...
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The tool-workpiece vibration in the precision milling process plays a pivotal role in influencing the surface quality. To solve the machining problem coming with the process vibration, the active vibration control model as well as the corresponding platform are developed, and the active vibration control algorithms are applied to reduce the relative vibrations and improve the surface quality. Firstly, the milling vibration reduction and surface quality improvement are modeled based on the active control algorithms and the system dynamic characteristics. Then, applying the different algorithm control strategies, such as PID, Fuzzy PID, BP neural network, and BP neural network PID control, the control effect is simulated and analyzed. Finally, an experimental platform is established to validate the system's reliability. The efficiency of various active control methods is compared in terms of frequency vibration control and surface finish roughness improvement. The results indicate that under different milling parameters, the four algorithm control strategies exhibit optimal effects of 13.5%, 30.4%, 28.8%, and 40.1% respectively. These findings provide valuable insights into selecting the optimal vibration control method for precision milling.
Multi-functional photovoltaic (PV) inverters incorporate ancillary services to enhance power quality and mitigate stability issues in distribution networks. These next-generation PV inverters will achieve a higher uti...
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Multi-functional photovoltaic (PV) inverters incorporate ancillary services to enhance power quality and mitigate stability issues in distribution networks. These next-generation PV inverters will achieve a higher utilization of the inverter's rated capacity, improving the cost-effectiveness of PV technology. However, the power required to perform ancillary services, such as load compensation capabilities, could exceed the inverter's capacity, risking the components' integrity. Therefore, multi-functional control algorithms must limit the power capacity according to the system's nominal currents. Despite this, most control proposals do not address this issue when load balancing capabilities are included for PV inverter control. This paper proposes a flexible control strategy for three-phase multi-functional PV inverters, considering load balancing functionalities while keeping the inverter currents within safe operating limits. The proposal introduces two control parameters whose variation results in different load compensation capabilities. These parameters can be adapted dynamically according to the inverter rated capacity not used for active power injection and the load compensation requirements. Additionally, a control algorithm is proposed to limit the inverter current according to the nominal values supported by the device. This algorithm also allows setting compensation objectives following a priority scheme in which the injection of the PV active power is prioritized over the load compensation functionalities. Reactive power compensation and load balancing functionalities are also considered at a lower level of hierarchical priority. The proposal was evaluated through experimental tests on a multi-functional PV inverter prototype under various operational conditions. The experimental results show an excellent control strategy performance, achieving the control objectives under unbalanced load conditions.
Switched reluctance motors are a potential competitor to permanent magnet motors and induction motors for various industrial applications. The switched reluctance motors without permanent magnets have gained increased...
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Switched reluctance motors are a potential competitor to permanent magnet motors and induction motors for various industrial applications. The switched reluctance motors without permanent magnets have gained increased interest due to their simple structure, low cost, robustness, and high fault tolerance. However, the nonlinear characteristics caused by the double salient structure limit its wide applications. Advanced control techniques have been developed to suppress torque ripple, enhance anti-disturbance ability, reduce the switching frequency, expand speed range, and improve efficiency. The control strategies such as direct torque control and control algorithms like sliding mode control are two main approaches considered. Previous work only focuses on one side of control techniques. Thus, based on various control techniques proposed in recent years, this review classifies and summarizes their benefits and shortcomings. In addition, some essential trends in control development are presented and highlighted as future perspectives.
An innovative Computational Fluid Dynamics (CFD) approach, defined as the Forcing Function Method (FFM), is used to simulate Ride control Systems (RCS) on an Incat Tasmania Wave-Piercing Catamaran vessel in analysis c...
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An innovative Computational Fluid Dynamics (CFD) approach, defined as the Forcing Function Method (FFM), is used to simulate Ride control Systems (RCS) on an Incat Tasmania Wave-Piercing Catamaran vessel in analysis conducted at model scale. This study examines the FFM's capabilities in head sea regular waves using CFD, and considers three ride control scenarios: Bare Hull (BH), Pitch control (PC), and Non-Linear Pitch control (NL PC). CFD-predicted vessel motion is compared to experimental data from a 2.5 m Incat Tasmania Wave-Piercing Catamaran model at 2.89 m/s (Fr similar to 0.6), showing good agreement. Modification in FFM to account for emergence of control surfaces from the water, and time series of lift forces produced by FFM are also discussed. The frequency domain analysis using heave and pitch Response Amplitude Operators (RAOs) showed a good of agreement in motion reduction trends between CFD and experiments, providing a high level of confidence in the FFM predictions. Dimensionless vertical accelerations are calculated along the length of hull using the various control algorithms, showing a considerable reduction in acceleration, especially at the bow. These outcomes demonstrate the novel CFD approach, FFM, that can be used by ship designers for predicting high-speed vessel motion reductions from deployment of RCS, and thereby improving passenger comfort.
The Filtered Smith Predictor (FSP) is a practical structure in industrial control systems, especially those with dominant time delays. Despite its importance, a notable gap exists in developing tailored algorithms for...
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The Filtered Smith Predictor (FSP) is a practical structure in industrial control systems, especially those with dominant time delays. Despite its importance, a notable gap exists in developing tailored algorithms for the FSP that can effectively diagnose model degradation and the presence of abrupt disturbances. This research addresses the challenge of distinguishing between model -plant mismatch (MPM) and unmeasured disturbances (UD), which is crucial to maintaining control system performance and stability. We propose a novel algorithm that diagnoses, monitors, and self -tunes the FSP structure. By leveraging the sensitivity transfer function, our method ascertains nominal closed -loop performance without MPM or UD and meticulously analyzes the real effects of these factors. A dynamic time window and an operating range, used as tuning parameters, enable a precise assessment of the model's predictive capacity and the detection of UD. Additionally, the algorithm incorporates a self -tuning mechanism for the FSP's robustness filter, responding adaptively to identified discrepancies and ensuring enhanced system stability. Demonstrated through detailed simulated case studies and a real -life temperature control experiment, our methodology significantly improves the diagnosis and self -tuning capabilities of FSP structures. The results highlight a marked enhancement in system stability and performance, providing our approach's practical value and effectiveness in real -world industrial applications.
A practical examination of the traditional robotic arm (RA) in operation revealed a significant limitation in its ability to control the position of motion. This underscores the urgent need to enhance the current RA&#...
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A practical examination of the traditional robotic arm (RA) in operation revealed a significant limitation in its ability to control the position of motion. This underscores the urgent need to enhance the current RA's position control capabilities. Therefore, this study proposes the use of nonlinear differential equations (NDEs) to establish a mathematical model and the design of NDE-based RA motion control algorithms in conjunction with a central pattern generator neural network. A comparison of the control effects showed that the proposed method was highly fitted to the target trajectory. The joint node (JN) motion tracking trajectories of the three RAs were similar, up to 90-85% to the target trajectories of the JNs. In addition, the control of the motion position was similar up to 95-98% to the target motion position trajectories. The motion control algorithm based on NDEs was effective in improving the average execution time of the Pareto optimal frontier of the RA by 58.29%. The joint velocity and angle changes of the three types of RAs under the NDE control algorithm exhibited a high degree of similarity to the fluctuations observed in the expected and predicted curves. These observations contribute to an understanding of the effectiveness of the system observer in observing the joint angle changes. This indicates that the motion control based on NDEs can effectively enhance the tracking effectiveness of the JN positions of the RA, improve the control ability of the RA motion, and increase the joint stability of the RA.
We consider a principle or controller that can pick actions from a fixed action set to control an evolving system with converging dynamics. The actions are interpreted as different configurations or policies. We consi...
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We consider a principle or controller that can pick actions from a fixed action set to control an evolving system with converging dynamics. The actions are interpreted as different configurations or policies. We consider systems with converging dynamics, i.e., if the principle holds the same action, the system will asymptotically converge (possibly requiring a significant amount of time) to a unique stable state determined by this action. This phenomenon can be observed in diverse domains such as epidemic control, computing systems, and markets. In our model, the dynamics of the system are unknown to the principle, and the principle can only receive bandit feedback (maybe noisy) on the impacts of his actions. The principle aims to learn which stable state yields the highest reward while adhering to specific constraints (i.e., optimal stable state) and to immerse the system into this state as quickly as possible. A unique challenge in our model is that the principle has no prior knowledge about the stable state of each action, but waits for the system to converge to the suboptimal stable states costs valuable time. We measure the principle's performance in terms of regret and constraint violation. In cases where the action set is finite, we propose a novel algorithm, termed Optimistic-Pessimistic Convergence and Confidence Bounds (OP-C2B), that knows to switch an action quickly if it is not worth waiting until the stable state is reached. This is enabled by employing "convergence bounds" to determine how far the system is from the stable states, and choosing actions through maintaining a pessimistic assessment of the set of feasible actions while acting optimistically within this set. We establish that OP-C2B can ensure sublinear regret and constraint violation simultaneously. Particularly, OP-C2B achieves logarithmic regret and constraint violation when the system convergence rate is linear or superlinear. Furthermore, we generalize our algorithm OP-C2B to the case
The evolving technologies regarding Unmanned Aerial Vehicles (UAVs) have led to their extended applicability in diverse domains, including surveillance, commerce, military, and smart electric grid monitoring. Modern U...
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The evolving technologies regarding Unmanned Aerial Vehicles (UAVs) have led to their extended applicability in diverse domains, including surveillance, commerce, military, and smart electric grid monitoring. Modern UAV avionics enable precise aircraft operations through autonomous navigation, obstacle identification, and collision prevention. The structures of avionics are generally complex, and thorough hierarchies and intricate connections exist in between. For a comprehensive understanding of a UAV design, this paper aims to assess and critically review the purpose-classified electronics hardware inside UAVs, each with the corresponding performance metrics thoroughly analyzed. This review includes an exploration of different algorithms used for data processing, flight control, surveillance, navigation, protection, and communication. Consequently, this paper enriches the knowledge base of UAVs, offering an informative background on various UAV design processes, particularly those related to electric smart grid applications. As a future work recommendation, an actual relevant project is openly discussed.
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