This study proposes an active surge control method based on deep reinforcement learning to ensure the stability of compressors when adhering to the pressure rise command across the wide operating range of an ***,the s...
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This study proposes an active surge control method based on deep reinforcement learning to ensure the stability of compressors when adhering to the pressure rise command across the wide operating range of an ***,the study establishes the compressor dynamic model with uncertainties,disturbances,and Close-Coupled Valve(CCV)actuator *** upon this foundation,a Partially Observable Markov Decision Process(POMDP)is defined to facilitate active surge *** address the issue of unobservability,a nonlinear state observer is designed using a finite-time high-order sliding ***,an Improved Soft Actor-Critic(ISAC)algorithm is developed,incorporating prioritized experience replay and adaptive temperature parameter techniques,to strike a balance between exploration and convergence during *** addition,reasonable observation variables,error-segmented reward functions,and random initialization of model parameters are employed to enhance the robustness and generalization ***,to assess the effectiveness of the proposed method,numerical simulations are conducted,and it is compared with the fuzzy adaptive backstepping method and Second-Order Sliding Mode Control(SOSMC)*** simulation results demonstrate that the deep reinforcement learning based controller outperforms other methods in both tracking accuracy and ***,the proposed active surge controller can effectively ensure stable operation of compressors in the high-pressure-ratio and high-efficiency region.
In the existing multi-period robust optimization methods for the optimal power flow in radial distribution systems,the capability of distributed generators(DGs)to regulate the reactive power,the operation costs of the...
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In the existing multi-period robust optimization methods for the optimal power flow in radial distribution systems,the capability of distributed generators(DGs)to regulate the reactive power,the operation costs of the regulation equipment,and the current of the shunt capacitor of the cables are not *** this paper,a multi-period two-stage robust scheduling strategy that aims to minimize the total cost of the power supply is *** strategy considers the time-ofuse price,the capability of the DGs to regulate the active and reactive power,the action costs of the regulation equipment,and the current of the shunt capacitors of the cables in a radial distribution ***,the numbers of variables and constraints in the first-stage model remain constant during the iteration to enhance the computation *** solve the second-stage model,only the model of each period needs to be ***,their objective values are accumulated,revealing that the computation rate using the proposed method is much higher than that of existing *** effectiveness of the proposed method is validated by actual 4-bus,IEEE 33-bus,and PG 69-bus distribution systems.
The deployable telescopic boom,whose mass and stiffness play crucial roles,is extensively used in the design of space-deployable ***,the most existing optimal design that neglects the influence of the locking mechanis...
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The deployable telescopic boom,whose mass and stiffness play crucial roles,is extensively used in the design of space-deployable ***,the most existing optimal design that neglects the influence of the locking mechanisms in boom joints cannot raise the whole stiffness while reducing the boom *** tackle this challenge,a novel optimization model,which utilizes the arrangement of the locking mechanisms to achieve synchronous improvement of the stiffness and mass,is *** proposed optimization model incorporates a novel joint stiffness model developed based on an equivalent parallel mechanism that enables the consideration of multiple internal stiffness factors of the locking mechanisms and tubes,resulting in more accurate representations of the joint stiffness *** analysis shows that the proposed stiffness model achieves more than at least 11% improved accuracy compared with existing ***,case verification shows that the proposed optimization model can improve stiffness while effectively reducing mass,and it is applied in boom optimization design.
We propose an optimal stochastic scheduling strategy for a multi-vector energy complex(MEC),considering a fullblown model of the power-to-biomethane(Pt M)*** conventional optimization that uses a simple efficiency coe...
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We propose an optimal stochastic scheduling strategy for a multi-vector energy complex(MEC),considering a fullblown model of the power-to-biomethane(Pt M)*** conventional optimization that uses a simple efficiency coefficient to coarsely model energy conversion between electricity and biomethane,a detailed Pt M model is introduced to emphasize the reactor kinetics and chemical equilibria of *** model crystallizes the interactions between the Pt M process and MEC flexibility,allowing to adjust the operating condition of the methanation reactor for optimal MEC operation in stochastic *** optimization and flowsheet design of the Pt M process increase the average selectivity of methane(i.e.,ratio between net biomethane production and hydrogen consumption)up to 83.7%in the proposed synthesis *** results can provide information and predictions to operators about the optimal operating conditions of a Pt M unit while improving the MEC flexibility.
For uncertainty quantification of complex models with high-dimensional,nonlinear,multi-component coupling like digital twins,traditional statistical sampling methods,such as random sampling and Latin hypercube samplin...
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For uncertainty quantification of complex models with high-dimensional,nonlinear,multi-component coupling like digital twins,traditional statistical sampling methods,such as random sampling and Latin hypercube sampling,require a large number of samples,which entails huge computational ***,how to construct a small-size sample space has been a hot issue of interest for *** this end,this paper proposes a sequential search-based Latin hypercube sampling scheme to generate efficient and accurate samples for uncertainty ***,the sampling range of the samples is formed by carving the polymorphic uncertainty based on theoretical ***,the optimal Latin hypercube design is selected using the Latin hypercube sampling method combined with the"space filling"***,the sample selection function is established,and the next most informative sample is optimally selected to obtain the sequential test *** with the classical sampling method,the generated samples can retain more information on the basis of sparsity.A series of numerical experiments are conducted to demonstrate the superiority of the proposed sequential search-based Latin hypercube sampling scheme,which is a way to provide reliable uncertainty quantification results with small sample sizes.
This paper focuses on linear-quadratic(LQ)optimal control for a class of systems governed by first-order hyperbolic partial differential equations(PDEs).Different from most of the previous works,an approach of discret...
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This paper focuses on linear-quadratic(LQ)optimal control for a class of systems governed by first-order hyperbolic partial differential equations(PDEs).Different from most of the previous works,an approach of discretization-then-continuousization is proposed in this paper to cope with the infinite-dimensional nature of PDE *** contributions of this paper consist of the following aspects:(1)The differential Riccati equations and the solvability condition of the LQ optimal control problems are obtained via the discretization-then-continuousization method.(2)A numerical calculation way of the differential Riccati equations and a practical design way of the optimal controller are ***,the relationship between the optimal costate and the optimal state is established by solving a set of forward and backward partial difference equations(FBPDEs).(3)The correctness of the method used in this paper is verified by a complementary continuous method and the comparative analysis with the existing operator results is *** is shown that the proposed results not only contain the classic results of the standard LQ control problem of systems governed by ordinary differential equations as a special case,but also support the existing operator results and give a more convenient form of computation.
Electrorheological(ER) and magnetorheological(MR) dampers, which are active damping devices, stand out for their exceptional performance in mitigating vibrations in mechanical systems and construction engineering....
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Electrorheological(ER) and magnetorheological(MR) dampers, which are active damping devices, stand out for their exceptional performance in mitigating vibrations in mechanical systems and construction engineering. Their prowess lies in the inherent ability of ER/MR fluids to change their mechanical properties, particularly viscosity and shear stress, in response to the influence of electric or magnetic fields. In this study, a damper filled with Giant-ER(GER) fluid, a modified product of ER fluid,is employed in the rotor system for vibration suppression. This damper operates in a Cut submode derived from the conventional working modes. This mode results in an effective enhancement of the damping performance by integrating the advantages of these modes, thereby achieving a damping force density of 1.2 × 10~4 N/m2and a modulation coefficient of 15 within a multilayered cylindrical damper. Whereafter, the dynamics of the rotor system are modeled and analyzed based on the Jeffcott rotor model, which incorporates a parallelogram-structured motion decoupling mechanism equipped with the proposed Cut submode dampers that are introduced to reduce the vibration of the transmission shaft in the rotor system. Furthermore, to evaluate the damping effect, a vibration-damping performance validation testbed is constructed. The results are noteworthy, demonstrating that by leveraging the superior properties of the GER fluid, the Cut submode damper effectively suppresses the vibrations of the transmission shaft, particularly at the resonant frequencies, achieving an impressive 88.9% reduction when subjected to an electric field of 3 kV/mm compared to the action of 0 kV/mm. This performance highlights the exceptional effectiveness of the proposed Cut submode, underscoring its vast potential for various engineering applications.
In this paper, the problem of pre-specified performance fault-tolerant cluster consensus control and fault direction identification is solved for the human-in-the-loop(HIL) swarm unmanned aerial vehicles(UAVs) in the ...
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In this paper, the problem of pre-specified performance fault-tolerant cluster consensus control and fault direction identification is solved for the human-in-the-loop(HIL) swarm unmanned aerial vehicles(UAVs) in the presence of possible nonidentical and unknown direction faults(NUDFs) in the yaw *** control strategy begins with the design of a pre-specified performance event-triggered observer for each individual *** observers estimate the outputs of the human controlled UAVs, and simultaneously achieve the distributed design of actual control signals as well as cluster consensus of the observer *** is worth mentioning that these observers require neither the high-order derivatives of the human controlled UAVs' output nor a priori knowledge of the initial conditions. The fault-tolerant controller realizes the pre-specified performance output regulation through error transformation and the Nussbaum function. It should be pointed out that there are no chattering caused by the jump of the Nussbaum function when a reverse fault occurs. In addition, to provide a basis for further solving the problem of physical malfunctions, a fault direction identification algorithm is proposed to accurately identify whether a reverse fault has occurred. Simulation results verify the effectiveness of the proposed control and fault direction identification strategies when the reverse faults occur.
Dear Editor,This letter focuses on the distributed cooperative regulation problem for a class of networked re-entrant manufacturing systems(RMSs). The networked system is structured with a three-tier architecture:the ...
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Dear Editor,This letter focuses on the distributed cooperative regulation problem for a class of networked re-entrant manufacturing systems(RMSs). The networked system is structured with a three-tier architecture:the production line, the manufacturing layer and the workshop layer. The dynamics of re-entrant production lines are governed by hyperbolic partial differential equations (PDEs) based on the law of mass conservation.
A variety of soft wall-climbing robots have been developed that can move in certain *** of these soft robots can only move on conventional surfaces and lack adaptability to complex *** the adaptability of soft robots ...
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A variety of soft wall-climbing robots have been developed that can move in certain *** of these soft robots can only move on conventional surfaces and lack adaptability to complex *** the adaptability of soft robots on complex surfaces is still a challenging *** this end,we study the layered structure of the starfish tube foot and the valve flap structure in the water vascular system,and use an ultrasonic stress detector to study the stiffness distribution of the arm *** by the motion of the starfish,we present a bionic soft wall-climbing robot,which is driven by two groups of pneumatic feet and achieves body bending through active adaptation *** design the structure of the foot to flex to provide driving force,and there are suction cups at the end of the foot to provide *** soft foot has a simple structure design,adapts to a variety of surfaces,and does not damage the surface of the *** stiffness layers achieve stiffness changes by the principle of line *** Central Pattern Generator theory is introduced to coordinately control the multiple feet of the *** experiments,we verify the adaptability of the soft robot to curved *** research may provide a reference for the design and development of crawling soft robots on complex surfaces.
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