To evaluate the combustion characteristics of sustainable aviation fuels on a research gas turbine engine, a separate test bench with a fuel pump has to be connected to the turbine. To keep the gas turbine unit connec...
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ISBN:
(纸本)9798350329537;9798350329520
To evaluate the combustion characteristics of sustainable aviation fuels on a research gas turbine engine, a separate test bench with a fuel pump has to be connected to the turbine. To keep the gas turbine unit connected with the pump unit and to operate the pump based on the required fuel the throughput must be determined. The pump test unit was not able to operate under static conditions since it only had an open-loop control. A closed-loop control had to be designed which operated based on a given RPM reference. A system identification was commenced on the pump unit, then a PID control was designed and implemented. All the identification and the controlling was tasked to a microcontroller. The relevant commands and given references were given to the controller via a computer connection.
The paper proposes a design method dedicated to control systems, which use a certain energy function (surface), called the Hamiltonian of the system. The plant requires, most of the time, the convergence at different ...
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ISBN:
(纸本)9798350329537;9798350329520
The paper proposes a design method dedicated to control systems, which use a certain energy function (surface), called the Hamiltonian of the system. The plant requires, most of the time, the convergence at different fixed points and at the same time in different ways (different behaviors). This phenomenon is possible by modifying the initial energy surface. Modification of the energy surface can be achieved by external (generalized) forces. The formalism suggested in this paper allows the calculation of generalized forces and, finally, to obtain the mentioned changes.
In engineering practice, a very common problem to solve is to guide a tool, a moving part of a machine, or the vehicle itself along a predefined path or trajectory with the smallest possible deviation. If the desired ...
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ISBN:
(纸本)9798350329537;9798350329520
In engineering practice, a very common problem to solve is to guide a tool, a moving part of a machine, or the vehicle itself along a predefined path or trajectory with the smallest possible deviation. If the desired nominal trajectory is known and can be derived at least twice with respect to time, and a kinematic model of the system is available, then the force or torque required to achieve the trajectory can be calculated from the nominal acceleration (this method is often referred as CTC: Computed Torque control). However, since the exact kinematic model is not available in most cases, the system parameters may vary during operation, and external disturbing forces and torques may be present, constant error feedback is required to calculate the acceleration required to maintain the desired trajectory. In practice, the implementation of CTC can be greatly simplified by tuning only one feedback parameter value. This paper presents a demonstration and experimental application of such a single-parameter CTC method for a single axis linear positioning.
The paper presents a comprehensive approach in design of an intelligent controller usable for small turbojet engines. The controller has been designed using a complex nonlinear model of a small turbojet engine, which ...
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ISBN:
(纸本)9798350329537;9798350329520
The paper presents a comprehensive approach in design of an intelligent controller usable for small turbojet engines. The controller has been designed using a complex nonlinear model of a small turbojet engine, which incorporates its dynamics dependent on velocity and altitude. The main contribution of the paper lies in the design of an adaptive fuzzy controller with a very small rule-base that is usable for control of small turbine engines under all standard operating conditions. The paper represents proof of concept that a very simple to implement, yet effective fuzzy adaptive algorithm performs on par with other more complex approaches. The adaptive controller uses the developed parametric estimation of the engine's main parameters and has been validated in simulation environment and compared to other adaptive methodologies.
The primary objective of control system design is to ensure that the system functions effectively, even in the presence of modeling inaccuracies. The Robust Sliding Mode control is a systematic approach that helps mai...
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ISBN:
(纸本)9798350329537;9798350329520
The primary objective of control system design is to ensure that the system functions effectively, even in the presence of modeling inaccuracies. The Robust Sliding Mode control is a systematic approach that helps maintain stability and consistent performance accuracy in situations with even considerable dynamic and parameter uncertainties. However, overestimating the control force can cause the system to chatter leading to good tracking accuracy at the cost of high wear of moving mechanical parts, and high heat losses. Smoothing the control signal can reduce chattering, which may result in deteriorated tracking accuracy. The Steffensen Convergence Accelerator Strategy is employed to improve tracking precision and the smoothness of the applied control signal by speeding up the convergence of the controller. Numerical simulations were conducted to analyze the strategy's effectiveness in controlling the van der Pol oscillator. This oscillator is a well-known example of a strong nonlinear system that exhibits nonlinear oscillations and an unstable equilibrium state. The results of the simulations demonstrate that Steffensen's accelerator considerably improved the control quality in terms of accuracy, simplicity, and smoothness of the applied control signal.
Bionic muscle-driven musculoskeletal systems can dynamically adjust the stiffness between active and antagonistic muscles to improve stability. However, they retain many problems, such as difficulty with sensory feedb...
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Bionic muscle-driven musculoskeletal systems can dynamically adjust the stiffness between active and antagonistic muscles to improve stability. However, they retain many problems, such as difficulty with sensory feedback control, which arises from the strong coupling of models and large computational loads encountered when optimizing the muscle force online. In this study, based on a bionic muscle model, an event-triggered-sliding-mode controller for a discrete-time-muscle-driven musculoskeletal system (MDMS) was designed to drive the system into a bounded region. Specifically, based on the Hamilton principle and discretization of muscle contraction dynamics, a new discrete-time-muscle-driven musculoskeletal model was constructed to facilitate the decoupling of the muscle model, feedback of the muscle state, and improvement of model control accuracy. Second, to guarantee the boundedness of the closed-loop system, an even-triggered-sliding-mode control law was established by introducing the input-to-state stable (ISS) method to a new type of discrete-time MDMS. The design ensured the convergence of different triggering cases, and an event-triggered-sliding-mode control law was established to obtain faster and smoother response characteristics. Finally, stability was ensured using the Lyapunov synthesis principle. The experimental results demonstrated that the proposed controller could effectively reduce the computational load while maintaining the same performance using a time-based approach. Note to Practitioners-The motivation of this study is to delve into the utilization of the Lyapunov control theory to enhance the control performance of the bionic muscle model. Additionally, it aimed to explore the initial application of the event-trigger mechanism within the musculoskeletal system. The primary focus is on discrete musculoskeletal system modeling, which facilitates the achievement of sensory feedback control for nonlinear muscle models characterized by strong c
This paper presents a sliding mode observer based fuzzy control. The sliding mode observer is developed for a linear dominant system, but taking into account the model mismatch. After that a fuzzy state feedback contr...
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In this paper, the skewed output noise is considered and we propose a lightweight robust algorithm for nonlinear state-space system identification based on the generalized hyperbolic variance gamma (GHVG) distribution...
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In this paper, the skewed output noise is considered and we propose a lightweight robust algorithm for nonlinear state-space system identification based on the generalized hyperbolic variance gamma (GHVG) distribution, which enhances the robustness of the proposed algorithm. To facilitate the realization of the proposed algorithm, the hidden variables are introduced to decompose the GHVG distribution into the Gaussian gamma mixture (GGM) distribution, which improves the computational efficiency of the proposed algorithm. The expectation maximization (EM) and the particle smoothing (PS) approaches are combined to solve the hidden variables and unknown states problems, which contributes to derive the estimation formulas of the model parameters and noise parameters simultaneously. To further reduce the computational burden of PS method for estimating the nonlinear states, a novel nearest neighbor idea is used in the identification process which ensures the performance of the proposed algorithm while reducing the number of particles involved in the calculation of the cost function. Finally, the verification results are fairly carried out to demonstrate the effectiveness of the proposed algorithm.
Artificial intelligence (AI) is not a fancy term anymore, or not limited to only researchers and academia. AI is currently becoming a part and parcel of our daily life, we are using AI/ intelligent systems by knowing ...
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The proliferation of Internet of Things (IoT) devices in home automation systems has introduced unprecedented convenience but also raised serious concerns regarding security vulnerabilities [1]. This paper delves into...
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