Pole placement is a well-established design method for linear controlsystems. Note however that with an output feedback controller of low-order such as PID one cannot achieve arbitrary pole placement for a high-order...
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Pole placement is a well-established design method for linear controlsystems. Note however that with an output feedback controller of low-order such as PID one cannot achieve arbitrary pole placement for a high-order or delay system, and then partially or hopefully, dominant pole placement becomes the only choice. To the best of the authors’ knowledge, no method is available in the literature to guarantee dominance of the assigned poles in the above case. This paper proposes two simple and easy methods which can guarantee the dominance of the assigned two poles for PID controlsystems. They are based on Root-Locus and Nyquist plot, respectively. If a solution exists, the parametrization of all the solutions is explicitly given. Examples are provided for illustration.
INTRODUCTION:NLRP3-dependent inflammasome signalling is a key pathway during inflammatory processes and its deregulation is implicated in several diseases. NLRP3-inflammasome pathway activation leads to the rapid, pho...
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INTRODUCTION:NLRP3-dependent inflammasome signalling is a key pathway during inflammatory processes and its deregulation is implicated in several diseases. NLRP3-inflammasome pathway activation leads to the rapid, phosphorylation-driven NF$\kappa$κB-pathway signalling, subsequently proceeds via slower transcription/translation process for producing pro-enzymes, and finally leads to the medium-speed enzymatic activation of the central inflammatory mediator IL-$1\beta$1β[1] . We here were interested in how the timing of the rate-limiting step of transcription/translation and the presence of a positive and negative auto-regulation would pose conditions for meaningful and stable IL-$1\beta$1β-activation.
METHODS:We extracted the essential topology of the inflammasome pathway network using a linear chain of first-order reaction and a second-order reaction for inhibitory feedback. We then performed an analytical treatment of the resulting ODE set to obtain closed-form formulae. We therefore looked for the steady states and characterized their stability by using a Jacobian-based, local analysis. We employed the Small Gain Theorem from control Theory as recently applied by us [2] and the Gershgorin Circle Theorem to obtain mathematically exact conditions for a positive ON state and stabilities for ON and OFF steady states.
RESULTS:We identified an ON- and one OFF- steady state whose properties we characterized in terms of the kinetic parameters by closed-form formulae. We found that under the assumption of a first-order information flow through the network, the existence of a biologically reasonable ON steady state required the simultaneous presence of the positive and the negative feedback. Assuming non-competitivity between IL-$1\beta$1β entities binding to different receptors, we found that a minimum kinetics for protein production is required to sustain a steady state with IL-$1\beta$1β activation. Assuming competitivity between IL-$1\beta$1β entities introduced additio
The number of stroke cases has increased dramatically in the last 30 years, and more and more people are left disabled because of stroke. It is vital to continue researching new ways to recover and improve their condi...
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ISBN:
(数字)9798331532147
ISBN:
(纸本)9798331532154
The number of stroke cases has increased dramatically in the last 30 years, and more and more people are left disabled because of stroke. It is vital to continue researching new ways to recover and improve their condition. Rehabilitation therapies are based on intensive and repeated training starting as soon as possible. However, the number of therapists is too few to treat the growing number of stroke survivors. Advanced technologies such as virtual reality (VR) and robot-assisted therapies have been introduced to improve stroke rehabilitation. VR-based rehabilitation immerses patients in simulated environments, providing visual feedback miming real-world activities. This approach motivates patients through interactive tasks while engaging their cognitive processes, which is crucial for neuroplasticity and motor recovery. Robot-assisted therapy complements VR by providing precise, repetitive movements and proprioceptive feedback. This paper presents a virtual reality- based and robotic-assisted upper limb neuromotor recovery system. The system combines VR immersion with robotic assistance, allowing patients to receive real-time guidance and support during exercise. The system adapts to the patient's condition, providing personalized visual and physical feedback to help relearn motor skills.
The majority of recent works on robust MPC either require very burdensome online computations or are restricted to relatively small feasible regions. This paper builds on a recent work which demonstrated that one coul...
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The majority of recent works on robust MPC either require very burdensome online computations or are restricted to relatively small feasible regions. This paper builds on a recent work which demonstrated that one could compute the maximal admissible set for a linear parameter varying system and shows how this set can be used as the terminal region and hence allows the definition of an MPC algorithm requiring only quadratic programming, but with a maximal region of attraction and guaranteed convergence for the robust case.
Further results on hysteresis compensation using the inverse multiplicative structure of the rate-dependent Prandtl-Ishlinskii (RDPI) model are presented. The proposed model-based feedforward controller is used to com...
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ISBN:
(纸本)9781509045839
Further results on hysteresis compensation using the inverse multiplicative structure of the rate-dependent Prandtl-Ishlinskii (RDPI) model are presented. The proposed model-based feedforward controller is used to compensate for the hysteresis nonlinearities at different operating conditions without formulating the inverse model. The study investigates the compensation error and parameters uncertainties when the proposed compensator is applied for compensation of the rate-dependent hysteresis nonlinearities. The compensation results show that better performance can be achieved with low sampling time. The proposed compensator is further examined in a closed-loop control system to improve the tracking performance of a piezoelectric cantilevered actuator.
Increasingly stringent throughput requirements in the industry necessitate the need for lightweight design of high-precision motion systems to allow for high accelerations, while still achieving accurate positioning o...
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The videoscope (VS) images have poor quality and low contrast. Hence, in this paper, three proposed frameworks to improve the quality of VS images are presented. The first framework depends on contrast-limited adaptiv...
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The purpose of this communication is to show an additional advantage of the well known guide for start and stop modes, GEMMA, that should motivate its use as well as to introduce the consideration of the human operato...
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The purpose of this communication is to show an additional advantage of the well known guide for start and stop modes, GEMMA, that should motivate its use as well as to introduce the consideration of the human operator as an integral part of the automation procedure. The inclusion of the human operator as well as his interplay with the automation device needs some guidelines that can be drawn from joining the GEMMA structured approach and some concepts borrowed from cognitive ergonomic theory and human-computer interaction. Finally, this paper shows some examples of human-machine interfaces (industrial panel, interface display screen).
Growing demands in today’s industry results in increasingly stringent performance and throughput specifications. For accurate positioning of high-precision motion systems, feedforward control plays a crucial role. No...
Growing demands in today’s industry results in increasingly stringent performance and throughput specifications. For accurate positioning of high-precision motion systems, feedforward control plays a crucial role. Nonetheless, conventional model-based feedforward approaches are no longer sufficient to satisfy the challenging performance requirements. An attractive method for systems with repetitive motion tasks is iterative learning control (ILC) due to its superior performance. However, for systems with non-repetitive motion tasks, ILC is generally not applicable, despite of some recent promising advances. In this paper, we aim to explore the use of deep learning to address the task flexibility constraint of ILC. For this purpose, a novel Task Analogy based Imitation Learning (TAIL)-ILC approach is developed. To benchmark the performance of the proposed approach, a simulation study is presented which compares the TAIL-ILC to classical model-based feedforward strategies and existing learning-based approaches, such as neural network based feedforward learning.
The indirect approach to continuous-time system identification consists in estimating continuous-time models by first determining an appropriate discrete-time model. For a zero-order hold sampling mechanism, this appr...
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