Communication bandwidth and network topology are two important factors that affect performance of distributed consensus in multi-agent *** available works about quantized average consensus assume that the adjacency ma...
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Communication bandwidth and network topology are two important factors that affect performance of distributed consensus in multi-agent *** available works about quantized average consensus assume that the adjacency matrices associated with the digraphs are doubly stochastic,which amounts to that the digital networks are ***,this assumption may be unrealistic in *** this paper,without assuming double stochasticity,the authors revisit an existing quantized average consensus protocol with the logarithmic quantization scheme,and investigate the quantized consensus problem in general directed digital networks that are strongly connected but not necessarily *** authors first derive an achievable upper bound of the quantization precision parameter to design suitable logarithmic quantizer,and this bound explicitly depends on network ***,by means of the matrix transformation and the Lyapunov techniques,the authors provide a testable condition under which the weighted average consensus can be achieved with the proposed quantized protocol.
This paper focus on dynamic visual seroving of a cable-driven soft robotic manipulator system. The soft robotic manipulator has no rigid structure. Based on Lagrange mechanics, kinetic energy, elastic potential energy...
This paper focus on dynamic visual seroving of a cable-driven soft robotic manipulator system. The soft robotic manipulator has no rigid structure. Based on Lagrange mechanics, kinetic energy, elastic potential energy and gravitational potential energy of each segment are analyzed, thus general dynamic equation of the soft robotic manipulator is obtained. On this basis, a depth-independent image Jacobian matrix is presented and an image-based visual servo controller is designed. Applied by adaptive algorithm, the controller could estimate unknown 3D feature positions online, and Lyapunov method is involved to prove the stability of the system. Experiments are conducted to demonstrate reasonableness and validity of dynamic model of the soft robotic manipulator and image-based adaptive visual servo controller.
As batches operate at different statuses across different phases, it can be advantageous to partition the whole batch process into different phases and characterize them separately by multiple local phase models. The ...
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ISBN:
(纸本)9781467355322
As batches operate at different statuses across different phases, it can be advantageous to partition the whole batch process into different phases and characterize them separately by multiple local phase models. The conventional clustering-based phase division algorithm overlooks the time sequence of batch operation which thus may mix different time segments located within a batch into one phase. Moreover, it is hard to capture the transitions between neighboring phases. In the present work, an automatic step-wise sequential phase division algorithm is developed to capture the changes of process characteristics along time direction within each batch. Its theoretical support is framed and the related statistical characteristics are analyzed. Using this algorithm, major phases are captured and the transition regions are separated from them as separate time regions. Thus, different statistical models are developed to reflect their time-varying characteristics. The online monitoring system is set up, which can realtime judge the affiliation of each new sample and check its status by adopting the proper statistical model. Comprehensive comparison is conducted between the proposed algorithm and clustering-based phase division algorithm. Its feasibility and performance are illustrated by an injection molding process which presents typical multiphase nature as well as transition characteristics.
In this paper, we consider the control of large-scale processes with both input and state couplings. A distributed model predictive control(MPC) strategy for tracking based on the reference trajectories is presented. ...
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ISBN:
(纸本)9781479947249
In this paper, we consider the control of large-scale processes with both input and state couplings. A distributed model predictive control(MPC) strategy for tracking based on the reference trajectories is presented. The proposed distributed MPC strategy requires decomposing a large-scale system into several smaller ones and solving convex optimization problems independently. Distributed MPC tracking strategies for unconstrained and constrained processes are presented, respectively. An iterative algorithm is presented to coordinate the distributed MPC controllers. The proposed algorithm is applied to a four-tank process to demonstrate the effectiveness.
This paper considers reset controlsystems with output *** present sufficient conditions for the quadratic stability and finite L2 gain ***,the results are extended to piecewise quadratic stability which is much less ...
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ISBN:
(纸本)9781479947249
This paper considers reset controlsystems with output *** present sufficient conditions for the quadratic stability and finite L2 gain ***,the results are extended to piecewise quadratic stability which is much less ***,an iterative algorithm is proposed to design the reset *** the obtained results are given as linear matrix inequalities(LMIs) that can be solved *** examples are given to illustrate the results.
Fractional order proportional-integral-derivative (FOPID) controller generalizes the standard PID controller. Compared to PID controller, FOPID controller has more parameters and the tuning of parameters is more compl...
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Fractional order proportional-integral-derivative (FOPID) controller generalizes the standard PID controller. Compared to PID controller, FOPID controller has more parameters and the tuning of parameters is more complex. In this paper, an improved artificial bee colony algorithm, which combines cyclic exchange neighborhood with chaos (CNC-ABC), is proposed for the sake of tuning the parameters of FOPID controller. The characteristic of the proposed CNC-ABC exists in two folds: one is that it enlarges the search scope of the solution by utilizing cyclic exchange neighborhood techniques, speeds up the convergence of artificial bee colony algorithm (ABC). The other is that it has potential to get out of local optima by exploiting the ergodicity of chaos. The proposed CNC-ABC algorithm is used to optimize the parameters of the FOPID controller for an automatic voltage regulator (AVR) system. Numerical simulations show that the CNC-ABC FOPID controller has better performance than other FOPID and PID controllers.
Spectrum sharing is a promising technique responsible for providing efficient and fair spectrum allocation. Considering the unevenness phenomenon of spectrum usage in industrial wireless networks, a novel spectrum sha...
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Spectrum sharing is a promising technique responsible for providing efficient and fair spectrum allocation. Considering the unevenness phenomenon of spectrum usage in industrial wireless networks, a novel spectrum sharing scheme, in the framework of industrial cognitive radio network (ICRN), is proposed in this paper via an autonomous switching technique to equalize the spectrum usage and increase the spectrum access possibility of new requests. The autonomous switching technique borrows the idea from the fact that specific collective motion can be achieved by local actions of individuals in many biological systems. The accessed nodes sense the limited spectrum range around their central frequency and then make the decision of channel switching autonomously. Several sensing report based rules are presented to facilitate the switching decision in order to equalize the channel usage among the sensing range of each node. It is demonstrated that by using these rules the spectrum usage becomes more even, and thus the spectrum utilization and fairness are both improved. Numerical examples are given to show the effectiveness of the proposed spectrum sharing scheme.
This paper focuses on the load shifting problem in a household scenario with a large-capacity battery. We propose a novel Model Predictive control (MPC) framework to control the charge/discharge power of battery, he...
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ISBN:
(纸本)9781467355339
This paper focuses on the load shifting problem in a household scenario with a large-capacity battery. We propose a novel Model Predictive control (MPC) framework to control the charge/discharge power of battery, hence to shave the peak load. Being different from other studies, the framework is designed on the base of individual habit of energy consumption, as it is envisioned that the individual habit is critical for choosing the suitable energy services. In this paper, the habit is modeled as a Markov process and gradually learned by an iterative algorithm;thus, the habit can be utilized for the prediction of future energy consumption. Then, the rolling optimization is applied for the optimal control of the charge/discharge power of battery. It is shown by numerical simulations that the proposed approach can significantly reduce the peak load.
In this paper, T-G-P model is built to find maximum power point according to light intensity and temperature, making it easier and more clearly for photovoltaic system to track the MPP. A predictive controller conside...
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As well-known, model predictive control is closely related to optimal control. This paper studies relationships between them and provides a unified framework for optimality analysis of model predictive controllers (MP...
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As well-known, model predictive control is closely related to optimal control. This paper studies relationships between them and provides a unified framework for optimality analysis of model predictive controllers (MPC). The optimality is evaluated by comparing total performance of MPC with finite and infinite horizon optimal cost. Based on relaxed value iteration method, upper and lower bounds of optimality evaluation functions are expressed explicitly in terms of optimization horizon. These results reveal detailed characteristics on performance of closed-loop MPC systems due to using “receding horizon optimization” implementation style.
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