This article proposes a finite-time proportional-integral-derivative(FT-PID) control method to fast stabilize the control system to achieve the desired performance within the predesignated time *** a considered nonaff...
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This article proposes a finite-time proportional-integral-derivative(FT-PID) control method to fast stabilize the control system to achieve the desired performance within the predesignated time *** a considered nonaffined nonlinear system, we develop a new dynamic linearization approach to reformulate the system model as a linear data model(LDM) whose arguments are consistent with that used in the PID control law. Then, a projection algorithm is presented to estimate the unknown pseudo gradient vector of the LDM. Subsequently, an adaptive tuning algorithm is designed to update the three PID parameters by solving linear matrix inequalities in terms of the predesignated error precision and the finite-time instant. The finite-time convergence of the proposed FT-PID control system is shown mathematically, which guarantees a pre-specified error precision to be achieved within the predesignated finite-time instants. As a result, not only can the proposed FT-PID control save the control cost but it also improves the production efficiency. The simulation study verifies the results.
A novel dual-channel dynamic event-triggered model-free adaptive control method with compensation is proposed for nonlinear networked control systems (NCSs) subjected to random packet loss. In order to tackle the issu...
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A novel dual-channel dynamic event-triggered model-free adaptive control method with compensation is proposed for nonlinear networked control systems (NCSs) subjected to random packet loss. In order to tackle the issue of redundant data transmission, a dual-channel triggering control framework is designed, where data transmission only occurs upon meeting the triggering conditions. Compared with the traditional static event-triggered schemes with fixed triggering thresholds, the proposed method allows for dynamically adjustable triggering thresholds. This means that the number of data transmissions in the forward and feedback channels can be further reduced. In addition, considering the detrimental impact of random packet loss and output event-triggered on the system, compensation is applied to the system's output data using the linear data model of the nonlinear system, which is directly derived from I/O data without incorporating any other mechanistic model information, thereby ensuring optimal control performance. In contrast to existing results, the proposed control strategy can enhance system performance while conserving network communication resources. The effectiveness and superiority of the proposed scheme have been validated through two simulations.
作者：
Chen, GuangjunDong, JiuxiangNortheastern Univ
Coll Informat Sci & Engn Shenyang 110819 Peoples R China Northeastern Univ
Coll Informat Sci & Engn State Key Lab Synthet Automat Proc Ind Minist Educ China Shenyang 110819 Peoples R China Northeastern Univ
Key Lab Vibrat & Control Aeroprop Syst Minist Educ China Shenyang 110819 Peoples R China
The problem of data-driven control (DDC) for nonlinear systems with dual-channel event-triggering is investigated in this brief. First, the nonlinear system is converted into a dynamic linearized datamodel using the ...
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The problem of data-driven control (DDC) for nonlinear systems with dual-channel event-triggering is investigated in this brief. First, the nonlinear system is converted into a dynamic linearized datamodel using the local dynamic linearization techniques. Then, a new dual-channel triggered control framework is designed based on the transformed linearized datamodel, and semi-independent dynamic event-triggered strategies are designed for the two channels of control input and measurement output. Different from the traditional single-channel event triggered, the main advantages of the proposed control strategy are that the input and output channels are semi-independently triggered, and it can accomplish the tracking control objectives by relying only on the input and output data of the system, and reducing the communication frequency of the input and output channels while ensuring stability. Finally, the effectiveness of the developed dual-channel event-triggered control strategy is verified by the application experiments.
A data-driven iterative learning control (DDILC) method is proposed for the control of the internal mixer temperature (IMT) system with high complex dynamics. First, the dynamic relationships between plate heat exchan...
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ISBN:
(纸本)9798350321050
A data-driven iterative learning control (DDILC) method is proposed for the control of the internal mixer temperature (IMT) system with high complex dynamics. First, the dynamic relationships between plate heat exchanger and electrical exchanger of IMT system is described as a state space model. Then, by using the iterative dynamic linearization tool, the IMT system is transformed into an iterative linear incremental model without neglecting any unmodeled dynamics, where the unknown time-varying parameters are estimated in real-time with the use of only I/O data of IMT system. An event triggering strategy is further incorporated into the proposed DDILC to reduce the number of controller executions and save computation cost. Finally, the simulation study on IMT system verifies the applicability of the proposed DDILC.
In this work, an enhanced data-driven optimal iterative learning control (eDDOILC) is proposed for nonlinear nonaffine systems where a new iterative sliding mode surface (ISMS) is designed to replace the traditional t...
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In this work, an enhanced data-driven optimal iterative learning control (eDDOILC) is proposed for nonlinear nonaffine systems where a new iterative sliding mode surface (ISMS) is designed to replace the traditional tracking error in the controller design and analysis. It is the first time to extend the sliding mode surface to the iteration domain for systems operate repetitively over a finite time interval. By virtual of the new designed ISMS, the control design becomes more flexible where both the time and the iteration dynamics can be taken into account. Before proceeding to the controller design, an iterative dynamic linear data model is built between two consecutive iterations to formulate the linear input-output data relationship of the repetitive nonlinear nonaffine discrete-time system. The linear data model is virtual and does not have any physical meanings, which is very different to the traditional mechanism mathematical model. In the sequel, the eDDOILC is proposed by designing an objective function with respect to the proposed two-dimensional ISMS. Rigorous proof is provided to show the convergence of the proposed eDDOILC method. Furthermore, the results have been extended to a multiple-input multiple-output (MIMO) nonaffine nonlinear discrete-time repetitive system. In general, the proposed eDDOILC is data-driven where no explicit model information is included. It is illustrated that the presented eDDOILC is effective when applied to the nonlinear nonaffine uncertain systems.
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