Today＇s automation industry is driven by the need for an increased productivity, higher flexibility, and higher individuality, and characterized by tailor-made and more complex control solutions. In the processing in...Today＇s automation industry is driven by the need for an increased productivity, higher flexibility, and higher individuality, and characterized by tailor-made and more complex control solutions. In the processing industry, logic controller design is often a manual, experience-based, and thus an error-prone procedure. Typically, the specifications are given by a set of informal requirements and a technical flowchart and both are used to be directly translated into the control code. This paper proposes a method in which the control program is constructed as a sequential function chart （SFC） by transforming the requirements via clearly defined intermediate formats. For the purpose of analysis, the resulting SFC can be translated algorithmically into timed automata. A rigorous verification can be used to determine whether all specifications are satisfied if a formal model of the plant is available which is then composed with the automata model of the logic controller （LC）.展开更多
μ-synthesis is a practical design approach and has been applied successfully to achieve a nominal and robust performance objectives. However, this design method suffers from the complexity of its practical implementa...μ-synthesis is a practical design approach and has been applied successfully to achieve a nominal and robust performance objectives. However, this design method suffers from the complexity of its practical implementation and high computational demand due to its high order dynamics. To overcome this problem, the interaction between fuzzy logic control which is a part of intelligence control theory and p-synthesis controller is carried out. This is called integrated fuzzy robust controller in this paper. It is obtained by coupling fuzzy pd with p-synthesis controller through the outer loop. Using this design strategy, we can keep the system performance and robustness even a high order p-synthesis controller is reduced into second order model. In order to test the effectiveness of this design method, the linear simulation results for a launch vehicle＇s attitude control motion are presented at the end of this paper.展开更多
本文描述了一种具有AI深度学习功能的PLC设计。该PLC采用瑞芯微的RK3588和中控微电子的CMC(Control Module on Chip)作为双核心,不仅支持IEC 61131-3标准的逻辑控制编程语言,也支持PLCopen标准的运动控制功能,同时还具有强大的AI算力,...本文描述了一种具有AI深度学习功能的PLC设计。该PLC采用瑞芯微的RK3588和中控微电子的CMC(Control Module on Chip)作为双核心,不仅支持IEC 61131-3标准的逻辑控制编程语言,也支持PLCopen标准的运动控制功能,同时还具有强大的AI算力,可广泛应用于自动化流水线、机器人控制等场景。展开更多
In this paper, a robust adaptive fuzzy dynamic surface control for a class of uncertain nonlinear systems is proposed. A novel adaptive fuzzy dynamic surface model is built to approximate the uncertain nonlinear funct...In this paper, a robust adaptive fuzzy dynamic surface control for a class of uncertain nonlinear systems is proposed. A novel adaptive fuzzy dynamic surface model is built to approximate the uncertain nonlinear functions by only one fuzzy logic system. The approximation capability of this model is proved and the model is implemented to solve the problem that too many approximators are used in the controller design of uncertain nonlinear systems. The shortage of ＂explosion of complexity＂ in backstepping design procedure is overcome by using the proposed dynamic surface control method. It is proved by constructing appropriate Lyapunov candidates that all signals of closed-loop systems are semi-globally uniformly ultimate bounded. Also, this novel controller stabilizes the states of uncertain nonlinear systems faster than the adaptive sliding mode controller （SMC）. Two simulation examples are provided to illustrate the effectiveness of the control approach proposed in this paper.展开更多
基金the European Union through the Network of Excellence Hybrid Control (HYCON) under contract IST-511368.
文摘Today＇s automation industry is driven by the need for an increased productivity, higher flexibility, and higher individuality, and characterized by tailor-made and more complex control solutions. In the processing industry, logic controller design is often a manual, experience-based, and thus an error-prone procedure. Typically, the specifications are given by a set of informal requirements and a technical flowchart and both are used to be directly translated into the control code. This paper proposes a method in which the control program is constructed as a sequential function chart （SFC） by transforming the requirements via clearly defined intermediate formats. For the purpose of analysis, the resulting SFC can be translated algorithmically into timed automata. A rigorous verification can be used to determine whether all specifications are satisfied if a formal model of the plant is available which is then composed with the automata model of the logic controller （LC）.
文摘μ-synthesis is a practical design approach and has been applied successfully to achieve a nominal and robust performance objectives. However, this design method suffers from the complexity of its practical implementation and high computational demand due to its high order dynamics. To overcome this problem, the interaction between fuzzy logic control which is a part of intelligence control theory and p-synthesis controller is carried out. This is called integrated fuzzy robust controller in this paper. It is obtained by coupling fuzzy pd with p-synthesis controller through the outer loop. Using this design strategy, we can keep the system performance and robustness even a high order p-synthesis controller is reduced into second order model. In order to test the effectiveness of this design method, the linear simulation results for a launch vehicle＇s attitude control motion are presented at the end of this paper.
文摘本文描述了一种具有AI深度学习功能的PLC设计。该PLC采用瑞芯微的RK3588和中控微电子的CMC(Control Module on Chip)作为双核心,不仅支持IEC 61131-3标准的逻辑控制编程语言,也支持PLCopen标准的运动控制功能,同时还具有强大的AI算力,可广泛应用于自动化流水线、机器人控制等场景。
基金supported by National Natural Science Foundation of China (No. 60525303 and 60704009)Key Research Program of Hebei Education Department (No. ZD200908)
文摘In this paper, a robust adaptive fuzzy dynamic surface control for a class of uncertain nonlinear systems is proposed. A novel adaptive fuzzy dynamic surface model is built to approximate the uncertain nonlinear functions by only one fuzzy logic system. The approximation capability of this model is proved and the model is implemented to solve the problem that too many approximators are used in the controller design of uncertain nonlinear systems. The shortage of ＂explosion of complexity＂ in backstepping design procedure is overcome by using the proposed dynamic surface control method. It is proved by constructing appropriate Lyapunov candidates that all signals of closed-loop systems are semi-globally uniformly ultimate bounded. Also, this novel controller stabilizes the states of uncertain nonlinear systems faster than the adaptive sliding mode controller （SMC）. Two simulation examples are provided to illustrate the effectiveness of the control approach proposed in this paper.
