High resolution mass spectrometry in combination with distillation and SARA fractionation provides us an opportunity for in-depth understanding about the hydrotreating process at the molecular level. In this study, th...High resolution mass spectrometry in combination with distillation and SARA fractionation provides us an opportunity for in-depth understanding about the hydrotreating process at the molecular level. In this study, the atmospheric residue derived from Arabian heavy crude and its hydrotreated products were initially subjected to distillation and SARA fractionation. The saturates were characterized by GC FI/FD TOF MS. The aromatics and resins were characterized by APPI FT-ICR MS. Compositional changes of different compounds (paraffins, naphthenes, aromatic hydrocarbons, and heteroatomic compounds) contained in different distillates (vacuum gas oil, vacuum residue) were obtained. More detailed knowledge about the hydrotreating process was achieved.展开更多
In this paper, a parallel fuzzy proportional plus fuzzy integral plus fuzzy derivative （FP＋FI＋FD） controller is proposed. It is derived from the conventional parallel proportional-integral-derivative （PID） contr...In this paper, a parallel fuzzy proportional plus fuzzy integral plus fuzzy derivative （FP＋FI＋FD） controller is proposed. It is derived from the conventional parallel proportional-integral-derivative （PID） controller. It preserves the linear structure of a conventional parallel PID controller, with analytical formulas. The final shape of the controller is a discrete-time fuzzy version of a conventional parallel PID controller. Computer simulations are performed to evaluate the performance of the FP＋FI＋FD controller for setpoint tracking and load-disturbance rejection for some complex processes, such as first- and second-order processes with delay, inverse response process with and without delay and higher order processes. Also, the performance of the proposed fuzzy controller is evaluated experimentally on highly nonlinear liquid-flow process with a hysteresis characteristic due to a pneumatic control valve. The simulation and real time control is done using National InstrumentTM hardware and software （LabVIEWTM）. The response of the FP＋FI＋FD controller is compared with the conventional parallel PID controller, tuned with the Ziegler-Nichols （Z-H） and /~strSm- H^gglund （A-H） tuning technique. It is observed that the FP＋FI＋FD controller performed much better than the conventional PI/PID controller. Simulation and experimental results demonstrate the effectiveness of the proposed parallel FP＋FI＋FD controller.展开更多
The study presented in this paper is in continuation with the paper published by the authors on parallel fuzzy proportional plus fuzzy integral plus fuzzy derivative （FP ＋ FI ＋ FD） controller. It addresses the sta...The study presented in this paper is in continuation with the paper published by the authors on parallel fuzzy proportional plus fuzzy integral plus fuzzy derivative （FP ＋ FI ＋ FD） controller. It addresses the stability analysis of parallel FP ＋ FI ＋ FD controller. The famous＂small gain theorem＂ is used to study the bounded-input and bounded-output （BIBO） stability of the fuzzy controller. Sufficient BIBO-stability conditions are developed for parallel FP ＋ FI ＋ FD controller. FP ＋ FI ＋ FD controller is derived from the conventional parallel proportional plus integral plus derivative （PID） controller. The parallel FP ＋ FI ＋ FD controller is actually a nonlinear controller with variable gains. It shows much better set-point tracking, disturbance rejection and noise suppression for nonlinear processes as compared to conventional PID controller.展开更多
The paper addresses the adaptive behaviour of parallel fuzzy proportional plus fuzzy integral plus fuzzy derivative (FP+FI+FD) controller. The parallel FP+FI+FD controller is actually a non-linear adaptive controller ...The paper addresses the adaptive behaviour of parallel fuzzy proportional plus fuzzy integral plus fuzzy derivative (FP+FI+FD) controller. The parallel FP+FI+FD controller is actually a non-linear adaptive controller whose gain changes continuously with output of the process under control. Two non-stationary processes, whose characteristics change with time, are considered for simulation study. Simulation is performed using software LabVIEW TM . The set-point tracking response of parallel FP+FI+FD is compared with conventional parallel proportional plus integral plus derivative (PID) controller, tuned with the Ziegler-Nichols (Z-N) tuning technique. Simulation results show that conventional PID controller fails to track the set-point and becomes unstable as the process changes its characteristic with time. But the parallel FP+FI+FD controller shows considerably much better set-point tracking response and does not deviate from steady state. Also, a huge spike is observed in the output of PID controller as the reference set-point and process parameters are changed, while the FP+FI+FD controller gives spike free control signal.展开更多
In this paper, a robust fractional order fuzzy P ＋ fuzzy I ＋ fuzzy D （FOFP ＋ FOFI ＋ FOFD） controller is presented for a nonlinear and uncertain 2-1ink planar rigid manipulator. It is a nonlinear fuzzy controller...In this paper, a robust fractional order fuzzy P ＋ fuzzy I ＋ fuzzy D （FOFP ＋ FOFI ＋ FOFD） controller is presented for a nonlinear and uncertain 2-1ink planar rigid manipulator. It is a nonlinear fuzzy controller with variable gains that makes it self- adjustable or adaptive in nature. The fractional order operators further make it more robust by providing additional degrees of freedom to the design engineer. The integer order counterpart, fuzzy P ＋ fuzzy I ＋ fuzzy D （FP ＋ FI ＋ FD） controller, for a comparative study, was realized by taking the integer value for the fractional order operators in FOFP ＋ FOFI ＋ FOFD controller. The performances of both the fuzzy controllers are evaluated for reference trajectory tracking and disturbance rejection with and without model uncertainty and measurement noise. Genetic algorithm was used to optimize the parameters of controller under study for minimum integral of absolute error. Simulation results demonstrated that FOFP ＋ FOFI ＋ FOFD controller show much better performance as compared to its counterpart FP ＋ FI ＋ FD controller in servo as well as the regulatory problem and in model uncertainty and noisy environment FOFP ＋ FOFI ＋ FOFD controller demonstrated more robust behavior as compared to the FP ＋ FI ＋ FD controller. For the developed controller bounded-input and bounded-output stability conditions are also developed using Small Gain Theorem.展开更多
基金supported by the National Basic Research Program of China (2010CB226901)
文摘High resolution mass spectrometry in combination with distillation and SARA fractionation provides us an opportunity for in-depth understanding about the hydrotreating process at the molecular level. In this study, the atmospheric residue derived from Arabian heavy crude and its hydrotreated products were initially subjected to distillation and SARA fractionation. The saturates were characterized by GC FI/FD TOF MS. The aromatics and resins were characterized by APPI FT-ICR MS. Compositional changes of different compounds (paraffins, naphthenes, aromatic hydrocarbons, and heteroatomic compounds) contained in different distillates (vacuum gas oil, vacuum residue) were obtained. More detailed knowledge about the hydrotreating process was achieved.
文摘In this paper, a parallel fuzzy proportional plus fuzzy integral plus fuzzy derivative （FP＋FI＋FD） controller is proposed. It is derived from the conventional parallel proportional-integral-derivative （PID） controller. It preserves the linear structure of a conventional parallel PID controller, with analytical formulas. The final shape of the controller is a discrete-time fuzzy version of a conventional parallel PID controller. Computer simulations are performed to evaluate the performance of the FP＋FI＋FD controller for setpoint tracking and load-disturbance rejection for some complex processes, such as first- and second-order processes with delay, inverse response process with and without delay and higher order processes. Also, the performance of the proposed fuzzy controller is evaluated experimentally on highly nonlinear liquid-flow process with a hysteresis characteristic due to a pneumatic control valve. The simulation and real time control is done using National InstrumentTM hardware and software （LabVIEWTM）. The response of the FP＋FI＋FD controller is compared with the conventional parallel PID controller, tuned with the Ziegler-Nichols （Z-H） and /~strSm- H^gglund （A-H） tuning technique. It is observed that the FP＋FI＋FD controller performed much better than the conventional PI/PID controller. Simulation and experimental results demonstrate the effectiveness of the proposed parallel FP＋FI＋FD controller.
文摘The study presented in this paper is in continuation with the paper published by the authors on parallel fuzzy proportional plus fuzzy integral plus fuzzy derivative （FP ＋ FI ＋ FD） controller. It addresses the stability analysis of parallel FP ＋ FI ＋ FD controller. The famous＂small gain theorem＂ is used to study the bounded-input and bounded-output （BIBO） stability of the fuzzy controller. Sufficient BIBO-stability conditions are developed for parallel FP ＋ FI ＋ FD controller. FP ＋ FI ＋ FD controller is derived from the conventional parallel proportional plus integral plus derivative （PID） controller. The parallel FP ＋ FI ＋ FD controller is actually a nonlinear controller with variable gains. It shows much better set-point tracking, disturbance rejection and noise suppression for nonlinear processes as compared to conventional PID controller.
文摘The paper addresses the adaptive behaviour of parallel fuzzy proportional plus fuzzy integral plus fuzzy derivative (FP+FI+FD) controller. The parallel FP+FI+FD controller is actually a non-linear adaptive controller whose gain changes continuously with output of the process under control. Two non-stationary processes, whose characteristics change with time, are considered for simulation study. Simulation is performed using software LabVIEW TM . The set-point tracking response of parallel FP+FI+FD is compared with conventional parallel proportional plus integral plus derivative (PID) controller, tuned with the Ziegler-Nichols (Z-N) tuning technique. Simulation results show that conventional PID controller fails to track the set-point and becomes unstable as the process changes its characteristic with time. But the parallel FP+FI+FD controller shows considerably much better set-point tracking response and does not deviate from steady state. Also, a huge spike is observed in the output of PID controller as the reference set-point and process parameters are changed, while the FP+FI+FD controller gives spike free control signal.
文摘In this paper, a robust fractional order fuzzy P ＋ fuzzy I ＋ fuzzy D （FOFP ＋ FOFI ＋ FOFD） controller is presented for a nonlinear and uncertain 2-1ink planar rigid manipulator. It is a nonlinear fuzzy controller with variable gains that makes it self- adjustable or adaptive in nature. The fractional order operators further make it more robust by providing additional degrees of freedom to the design engineer. The integer order counterpart, fuzzy P ＋ fuzzy I ＋ fuzzy D （FP ＋ FI ＋ FD） controller, for a comparative study, was realized by taking the integer value for the fractional order operators in FOFP ＋ FOFI ＋ FOFD controller. The performances of both the fuzzy controllers are evaluated for reference trajectory tracking and disturbance rejection with and without model uncertainty and measurement noise. Genetic algorithm was used to optimize the parameters of controller under study for minimum integral of absolute error. Simulation results demonstrated that FOFP ＋ FOFI ＋ FOFD controller show much better performance as compared to its counterpart FP ＋ FI ＋ FD controller in servo as well as the regulatory problem and in model uncertainty and noisy environment FOFP ＋ FOFI ＋ FOFD controller demonstrated more robust behavior as compared to the FP ＋ FI ＋ FD controller. For the developed controller bounded-input and bounded-output stability conditions are also developed using Small Gain Theorem.
