Performance Enhancement of Pneumatic Vibration Isolators Using Self-Tuning PID Feedback and Time-Delay-Control (TDC)-Based Feedforward Scheme

2018 ◽  
Author(s):  
Jin-Wei Liang ◽  
Hung-Yi Chen ◽  
Lyu-Cyuan Zeng
Keyword(s):  
Mathematical Model ◽  
Performance Enhancement ◽  
Control Method ◽  
Hybrid Control ◽  
Model Performance ◽  
Experimental Investigations ◽  
Isolation System ◽  
Control Scheme ◽  
Self Tuning ◽  
Hybrid Control Scheme

A hybrid control scheme that combines a self-tuning PID-feedback loop and TDC-based feedforward scheme is proposed in this study to cope with an active pneumatic vibration isolator. In order to establish an effective TDC feedforward control a reliable mathematical model of the pneumatic isolator is required and developed firstly. Numerical and experimental investigations on the validity of the mathematical model are performed. It is found that although slight discrepancy exists between predicted and observed behaviors of the system, the overall model performance is acceptable. The resultant model is then applied in the design of the TDC feedforward scheme. A neuro-based adaptive PID control is integrated with the TDC feedforward algorithm to form the hybrid control. Numerical and experimental isolation tests are carried out to examine the suppression performances of the proposed hybrid control scheme. The results show that the proposed hybrid control method outperforms solely TDC feedforward while the latter outperforms the passive isolation system. Moreover, the proposed hybrid control scheme can suppress the vibration near the system’s resonance.

P-CMAC-Based Control Method and its Application in Filament Tension Control

2010 ◽  
Vol 33 ◽  
pp. 101-104
Author(s):  
D.X. Chen ◽  
G. Wang
Keyword(s):  
Neural Network ◽  
Pid Controller ◽  
Fuzzy Inference ◽  
Control Method ◽  
Hybrid Control ◽  
Tracking Error ◽  
Tension Control ◽  
Approximation Accuracy ◽  
Control Scheme ◽  
Hybrid Control Scheme

Cerebella Model Articulation Controller (CMAC) is considered as local association and generalization neural network. Parametric CMAC (P-CMAC) is a modification to the original CMAC. The introduction of continuous activation function applied in the input space can overcome the binary behavior of the original CMAC. Takagi-Sugeno(TS) type fuzzy inference is embedded in the internal mapping to improve the approximation accuracy. Hybrid control scheme, which combines P-CMAC neural network and traditional PID controller, is proposed in the paper. The output of P-CMAC network dominates the overall control signal applied to the plant, while the traditional PID controller serves as compensator for reducing tracking error. The application of hybrid control scheme to filament tension control is illustrated. The experimental results have shown the effectiveness and accuracy improvement of the control scheme.

scholarly journals A Novel Control Approach to Hybrid Multilevel Inverter for High-Power Applications

Energies ◽  
2021 ◽  
Vol 14 (15) ◽  
pp. 4563
Author(s):  
Muhammad Ali ◽  
Ghulam Hafeez ◽  
Ajmal Farooq ◽  
Zeeshan Shafiq ◽  
Faheem Ali ◽  
...  
Keyword(s):  
Control Method ◽  
Hybrid Control ◽  
Low Voltage ◽  
Harmonic Distortion ◽  
Multilevel Inverter ◽  
Computationally Efficient ◽  
Matlab Simulink ◽  
Control Approach ◽  
Control Scheme ◽  
Hybrid Control Scheme

This paper proposes a hybrid control scheme for a newly devised hybrid multilevel inverter (HMLI) topology. The circuit configuration of HMLI is comprised of a cascaded converter module (CCM), connected in series with an H-bridge converter. Initially, a finite set model predictive control (FS-MPC) is adopted as a control scheme, and theoretical analysis is carried out in MATLAB/Simulink. Later, in the real-time implementation of the HMLI topology, a hybrid control scheme which is a variant of the FS-MPC method has been proposed. The proposed control method is computationally efficient and therefore has been employed to the HMLI topology to mitigate the high-frequency switching limitation of the conventional MPC. Moreover, a comparative analysis is carried to illustrate the advantages of the proposed work that includes low switching losses, higher efficiency, and improved total harmonic distortion (THD) in output current. The inverter topology and stability of the proposed control method have been validated through simulation results in MATLAB/Simulink environment. Experimental results via low-voltage laboratory prototype have been added and compared to realize the study in practice.

scholarly journals Electronic Differential and Neuro-Fuzzy Sliding Mode Control with Extended State Observer for an Electric Vehicle System

2018 ◽  
Vol 61 ◽  
pp. 00007
Author(s):  
Ibrahim Farouk Bouguenna ◽  
Ahmed Azaiz ◽  
Ahmed Tahour ◽  
Ahmed Larbaoui
Keyword(s):  
Sliding Mode Control ◽  
Hybrid Control ◽  
Sliding Mode ◽  
Current Loop ◽  
Fuzzy Sliding Mode Control ◽  
Mode Control ◽  
Neuro Fuzzy ◽  
Control Scheme ◽  
Fuzzy Sliding Mode ◽  
Hybrid Control Scheme

In this paper a neuro-fuzzy-sliding mode control (NFSMC) with extended state observer (ESO) technique; is designed to guarantee the traction of an electric vehicle with two distinct permanent magnet synchronous motor (PMSM). Each PMSM systems (source-convertermotor) are attached to an electronic differential (ED), in order to adjust the senses of direction of the vehicle, and sustain a stable speed by adapting the difference in velocity of each motor-wheel according to the direction in the case of a turn. Two types of controllers are employed by a hybrid control scheme to assure the control and the performance of the vehicle. This hybrid control scheme guarantees the stability of the vehicle by ED, reduces the chattering phenomena in the PMSM electric motor, and improves the disturbance rejection ability which employs tow types of controllers. The neuro-fuzzy sliding mode control on the direct current loop and ESO controller on the speed loop, and the quadratic current loop; taking into account the dynamic of the vehicle. Simulation runs under Matlab/Simulink to assess the efficiency, and strength of the recommended control method on the closed loop system.

scholarly journals Transient stability control by means of under-frequency load shedding and a hybrid control scheme

2017 ◽  
Vol 28 (4) ◽  
Author(s):  
P. F. Le Roux ◽  
R.C. Bansal
Keyword(s):  
Transient Stability ◽  
Hybrid Control ◽  
Stability Control ◽  
Load Shedding ◽  
Electrical Network ◽  
Traditional Methods ◽  
Transient Fault ◽  
System A ◽  
Control Scheme ◽  
Hybrid Control Scheme

An electrical network constantly faces unforeseen events such as faults on lines, loss of load and loss of generation. Under-frequency load shedding and generator tripping are traditional methods used to stabilise a network when a transient fault occurs. These methods will prevent any network instability by shedding load or tripping the most critical generator at a calculated time when required. By executing these methods, the network can be stabilised in terms of balancing the generation and the load of a power system. A hybrid control scheme is proposed where the traditional methods are combined to reduce the stress levels exerted on the network and to minimise the load to be shed.

Hybrid Control Scheme for Anaerobic Digestion in a CSTR-UASB Reactor System

2020 ◽  
Vol 13 (3) ◽  
Author(s):  
Atthasit Tawai ◽  
Kanyarat Kitsubthawee ◽  
Chanin Panjapornpon ◽  
Weiming Shao
Keyword(s):  
Anaerobic Digestion ◽  
Hybrid Control ◽  
Reactor System ◽  
Uasb Reactor ◽  
Control Scheme ◽  
Hybrid Control Scheme

Joint Self-Tuning With Cartesian Setpoints

1986 ◽  
Vol 108 (2) ◽  
pp. 146-150 ◽  
Author(s):  
P. G. Backes ◽  
G. G. Leininger ◽  
Chun-Hsien Chung
Keyword(s):  
Real Time ◽  
Control Method ◽  
Hybrid Control ◽  
Pole Placement ◽  
Real Time Control ◽  
Time Control ◽  
Self Tuning ◽  
Cause Of Error ◽  
Time Position ◽  
Manipulator Control

A joint coordinate self-tuning manipulator control method is presented which uses Cartesian setpoints. The method is capable of both position and hybrid control. Position and force errors are transformed from Cartesian coordinates to position and force errors at the joints. The position and force errors at each joint are combined into one hybrid error that is eliminated using pole-placement self-tuning. Real time position and hybrid control results are given. No prior knowledge of manipulator or load dynamics is required and real time control results show that the goal of consistent control with changing load dynamics is achieved. The major cause of error in position and hybrid control is the large friction effects in the joints.

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