Abstract: Design of membership function ranges in fuzzy logic control (FLC) is presented for robust control of a variable speed refrigeration system (VSRS). The criterion values of the membership function ranges can be carried out from the static experimental data, and two different values are offered to compare control performance. Some simulations and real experiments for the VSRS were conducted to verify the validity of the designed membership functions. The experimental results showed good agreement with the simulation results, and the error change rate and its sampling time strongly affected the control performance at transient state of the VSRS.
Abstract: This paper presents the effect of the orbit inclination
on the pointing error of the satellite antenna and consequently on its
footprint on earth for a typical Ku- band payload system. The performance assessment is examined using both analytical
simulations and practical measurements, taking into account all the
additional sources of the pointing errors, such as East-West station
keeping, orbit eccentricity, and actual attitude control performance. An implementation and computation of the sinusoidal biases in
satellite roll and pitch used to compensate the pointing error of the
satellite antenna coverage is studied and evaluated before and after
the pointing corrections performed. A method for evaluation of the performance of the implemented
biases has been introduced through measuring satellite received level
from a mono-pulse tracking 11.1m transmitting antenna before and
after the implementation of the pointing corrections.
Abstract: At present, the cascade PID control is widely used to
control the superheating temperature (main steam temperature). As
Main Steam Temperature has the characteristics of large inertia, large
time-delay and time varying, etc., conventional PID control strategy
cannot achieve good control performance. In order to overcome the
bad performance and deficiencies of main steam temperature control
system, Model Free Adaptive Control (MFAC) - P cascade control
system is proposed in this paper. By substituting MFAC in PID of the
main control loop of the main steam temperature control, it can
overcome time delays, non-linearity, disturbance and time variation.
Abstract: In this paper, the stability analysis of a GA-Based adaptive fuzzy sliding model controller for a nonlinear system is discussed. First, a nonlinear plant is well-approximated and described with a reference model and a fuzzy model, both involving FLC rules. Then, FLC rules and the consequent parameter are decided on via an Evolved Bat Algorithm (EBA). After this, we guarantee a new tracking performance inequality for the control system. The tracking problem is characterized to solve an eigenvalue problem (EVP). Next, an adaptive fuzzy sliding model controller (AFSMC) is proposed to stabilize the system so as to achieve good control performance. Lyapunov’s direct method can be used to ensure the stability of the nonlinear system. It is shown that the stability analysis can reduce nonlinear systems into a linear matrix inequality (LMI) problem. Finally, a numerical simulation is provided to demonstrate the control methodology.
Abstract: This paper addresses the design of predictive
networked controller with adaptation of a communication delay. The
networked control system contains random delays from sensor to
controller and from controller to actuator. The proposed predictive
controller includes an adaptation loop which decreases the influence
of communication delay on the control performance. Also, the
predictive controller contains a filter which improves the robustness
of the control system. The performance of the proposed adaptive
predictive controller is demonstrated by simulation results in
comparison with PI controller and predictive controller with constant
delay.
Abstract: Nonlinear system identification is becoming an important tool which can be used to improve control performance. This paper describes the application of adaptive neuro-fuzzy inference system (ANFIS) model for controlling a car. The vehicle must follow a predefined path by supervised learning. Backpropagation gradient descent method was performed to train the ANFIS system. The performance of the ANFIS model was evaluated in terms of training performance and classification accuracies and the results confirmed that the proposed ANFIS model has potential in controlling the non linear system.
Abstract: Since the driving speed and control accuracy of
commercial optical disk are increasing significantly, it needs an
efficient controller to monitor the track seeking and following
operations of the servo system for achieving the desired data
extracting response. The nonlinear behaviors of the actuator and servo
system of the optical disk drive will influence the laser spot
positioning. Here, the model-free fuzzy control scheme is employed to
design the track seeking servo controller for a d.c. motor driving
optical disk drive system. In addition, the sliding model control
strategy is introduced into the fuzzy control structure to construct a
1-D adaptive fuzzy rule intelligent controller for simplifying the
implementation problem and improving the control performance. The
experimental results show that the steady state error of the track
seeking by using this fuzzy controller can maintain within the track
width (1.6 μm ). It can be used in the track seeking and track
following servo control operations.
Abstract: In this paper the development of a heat exchanger as a
pilot plant for educational purpose is discussed and the use of neural
network for controlling the process is being presented. The aim of the
study is to highlight the need of a specific Pseudo Random Binary
Sequence (PRBS) to excite a process under control. As the neural
network is a data driven technique, the method for data generation
plays an important role. In light of this a careful experimentation
procedure for data generation was crucial task. Heat exchange is a
complex process, which has a capacity and a time lag as process
elements. The proposed system is a typical pipe-in- pipe type heat
exchanger. The complexity of the system demands careful selection,
proper installation and commissioning. The temperature, flow, and
pressure sensors play a vital role in the control performance. The
final control element used is a pneumatically operated control valve.
While carrying out the experimentation on heat exchanger a welldrafted
procedure is followed giving utmost attention towards safety
of the system. The results obtained are encouraging and revealing
the fact that if the process details are known completely as far as
process parameters are concerned and utilities are well stabilized then
feedback systems are suitable, whereas neural network control
paradigm is useful for the processes with nonlinearity and less
knowledge about process. The implementation of NN control
reinforces the concepts of process control and NN control paradigm.
The result also underlined the importance of excitation signal
typically for that process. Data acquisition, processing, and
presentation in a typical format are the most important parameters
while validating the results.