Abstract: This paper presents the design and analysis of a parallel
connected inverter configuration of. The configuration consists of
parallel connected three-phase dc/ac inverter. Series resistors added
to the inverter output to maintain same current in each inverter of the
two parallel inverters, and to reduce the circulating current in the
parallel inverters to the minimum. High frequency third harmonic
injection PWM (THIPWM) employed to reduce the total harmonic
distortion and to make maximum use of the voltage source. DSP was
used to generate the THIPWM and the control algorithm for the
converter. Selected experimental results have been shown to validate
the proposed system.
Abstract: In this study, control performance of a smart base
isolation system consisting of a friction pendulum system (FPS) and a
magnetorheological (MR) damper has been investigated. A fuzzy
logic controller (FLC) is used to modulate the MR damper so as to
minimize structural acceleration while maintaining acceptable base
displacement levels. To this end, a multi-objective optimization
scheme is used to optimize parameters of membership functions and
find appropriate fuzzy rules. To demonstrate effectiveness of the
proposed multi-objective genetic algorithm for FLC, a numerical
study of a smart base isolation system is conducted using several
historical earthquakes. It is shown that the proposed method can find
optimal fuzzy rules and that the optimized FLC outperforms not only a
passive control strategy but also a human-designed FLC and a
conventional semi-active control algorithm.
Abstract: The adaptive power control of Code Division Multiple
Access (CDMA) communications using Remote Radio Head
(RRH) between multiple Unmanned Aerial Vehicles (UAVs) with
a link-budget based Signal-to-Interference Ratio (SIR) estimate is
applied to four inner loop power control algorithms. It is concluded
that Base Station (BS) can calculate not only UAV distance using
linearity between speed and Consecutive Transmit-Power-Control
Ratio (CTR) of Adaptive Step-size Closed Loop Power Control (ASCLPC),
Consecutive TPC Ratio Step-size Closed Loop Power Control
(CS-CLPC), Fixed Step-size Power Control (FSPC), but also UAV
position with Received Signal Strength Indicator (RSSI) ratio of
RRHs.
Abstract: The problem of manipulator control is a highly
complex problem of controlling a system which is multi-input, multioutput,
non-linear and time variant. In this paper some adaptive
fuzzy, and a new hybrid fuzzy control algorithm have been
comparatively evaluated through simulations, for manipulator
control. The adaptive fuzzy controllers consist of self-organizing,
self-tuning, and coarse/fine adaptive fuzzy schemes. These
controllers are tested for different trajectories and for varying
manipulator parameters through simulations. Various performance
indices like the RMS error, steady state error and maximum error are
used for comparison. It is observed that the self-organizing fuzzy
controller gives the best performance. The proposed hybrid fuzzy
plus integral error controller also performs remarkably well, given its
simple structure.
Abstract: A semi-active control strategy for suspension
systems of passenger cars is presented employing
Magnetorheological (MR) dampers. The vehicle is modeled with
seven DOFs including the, roll pitch and bounce of car body, and
the vertical motion of the four tires. In order to design an optimal
controller based on the actuator constraints, a Linear-Quadratic
Regulator (LQR) is designed. The design procedure of the LQR
consists of selecting two weighting matrices to minimize the energy
of the control system. This paper presents a hybrid optimization
procedure which is a combination of gradient-based and
evolutionary algorithms to choose the weighting matrices with
regards to the actuator constraint. The optimization algorithm is
defined based on maximum comfort and actuator constraints. It is
noted that utilizing the present control algorithm may significantly
reduce the vibration response of the passenger car, thus, providing
a comfortable ride.
Abstract: Today, transport and logistic systems are often tightly
integrated in the production. Lean production and just-in-time delivering create multiple constraints that have to be fulfilled. As transport networks often have evolved over time they are very
expensive to change. This paper describes a discrete-event-simulation
system which simulates transportation models using real time
resource routing and collision avoidance. It allows for the
specification of own control algorithms and validation of new
strategies. The simulation is integrated into a virtual reality (VR)
environment and can be displayed in 3-D to show the progress.
Simulation elements can be selected through VR metaphors. All data
gathered during the simulation can be presented as a detailed summary afterwards. The included cost-benefit calculation can help to optimize the financial outcome. The operation of this approach is shown by the example of a timber harvest simulation.
Abstract: Physiological control of a left ventricle assist device (LVAD) is generally a complicated task due to diverse operating environments and patient variability. In this work, a tracking control algorithm based on sliding mode and feed forward control for a class of discrete-time single input single output (SISO) nonlinear uncertain systems is presented. The controller was developed to track the reference trajectory to a set operating point without inducing suction in the ventricle. The controller regulates the estimated mean pulsatile flow Qp and mean pulsatility index of pump rotational speed PIω that was generated from a model of the assist device. We recall the principle of the sliding mode control theory then we combine the feed-forward control design with the sliding mode control technique to follow the reference trajectory. The uncertainty is replaced by its upper and lower boundary. The controller was tested in a computer simulation covering two scenarios (preload and ventricular contractility). The simulation results prove the effectiveness and the robustness of the proposed controller
Abstract: A novel low-cost impedance control structure is
proposed for monitoring the contact force between end-effector and
environment without installing an expensive force/torque sensor.
Theoretically, the end-effector contact force can be estimated from the
superposition of each joint control torque. There have a nonlinear
matrix mapping function between each joint motor control input and
end-effector actuating force/torques vector. This new force control
structure can be implemented based on this estimated mapping matrix.
First, the robot end-effector is manipulated to specified positions, then
the force controller is actuated based on the hall sensor current
feedback of each joint motor. The model-free fuzzy sliding mode
control (FSMC) strategy is employed to design the position and force
controllers, respectively. All the hardware circuits and software
control programs are designed on an Altera Nios II embedded
development kit to constitute an embedded system structure for a
retrofitted Mitsubishi 5 DOF robot. Experimental results show that PI
and FSMC force control algorithms can achieve reasonable contact
force monitoring objective based on this hardware control structure.
Abstract: This paper proposed a nonlinear model predictive
control (MPC) method for the control of gantry crane. One of the main
motivations to apply MPC to control gantry crane is based on its
ability to handle control constraints for multivariable systems. A
pre-compensator is constructed to compensate the input nonlinearity
(nonsymmetric dead zone with saturation) by using its inverse
function. By well tuning the weighting function matrices, the control
system can properly compromise the control between crane position
and swing angle. The proposed control algorithm was implemented for
the control of gantry crane system in System Control Lab of University
of Technology, Sydney (UTS), and achieved desired experimental
results.
Abstract: Based on a theoretical erbium-doped fiber amplifier
(EDFA) model, we have proposed an application of disturbance
observer(DOB) with proportional/integral/differential(PID) controller
to EDFA for minimizing gain-transient time of wavelength
-division-multiplexing (WDM) multi channels in optical amplifier in
channel add/drop networks. We have dramatically reduced the
gain-transient time to less than 30μsec by applying DOB with PID
controller to the control of amplifier gain. The proposed DOB-based
gain control algorithm for EDFA was implemented as a digital control
system using TI's DSP(TMS320C28346) chip and experimental
results of the system verify the excellent performance of the proposed
gain control methodology.
Abstract: In the real application of active control systems to
mitigate the response of structures subjected to sever external
excitations such as earthquake and wind induced vibrations, since the
capacity of actuators is limited then the actuators saturate. Hence, in
designing controllers for linear and nonlinear structures under sever
earthquakes, the actuator saturation should be considered as a
constraint. In this paper optimal design of active controllers for
nonlinear structures by considering the actuator saturation has been
studied. To this end a method has been proposed based on defining
an optimization problem which considers the minimizing of the
maximum displacement of the structure as objective when a limited
capacity for actuator has been used as a constraint in optimization
problem. To evaluate the effectiveness of the proposed method, a
single degree of freedom (SDF) structure with a bilinear hysteretic
behavior has been simulated under a white noise ground acceleration
of different amplitudes. Active tendon control mechanism, comprised
of pre-stressed tendons and an actuator, and extended nonlinear
Newmark method based instantaneous optimal control algorithm
have been used as active control mechanism and algorithm. To
enhance the efficiency of the controllers, the weights corresponding
to displacement, velocity, acceleration and control force in the
performance index have been found by using the Distributed Genetic
Algorithm (DGA). According to the results it has been concluded
that the proposed method has been effective in considering the
actuator saturation in designing optimal controllers for nonlinear
frames. Also it has been shown that the actuator capacity and the
average value of required control force are two important factors in
designing nonlinear controllers for considering the actuator
saturation.
Abstract: In this paper, periodic force operation of a wastewater treatment process has been studied for the improved process performance. A previously developed dynamic model for the process is used to conduct the performance analysis. The static version of the model was utilized first to determine the optimal productivity conditions for the process. Then, feed flow rate in terms of dilution rate i.e. (D) is transformed into sinusoidal function. Nonlinear model predictive control algorithm is utilized to regulate the amplitude and period of the sinusoidal function. The parameters of the feed cyclic functions are determined which resulted in improved productivity than the optimal productivity under steady state conditions. The improvement in productivity is found to be marginal and is satisfactory in substrate conversion compared to that of the optimal condition and to the steady state condition, which corresponds to the average value of the periodic function. Successful results were also obtained in the presence of modeling errors and external disturbances.
Abstract: Wind turbine should be controlled to capture maximum
wind energy and to prevent the turbine from being stalled. To achieve
those two goals, wind turbine controller controls torque on generator
and limits input torque from wind by pitching blade. Usually, torque
on generator is controlled using inverter torque set point. However,
verifying a control algorithm in actual wind turbine needs a lot of
efforts to test and the actual wind turbine could be broken while testing
a control algorithm. So, several software have developed and
commercialized by Garrad Hassan, GH Bladed, and NREL, FAST.
Even though, those programs can simulate control system modeling
with subroutines or DLLs. However, those simulation programs are
not able to emulate detailed generator or PMSG. In this paper, a small
size wind turbine simulator is developed with induction motor and
small size drive train. The developed system can simulate wind turbine
control algorithm in the region before rated power.
Abstract: A fuzzy predictive pursuit guidance is proposed as an
alternative to the conventional methods. The purpose of this scheme
is to obtain a stable and fast guidance. The noise effects must be
reduced in homing missile guidance to get an accurate control. An
aerodynamic missile model is simulated first and a fuzzy predictive
pursuit control algorithm is applied to reduce the noise effects. The
performance of this algorithm is compared with the performance of
the classical proportional derivative control. Stability analysis of the
proposed guidance method is performed and compared with the
stability properties of other guidance methods. Simulation results
show that the proposed method provides the satisfying performance.
Abstract: Model Predictive Control (MPC) is an established control
technique in a wide range of process industries. The reason for
this success is its ability to handle multivariable systems and systems
having input, output or state constraints. Neverthless comparing to
PID controller, the implementation of the MPC in miniaturized
devices like Field Programmable Gate Arrays (FPGA) and microcontrollers
has historically been very small scale due to its complexity in
implementation and its computation time requirement. At the same
time, such embedded technologies have become an enabler for future
manufacturing enterprisers as well as a transformer of organizations
and markets. In this work, we take advantage of these recent advances
in this area in the deployment of one of the most studied and applied
control technique in the industrial engineering. In this paper, we
propose an efficient firmware for the implementation of constrained
MPC in the performed STM32 microcontroller using interior point
method. Indeed, performances study shows good execution speed
and low computational burden. These results encourage to develop
predictive control algorithms to be programmed in industrial standard
processes. The PID anti windup controller was also implemented in
the STM32 in order to make a performance comparison with the
MPC. The main features of the proposed constrained MPC framework
are illustrated through two examples.
Abstract: A novel design of two-wheeled robotic vehicle with moving payload is presented in this paper. A mathematical model describing the vehicle dynamics is derived and simulated in Matlab Simulink environment. Two control strategies were developed to stabilise the vehicle in the upright position. A robust Proportional- Integral-Derivative (PID) control strategy has been implemented and initially tested to measure the system performance, while the second control strategy is to use a hybrid fuzzy logic controller (FLC). The results are given on a comparative basis for the system performance in terms of disturbance rejection, control algorithms robustness as well as the control effort in terms of input torque.
Abstract: Since the actuator capacity is limited, in the real
application of active control systems under sever earthquakes it is
conceivable that the actuators saturate, hence the actuator saturation
should be considered as a constraint in design of optimal controllers.
In this paper optimal design of active controllers for nonlinear
structures by considering actuator saturation, has been studied. The
proposed method for designing optimal controllers is based on
defining an optimization problem which the objective has been to
minimize the maximum displacement of structure when a limited
capacity for actuator has been used. To this end a single degree of
freedom (SDF) structure with a bilinear hysteretic behavior has been
simulated under a white noise ground acceleration of different
amplitudes. Active tendon control mechanism, comprised of prestressed
tendons and an actuator, and extended nonlinear Newmark
method based instantaneous optimal control algorithm have been
used. To achieve the best results, the weights corresponding to
displacement, velocity, acceleration and control force in the
performance index have been optimized by the Distributed Genetic
Algorithm (DGA). Results show the effectiveness of the proposed
method in considering actuator saturation. Also based on the
numerical simulations it can be concluded that the actuator capacity
and the average value of required control force are two important
factors in designing nonlinear controllers which consider the actuator
saturation.
Abstract: Access control is a critical security service in Wire- less
Sensor Networks (WSNs). To prevent malicious nodes from joining
the sensor network, access control is required. On one hand, WSN
must be able to authorize and grant users the right to access to the
network. On the other hand, WSN must organize data collected by
sensors in such a way that an unauthorized entity (the adversary)
cannot make arbitrary queries. This restricts the network access only
to eligible users and sensor nodes, while queries from outsiders will
not be answered or forwarded by nodes. In this paper we presentee
different access control schemes so as to ?nd out their objectives,
provision, communication complexity, limits, etc. Using the node
density parameter, we also provide a comparison of these proposed
access control algorithms based on the network topology which can
be flat or hierarchical.
Abstract: This paper presents the study of a variable speed wind
energy conversion system based on a Doubly Fed Induction Generator
(DFIG) based on a sliding mode control applied to achieve control of
active and reactive powers exchanged between the stator of the DFIG
and the grid to ensure a Maximum Power Point Tracking (MPPT) of
a wind energy conversion system. The proposed control algorithm is
applied to a DFIG whose stator is directly connected to the grid and
the rotor is connected to the PWM converter. To extract a maximum
of power, the rotor side converter is controlled by using a stator
flux-oriented strategy. The created decoupling control between active
and reactive stator power allows keeping the power factor close to
unity. Simulation results show that the wind turbine can operate at
its optimum energy for a wide range of wind speed.
Abstract: The decisions made by admission control algorithms are
based on the availability of network resources viz. bandwidth, energy,
memory buffers, etc., without degrading the Quality-of-Service (QoS)
requirement of applications that are admitted. In this paper, we
present an energy-aware admission control (EAAC) scheme which
provides admission control for flows in an ad hoc network based
on the knowledge of the present and future residual energy of the
intermediate nodes along the routing path. The aim of EAAC is to
quantify the energy that the new flow will consume so that it can
be decided whether the future residual energy of the nodes along
the routing path can satisfy the energy requirement. In other words,
this energy-aware routing admits a new flow iff any node in the
routing path does not run out of its energy during the transmission
of packets. The future residual energy of a node is predicted using
the Multi-layer Neural Network (MNN) model. Simulation results
shows that the proposed scheme increases the network lifetime. Also
the performance of the MNN model is presented.