Abstract: In this paper, a longitudinal and lateral control approach
based on a nonlinear observer is proposed for a convoy of autonomous
vehicles to follow a desired trajectory. To authors best knowledge,
this topic has not yet been sufficiently addressed in the literature
for the control of multi vehicles. The modeling of the convoy
of the vehicles is revisited using a robotic method for simulation
purposes and control design. With these models, a sliding mode
observer is proposed to estimate the states of each vehicle in the
convoy from the available sensors, then a sliding mode control
based on this observer is used to control the longitudinal and lateral
movement. The validation and performance evaluation are done using
the well-known driving simulator Scanner-Studio. The results are
presented for different maneuvers of 5 vehicles.
Abstract: In response to widely used wearable medical devices equipped with a continuous glucose monitor (CGM) and insulin pump, the advanced control methods are still demanding to get the full benefit of these devices. Unlike costly clinical trials, implementing effective insulin-glucose control strategies can provide significant contributions to the patients suffering from chronic diseases such as diabetes. This study deals with a key role of two-layer insulin-glucose regulator based on model-predictive-control (MPC) scheme so that the patient’s predicted glucose profile is in compliance with the insulin level injected through insulin pump automatically. It is achieved by iterative optimization algorithm which is called an integrated perturbation analysis and sequential quadratic programming (IPA-SQP) solver for handling uncertainties due to unexpected variations in glucose-insulin values and body’s characteristics. The feasibility evaluation of the discussed control approach is also studied by means of numerical simulations of two case scenarios via measured data. The obtained results are presented to verify the superior and reliable performance of the proposed control scheme with no negative impact on patient safety.
Abstract: This article presents the design of optimal automatic generation control (AGC) based on full state feedback control for a multi-area interconnected power system. An extra high voltage AC transmission line in parallel with a high voltage DC link is considered as an area interconnection between the areas. The optimal AGC are designed and implemented in the wake of 1% load perturbation in one of the areas and the system dynamic response plots for various system states are obtained to investigate the system dynamic performance. The pattern of closed-loop eigenvalues are also determined to analyze the system stability. From the investigations carried out in the work, it is revealed that the dynamic performance of the system under consideration has an appreciable improvement when a high voltage DC line is paralleled with an extra high voltage AC line as an interconnection between the areas. The investigation of closed-loop eigenvalues reveals that the system stability is ensured in all case studies carried out with the designed optimal AGC.
Abstract: In order to maximize energy capturing from wind
energy, controlling the doubly fed induction generator to have optimal
power from the wind, generator speed and output electrical power
control in wind energy system have a great importance due to the
nonlinear behavior of wind velocities. In this paper purposes the
design of a control scheme is developed for power control of wind
energy system via H∞ fuzzy integral controller. Firstly, the nonlinear
system is represented in term of a TS fuzzy control design via linear
matrix inequality approach to find the optimal controller to have an
H∞ performance are derived. The proposed control method extract
the maximum energy from the wind and overcome the nonlinearity
and disturbances problems of wind energy system which give good
tracking performance and high efficiency power output of the DFIG.
Abstract: This paper considers an H∞ TS fuzzy state-derivative feedback controller for a class of nonlinear dynamical systems. A Takagi-Sugeno (TS) fuzzy model is used to approximate a class of nonlinear dynamical systems. Then, based on a linear matrix inequality (LMI) approach, we design an H∞ TS fuzzy state-derivative feedback control law which guarantees L2-gain of the mapping from the exogenous input noise to the regulated output to be less or equal to a prescribed value. We derive a sufficient condition such that the system with the fuzzy controller is asymptotically stable and H∞ performance is satisfied. Finally, we provide and simulate a numerical example is provided to illustrate the stability and the effectiveness of the proposed controller.
Abstract: In this paper, the problem of posture stabilization for a kinematic model of differential drive robots is studied. A more complex model of the kinematics of differential drive robots is used for the design of stabilizing control. This model is formulated in terms of the physical parameters of the system such as the radius of the wheels, and velocity of the wheels are the control inputs of it. In this paper, the framework of Lyapunov-based control design has been used to solve posture stabilization problem for the comprehensive model of differential drive robots. The results of the simulations show that the devised controller successfully solves the posture regulation problem. Finally, robustness and performance of the controller have been studied under system parameter uncertainty.
Abstract: Evolutionary Fuzzy PID Speed Controller for Permanent Magnet Synchronous Motor (PMSM) is developed to achieve the Speed control of PMSM in Closed Loop operation and to deal with the existence of transients. Consider a Fuzzy PID control design problem, based on common control Engineering Knowledge. If the transient error is big, that Good transient performance can be obtained by increasing the P and I gains and decreasing the D gains. To autotune the control parameters of the Fuzzy PID controller, the Evolutionary Algorithms (EA) are developed. EA based Fuzzy PID controller provides better speed control and guarantees the closed loop stability. The Evolutionary Fuzzy PID controller can be implemented in real time Applications without any concern about instabilities that leads to system failure or damage.
Abstract: We consider the problem of stabilization of an unstable
heat equation in a 2-D, 3-D and generally n-D domain by deriving a
generalized backstepping boundary control design methodology. To
stabilize the systems, we design boundary backstepping controllers
inspired by the 1-D unstable heat equation stabilization procedure.
We assume that one side of the boundary is hinged and the other
side is controlled for each direction of the domain. Thus, controllers
act on two boundaries for 2-D domain, three boundaries for 3-D
domain and ”n” boundaries for n-D domain. The main idea of the
design is to derive ”n” controllers for each of the dimensions by
using ”n” kernel functions. Thus, we obtain ”n” controllers for the
”n” dimensional case. We use a transformation to change the system
into an exponentially stable ”n” dimensional heat equation. The
transformation used in this paper is a generalized Volterra/Fredholm
type with ”n” kernel functions for n-D domain instead of the one
kernel function of 1-D design.
Abstract: Electrohydraulic servo system have been used in
industry in a wide number of applications. Its dynamics are highly
nonlinear and also have large extent of model uncertainties and
external disturbances. In this paper, a robust back-stepping control
(RBSC) scheme is proposed to overcome the problem of disturbances
and system uncertainties effectively and to improve the tracking
performance of EHS systems. In order to implement the proposed
control scheme, the system uncertainties in EHS systems are
considered as total leakage coefficient and effective oil volume. In
addition, in order to obtain the virtual controls for stabilizing system,
the update rule for the system uncertainty term is induced by
the Lyapunov control function (LCF). To verify the performance and
robustness of the proposed control system, computer simulation of
the proposed control system using Matlab/Simulink Software
is executed. From the computer simulation, it was found that the
RBSC system produces the desired tracking performance and has
robustness to the disturbances and system uncertainties of EHS
systems.
Abstract: Electrohydraulic servo system have been used in industry in a wide number of applications. Its dynamics are highly nonlinear and also have large extent of model uncertainties and external disturbances. In this paper, a robust back-stepping control (RBSC) scheme is proposed to overcome the problem of disturbances and system uncertainties effectively and to improve the tracking performance of EHS systems. In order to implement the proposed control scheme, the system uncertainties in EHS systems are considered as total leakage coefficient and effective oil volume. In addition, in order to obtain the virtual controls for stabilizing system, the update rule for the system uncertainty term is induced by the Lyapunov control function (LCF). To verify the performance and robustness of the proposed control system, computer simulation of the proposed control system using Matlab/Simulink Software is executed. From the computer simulation, it was found that the RBSC system produces the desired tracking performance and has robustness to the disturbances and system uncertainties of EHS systems.
Abstract: Verification and Validation of Simulated Process
Model is the most important phase of the simulator life cycle.
Evaluation of simulated process models based on Verification and
Validation techniques checks the closeness of each component model
(in a simulated network) with the real system/process with respect to
dynamic behaviour under steady state and transient conditions. The
process of Verification and Validation helps in qualifying the process
simulator for the intended purpose whether it is for providing
comprehensive training or design verification. In general, model
verification is carried out by comparison of simulated component
characteristics with the original requirement to ensure that each step
in the model development process completely incorporates all the
design requirements. Validation testing is performed by comparing
the simulated process parameters to the actual plant process
parameters either in standalone mode or integrated mode.
A Full Scope Replica Operator Training Simulator for PFBR -
Prototype Fast Breeder Reactor has been developed at IGCAR,
Kalpakkam, INDIA named KALBR-SIM (Kalpakkam Breeder
Reactor Simulator) where in the main participants are
engineers/experts belonging to Modeling Team, Process Design and
Instrumentation & Control design team. This paper discusses about
the Verification and Validation process in general, the evaluation
procedure adopted for PFBR operator training Simulator, the
methodology followed for verifying the models, the reference
documents and standards used etc. It details out the importance of
internal validation by design experts, subsequent validation by
external agency consisting of experts from various fields, model
improvement by tuning based on expert’s comments, final
qualification of the simulator for the intended purpose and the
difficulties faced while co-coordinating various activities.
Abstract: This paper proposes a new technique to design a
fixed-structure robust loop shaping controller for the pneumatic
servosystem. In this paper, a new method based on a particle swarm
optimization (PSO) algorithm for tuning the weighting function
parameters to design an H∞ controller is presented. The PSO
algorithm is used to minimize the infinity norm of the transfer
function of the nominal closed loop system to obtain the optimal
parameters of the weighting functions. The optimal stability margin is
used as an objective in PSO for selecting the optimal weighting
parameters; it is shown that the proposed method can simplify the
design procedure of H∞ control to obtain optimal robust controller for
pneumatic servosystem. In addition, the order of the proposed
controller is much lower than that of the conventional robust loop
shaping controller, making it easy to implement in practical works.
Also two-degree-of-freedom (2DOF) control design procedure is
proposed to improve tracking performance in the face of noise and
disturbance. Result of simulations demonstrates the advantages of the
proposed controller in terms of simple structure and robustness
against plant perturbations and disturbances.
Abstract: The coefficient diagram method is primarily an algebraic control design method whose objective is to easily obtain
a good controller with minimum user effort. As a matter of fact, if a
system model, in the form of linear differential equations, is known,
the user only need to define a time-constant and the controller order.
The later can be established regarding the expected disturbance type
via a lookup table first published by Koksal and Hamamci in 2004.
However an inaccuracy in this table was detected and pointed-out in
the present work. Moreover the above mentioned table was expanded
in order to enclose any k order type disturbance.
Abstract: A vehicle driving with an Adaptive Cruise Control
System (ACC) is usually controlled decentrally, based on the
information of radar systems and in some publications based on
C2X-Communication (CACC) to guarantee stable platoons. In this
paper we present a Model Predictive Control (MPC) design of a
centralized, server-based ACC-System, whereby the vehicular platoon
is modeled and controlled as a whole. It is then proven that the
proposed MPC design guarantees asymptotic stability and hence
string stability of the platoon. The Networked MPC design is
chosen to be able to integrate system constraints optimally as well
as to reduce the effects of communication delay and packet loss.
The performance of the proposed controller is then simulated and
analyzed in an LTE communication scenario using the LTE/EPC
Network Simulator LENA, which is based on the ns-3 network
simulator.
Abstract: In this paper feedforward controller is designed to eliminate nonlinear hysteresis behaviors of a piezoelectric stack actuator (PSA) driven system. The control design is based on inverse Prandtl-Ishlinskii (P-I) hysteresis model identified using particle swarm optimization (PSO) technique. Based on the identified P-I model, both the inverse P-I hysteresis model and feedforward controller can be determined. Experimental results obtained using the inverse P-I feedforward control are compared with their counterparts using hysteresis estimates obtained from the identified Bouc-Wen model. Effectiveness of the proposed feedforward control scheme is demonstrated. To improve control performance feedback compensation using traditional PID scheme is adopted to integrate with the feedforward controller.
Abstract: This paper introduces an open-source software package SCILAB [1], an alternative of MATLAB [2], which can be used for robust control design and analysis of a typical mass-spring-damper (MSD) system. Using the previously published ideas in [3,4], this popular mechanical system is considered to provide another example of usefulness of SCILAB for advanced control design.
Abstract: Due to simplicity and low cost, rotordynamic system is often modeled by using lumped parameters. Recently, finite elements have been used to model rotordynamic system as it offers higher accuracy. However, it involves high degrees of freedom. In some applications such as control design, this requires higher cost. For this reason, various model reduction methods have been proposed. This work demonstrates the quality of model reduction of rotor-bearing-support system through substructuring. The quality of the model reduction is evaluated by comparing some first natural frequencies, modal damping ratio, critical speeds, and response of both the full system and the reduced system. The simulation shows that the substructuring is proven adequate to reduce finite element rotor model in the frequency range of interest as long as the number and the location of master nodes are determined appropriately. However, the reduction is less accurate in an unstable or nearly-unstable system.
Abstract: The paper presents how to design the indirect vector control of three-phase induction motor drive systems using the artificial intelligence technique called the adaptive tabu search. The results from the simulation and the experiment show that the drive system with the controller designed from the proposed method can provide the best output speed response compared with those of the conventional method. The controller design using the proposed technique can be used to create the software package for engineers to achieve the optimal controller design of the induction motor speed control based on the indirect vector concept.
Abstract: In this paper we consider a nonlinear feedback control called augmented automatic choosing control (AACC) for nonlinear systems with constrained input. Constant terms which arise from section wise linearization of a given nonlinear system are treated as coefficients of a stable zero dynamics.Parameters included in the control are suboptimally selectedby extremizing a combination of Hamiltonian and Lyapunov functions with the aid of the genetic algorithm. This approach is applied to a field excitation control problem of power system to demonstrate the splendidness of the AACC. Simulation results show that the new controller can improve performance remarkably well.
Abstract: Power system stabilizers (PSS) must be capable of providing appropriate stabilization signals over a broad range of
operating conditions and disturbance. Traditional PSS rely on robust
linear design method in an attempt to cover a wider range of operating
condition. Expert or rule-based controllers have also been proposed.
Recently fuzzy logic (FL) as a novel robust control
design method has shown promising results. The emphasis in fuzzy
control design center is around uncertainties in the system parameters
& operating conditions. In this paper a novel Robust Fuzzy Logic Power
System Stabilizer (RFLPSS) design is proposed The RFLPSS
basically utilizes only one measurable Δω signal as input
(generator shaft speed).
The speed signal is discretized resulting in three inputs to the
RFLPSS. There are six rules for the fuzzification and two rules for
defuzzification. To provide robustness, additional signal namely,
speed are used as inputs to RFLPSS enabling appropriate gain
adjustments for the three RFLPSS inputs. Simulation studies
show the superior performance of the RFLPSS compared
with an optimally designed conventional PSS and discrete mode FLPSS.