Showing papers in "Isa Transactions in 2011"
TL;DR: The paper shows that random variation in network delay can be handled efficiently with fuzzy logic based PID controllers over conventional PID controllers.
Abstract: An optimal PID and an optimal fuzzy PID have been tuned by minimizing the Integral of Time multiplied Absolute Error (ITAE) and squared controller output for a networked control system (NCS) The tuning is attempted for a higher order and a time delay system using two stochastic algorithms viz the Genetic Algorithm (GA) and two variants of Particle Swarm Optimization (PSO) and the closed loop performances are compared The paper shows that random variation in network delay can be handled efficiently with fuzzy logic based PID controllers over conventional PID controllers
240 citations
TL;DR: A new fractional order template for reduced parameter modelling of stable minimum/non-minimum phase higher order processes is introduced and its advantage in frequency domain tuning of FOPID controllers is presented.
Abstract: In this paper, a comparative study is done on the time and frequency domain tuning strategies for fractional order (FO) PID controllers to handle higher order processes. A new fractional order template for reduced parameter modelling of stable minimum/non-minimum phase higher order processes is introduced and its advantage in frequency domain tuning of FOPID controllers is also presented. The time domain optimal tuning of FOPID controllers have also been carried out to handle these higher order processes by performing optimization with various integral performance indices. The paper highlights on the practical control system implementation issues like flexibility of online autotuning, reduced control signal and actuator size, capability of measurement noise filtration, load disturbance suppression, robustness against parameter uncertainties etc. in light of the above tuning methodologies.
217 citations
TL;DR: Simulation shows that compared to the widely used integral control method, the proposed method provides significantly improved disturbance rejection and robustness against load variation.
Abstract: Robust control of a class of uncertain systems that have disturbances and uncertainties not satisfying “matching” condition is investigated in this paper via a disturbance observer based control (DOBC) approach. In the context of this paper, “matched” disturbances/uncertainties stand for the disturbances/uncertainties entering the system through the same channels as control inputs. By properly designing a disturbance compensation gain, a novel composite controller is proposed to counteract the “mismatched” lumped disturbances from the output channels. The proposed method significantly extends the applicability of the DOBC methods. Rigorous stability analysis of the closed-loop system with the proposed method is established under mild assumptions. The proposed method is applied to a nonlinear MAGnetic LEViation (MAGLEV) suspension system. Simulation shows that compared to the widely used integral control method, the proposed method provides significantly improved disturbance rejection and robustness against load variation.
192 citations
TL;DR: Experimental results show that the proposed IPSO has stronger convergence and stability than the other four particle swarm optimization algorithms on solving reliability problems, and that the solutions obtained are better than the previously reported best-known solutions in the recent literature.
Abstract: An improved particle swarm optimization (IPSO) algorithm is proposed to solve reliability problems in this paper. The IPSO designs two position updating strategies: In the early iterations, each particle flies and searches according to its own best experience with a large probability; in the late iterations, each particle flies and searches according to the fling experience of the most successful particle with a large probability. In addition, the IPSO introduces a mutation operator after position updating, which can not only prevent the IPSO from trapping into the local optimum, but also enhances its space developing ability. Experimental results show that the proposed algorithm has stronger convergence and stability than the other four particle swarm optimization algorithms on solving reliability problems, and that the solutions obtained by the IPSO are better than the previously reported best-known solutions in the recent literature.
123 citations
TL;DR: A convenient solution in process plants where cabling is not possible is provided, which has lower installation and maintenance cost, provides reliable operation, and robust and flexible construction, suitable for industrial applications.
Abstract: This paper describes a water pumping control system that is designed for production plants and implemented in an experimental setup in a laboratory. These plants contain harsh environments in which chemicals, vibrations or moving parts exist that could potentially damage the cabling or wires that are part of the control system. Furthermore, the data has to be transferred over paths that are accessible to the public. The control systems that it uses are a programmable logic controller (PLC) and industrial wireless local area network (IWLAN) technologies. It is implemented by a PLC, an communication processor (CP), two IWLAN modules, and a distributed input/output (I/O) module, as well as the water pump and sensors. Our system communication is based on an Industrial Ethernet and uses the standard Transport Control Protocol/Internet Protocol for parameterisation, configuration and diagnostics. The main function of the PLC is to send a digital signal to the water pump to turn it on or off, based on the tank level, using a pressure transmitter and inputs from limit switches that indicate the level of the water in the tank. This paper aims to provide a convenient solution in process plants where cabling is not possible. It also has lower installation and maintenance cost, provides reliable operation, and robust and flexible construction, suitable for industrial applications.
110 citations
TL;DR: Two new adaptive model predictive control algorithms, both consisting of an on-line process identification part and a predictive control part, applied to the temperature control of a fluidized bed furnace reactor and the auto-pilot control of an F-16 aircraft.
Abstract: This paper presents two new adaptive model predictive control algorithms, both consisting of an on-line process identification part and a predictive control part. Both parts are executed at each sampling instant. The predictive control part of the first algorithm is the Nonlinear Model Predictive Control strategy and the control part of the second algorithm is the Generalized Predictive Control strategy. In the identification parts of both algorithms the process model is approximated by a series-parallel neural network structure which is trained by a recursive least squares (ARLS) method. The two control algorithms have been applied to: 1) the temperature control of a fluidized bed furnace reactor (FBFR) of a pilot plant and 2) the auto-pilot control of an F-16 aircraft. The training and validation data of the neural network are obtained from the open-loop simulation of the FBFR and the nonlinear F-16 aircraft models. The identification and control simulation results show that the first algorithm outperforms the second one at the expense of extra computation time.
109 citations
TL;DR: An adaptive control approach based on the neural networks is presented to control a DC motor system with dead-zone characteristics, where two neural networks are proposed to formulate the traditional identification and control approaches.
Abstract: In this paper, an adaptive control approach based on the neural networks is presented to control a DC motor system with dead-zone characteristics (DZC), where two neural networks are proposed to formulate the traditional identification and control approaches. First, a Wiener-type neural network (WNN) is proposed to identify the motor DZC, which formulates the Wiener model with a linear dynamic block in cascade with a nonlinear static gain. Second, a feedforward neural network is proposed to formulate the traditional PID controller, termed as PID-type neural network (PIDNN), which is then used to control and compensate for the DZC. In this way, the DC motor system with DZC is identified by the WNN identifier, which provides model information to the PIDNN controller in order to make it adaptive. Back-propagation algorithms are used to train both neural networks. Also, stability and convergence analysis are conducted using the Lyapunov theorem. Finally, experiments on the DC motor system demonstrated accurate identification and good compensation for dead-zone with improved control performance over the conventional PID control.
105 citations
TL;DR: Simulation results indicate that under healthy conditions, the rotor slot harmonics have the same magnitude in three phase currents, while under even 1 turn short circuit condition they differ from each other.
Abstract: The objective of this paper is to propose a new method for the detection of inter-turn short circuits in the stator windings of induction motors. In the previous reported methods, the supply voltage unbalance was the major difficulty, and this was solved mostly based on the sequence component impedance or current which are difficult to implement. Some other methods essentially are included in the offline methods. The proposed method is based on the motor current signature analysis and utilizes three phase current spectra to overcome the mentioned problem. Simulation results indicate that under healthy conditions, the rotor slot harmonics have the same magnitude in three phase currents, while under even 1 turn (0.3%) short circuit condition they differ from each other. Although the magnitude of these harmonics depends on the level of unbalanced voltage, they have the same magnitude in three phases in these conditions. Experiments performed under various load, fault, and supply voltage conditions validate the simulation results and demonstrate the effectiveness of the proposed technique. It is shown that the detection of resistive slight short circuits, without sensitivity to supply voltage unbalance is possible.
89 citations
TL;DR: Application results reveal that the weighted multi-scale morphological gradient filter achieves the same or better performance as EA and WT-EA, and requires low computation cost and is very suitable for on-line condition monitoring of bearing operating states.
Abstract: This paper presents a novel signal processing scheme, named the weighted multi-scale morphological gradient filter (WMMG), for rolling element bearing fault detection. The WMMG can depress the noise at large scale and preserve the impulsive shape details at small scale. Both a simulated signal and vibration signals from a bearing test rig are employed to evaluate the performance of the proposed technique. The traditional envelope analysis and a multi-scale enveloping spectrogram algorithm combining continuous wavelet transform and envelope analysis (WT-EA) are also studied and compared with the presented WMMG. Experimental results have demonstrated the effectiveness of the WMMG to extract the impulsive components from the raw vibration signal with strong background noise. We also investigated the classification performance on identifying bearing faults based on the WMMG and statistical parameters with varied noise levels. Application results reveal that the WMMG achieves the same or better performance as EA and WT-EA. Meanwhile, the WMMG requires low computation cost and is very suitable for on-line condition monitoring of bearing operating states.
85 citations
TL;DR: It is shown that the developed algorithm gives a comparable degree of accuracy to other algorithms, and can be used in a number of fields, including adaptive nonlinear control, model predictive control, fault detection, diagnostics and robotics.
Abstract: In this paper we propose a new approach to on-line Takagi-Sugeno fuzzy model identification. It combines a recursive fuzzy c-means algorithm and recursive least squares. First the method is derived and than it is tested and compared on a benchmark problem of the Mackey-Glass time series with other established on-line identification methods. We showed that the developed algorithm gives a comparable degree of accuracy to other algorithms. The proposed algorithm can be used in a number of fields, including adaptive nonlinear control, model predictive control, fault detection, diagnostics and robotics. An example of identification based on a real data of the waste-water treatment process is also presented.
83 citations
TL;DR: A simple analytical method is proposed for tuning the parameters of fractional order PI and PID controllers based on the obtained reduced models to show the efficiency of the proposed tuning algorithm.
Abstract: Fractional order PI and PID controllers are the most common fractional order controllers used in practice. In this paper, a simple analytical method is proposed for tuning the parameters of these controllers. The proposed method is useful in designing fractional order PI and PID controllers for control of complicated fractional order systems. To achieve the goal, at first a reduction technique is presented for approximating complicated fractional order models. Then, based on the obtained reduced models some analytical rules are suggested to determine the parameters of fractional order PI and PID controllers. Finally, numerical results are given to show the efficiency of the proposed tuning algorithm.
TL;DR: This paper describes how the constrained control algorithm is embedded in an industrial programmable logic controller (PLC) using the IEC 61131-3 programming standard and there is a definition and implementation of a novel auto-tuned predictive controller.
Abstract: This paper makes two key contributions. First, it tackles the issue of the availability of constrained predictive control for low-level control loops. Hence, it describes how the constrained control algorithm is embedded in an industrial programmable logic controller (PLC) using the IEC 61131-3 programming standard. Second, there is a definition and implementation of a novel auto-tuned predictive controller; the key novelty is that the modelling is based on relatively crude but pragmatic plant information. Laboratory experiment tests were carried out in two bench-scale laboratory systems to prove the effectiveness of the combined algorithm and hardware solution. For completeness, the results are compared with a commercial proportional-integral-derivative (PID) controller (also embedded in the PLC) using the most up to date auto-tuning rules.
TL;DR: Backstepping based robust control is first developed for the total 6 DOF dynamic model of SFF with parameter uncertainties, in which the model consists of relative translation and attitude rotation and redesigned to deal with the input constraint problem by incorporating a command filter.
Abstract: This paper treats the problem of synchronized control of spacecraft formation flying (SFF) in the presence of input constraint and parameter uncertainties. More specifically, backstepping based robust control is first developed for the total 6 DOF dynamic model of SFF with parameter uncertainties, in which the model consists of relative translation and attitude rotation. Then this controller is redesigned to deal with the input constraint problem by incorporating a command filter such that the generated control could be implementable even under physical or operating constraints on the control input. The convergence of the proposed control algorithms is proved by the Lyapunov stability theorem. Compared with conventional methods, illustrative simulations of spacecraft formation flying are conducted to verify the effectiveness of the proposed approach to achieve the spacecraft track the desired attitude and position trajectories in a synchronized fashion even in the presence of uncertainties, external disturbances and control saturation constraint.
TL;DR: This paper presents a novel adaptive fuzzy logic controller equipped with an adaptive algorithm to achieve H(∞) synchronization performance for uncertain fractional order chaotic systems and results signify the effectiveness of the proposed control scheme.
Abstract: This paper presents a novel adaptive fuzzy logic controller (FLC) equipped with an adaptive algorithm to achieve H ∞ synchronization performance for uncertain fractional order chaotic systems. In order to handle the high level of uncertainties and noisy training data, a desired synchronization error can be attenuated to a prescribed level by incorporating fuzzy control design and H ∞ tracking approach. Based on a Lyapunov stability criterion, not only the performance of the proposed method is satisfying with an acceptable synchronization error level, but also a rather simple stability analysis is performed. The simulation results signify the effectiveness of the proposed control scheme.
TL;DR: A fuzzy PID control scheme with a real-valued genetic algorithm (RGA) to a setpoint control problem to control a twin rotor MIMO system to move quickly and accurately to the desired attitudes, both the pitch angle and the azimuth angle in a cross-coupled condition.
Abstract: This paper presents a fuzzy PID control scheme with a real-valued genetic algorithm (RGA) to a setpoint control problem. The objective of this paper is to control a twin rotor MIMO system (TRMS) to move quickly and accurately to the desired attitudes, both the pitch angle and the azimuth angle in a cross-coupled condition. A fuzzy compensator is applied to the PID controller. The proposed control structure includes four PID controllers with independent inputs in 2-DOF. In order to reduce total error and control energy, all parameters of the controller are obtained by a RGA with the system performance index as a fitness function. The system performance index utilized the integral of time multiplied by the square error criterion (ITSE) to build a suitable fitness function in the RGA. A new method for RGA to solve more than 10 parameters in the control scheme is investigated. For real-time control, Xilinx Spartan II SP200 FPGA (Field Programmable Gate Array) is employed to construct a hardware-in-the-loop system through writing VHDL on this FPGA.
TL;DR: A modified IMC-based controller design is proposed to deal with step- or ramp-type load disturbance that is often encountered in engineering practices, based on a two-degree-of-freedom (2DOF) control structure that allows for separate optimization of load disturbance rejection from setpoint tracking.
Abstract: In view of the deficiencies in existing internal model control (IMC)-based methods for load disturbance rejection for integrating and unstable processes with slow dynamics, a modified IMC-based controller design is proposed to deal with step- or ramp-type load disturbance that is often encountered in engineering practices. By classifying the ways through which such load disturbance enters into the process, analytical controller formulae are correspondingly developed, based on a two-degree-of-freedom (2DOF) control structure that allows for separate optimization of load disturbance rejection from setpoint tracking. An obvious merit is that there is only a single adjustable parameter in the proposed controller, which in essence corresponds to the time constant of the closed-loop transfer function for load disturbance rejection, and can be monotonically tuned to meet a good trade-off between disturbance rejection performance and closed-loop robust stability. At the same time, robust tuning constraints are given to accommodate process uncertainties in practice. Illustrative examples from the recent literature are used to show effectiveness and merits of the proposed method for different cases of load disturbance.
TL;DR: A new PCA method based on variance sensitive adaptive threshold (T(vsa)) is proposed to overcome false alarms which occur in the transient states according to changing process conditions and the missing data problem.
Abstract: Principal Component Analysis (PCA) is a statistical process monitoring technique that has been widely used in industrial applications. PCA methods for Fault Detection (FD) use data collected from a steady-state process to monitor T 2 and Q statistics with a fixed threshold. For the systems where transient values of the processes must be taken into account, the usage of a fixed threshold in PCA method causes false alarms and missing data that significantly compromise the reliability of the monitoring systems. In the present article, a new PCA method based on variance sensitive adaptive threshold ( T v s a ) is proposed to overcome false alarms which occur in the transient states according to changing process conditions and the missing data problem. The proposed method is implemented and validated experimentally on an electromechanical system. The method is compared with the conventional monitoring methods. Experimental tests and tabulated results confirm the fact that the proposed method is applicable and effective for both the steady-state and transient operations and gives early warning to operators.
TL;DR: A new surface in an active sliding mode to synchronize two chaotic systems with parametric uncertainty is defined, where the appropriate eigenvalues are easily assigned and calculation of parameters of the controller becomes simpler than the classical alternative.
Abstract: This paper defines a new surface in an active sliding mode to synchronize two chaotic systems with parametric uncertainty. To verify the capability of the proposed scheme, signals are also contaminated by measurement noise. The integral acting surface produces a dynamics for error, where the appropriate eigenvalues are easily assigned. Using this surface, calculation of parameters of the controller becomes simpler than the classical alternative. A sufficient condition, as a guideline of the designated procedure, is dedicated to provide a robust stability of the error dynamics. Finally, a simulation study is performed to verify the robustness and effectiveness of the proposed control strategy.
TL;DR: The proposed tuning methodology is independent of the specific choice of plant and is also applicable for less complicated systems, thus it is useful in a wide variety of scenarios.
Abstract: The issues of stochastically varying network delays and packet dropouts in Networked Control System (NCS) applications have been simultaneously addressed by time domain optimal tuning of fractional order (FO) PID controllers. Different variants of evolutionary algorithms are used for the tuning process and their performances are compared. Also the effectiveness of the fractional order PI λ D μ controllers over their integer order counterparts is looked into. Two standard test bench plants with time delay and unstable poles which are encountered in process control applications are tuned with the proposed method to establish the validity of the tuning methodology. The proposed tuning methodology is independent of the specific choice of plant and is also applicable for less complicated systems. Thus it is useful in a wide variety of scenarios. The paper also shows the superiority of FOPID controllers over their conventional PID counterparts for NCS applications.
TL;DR: The proposed method indicates a general form of the PID parameters and unifies a large number of existing rules as PI/PD/PID controller tuning with various GPM specifications.
Abstract: In this paper, an analytical method is proposed for proportional–integral/proportional–derivative/proportional–integral–derivative (PI/PD/PID) controller tuning with specified gain and phase margins (GPMs) for integral plus time delay (IPTD) processes. Explicit formulas are also obtained for estimating the GPMs resulting from given PI/PD/PID controllers. The proposed method indicates a general form of the PID parameters and unifies a large number of existing rules as PI/PD/PID controller tuning with various GPM specifications. The GPMs realized by existing PID tuning rules are computed and documented as a reference for control engineers to tune the PID controllers.
TL;DR: Performance of the proposed dynamic set-point weighting based PI controller (DSWPI) for various second- and third-order processes shows a significant improvement during both the set- point and load disturbance responses over other methods.
Abstract: Responses of high-order systems under Ziegler-Nichols tuned PI controllers (ZNPIs) are characterized by excessive oscillation with a large overshoot. Although, a fixed set-point weighting based PI controller (FSWPI) may decrease the overshoot considerably, it fails to reduce the oscillation in the set-point response. Moreover, both FSWPI and ZNPI exhibit equally poor load regulation. Keeping in mind an overall improved performance, we propose an online dynamic set-point weighting technique for ZNPIs. The dynamic set-point weighting factor (β(d)) is heuristically derived from the instantaneous process trend. Performance of the proposed dynamic set-point weighting based PI controller (DSWPI) for various second- and third-order processes including a pH process shows a significant improvement during both the set-point and load disturbance responses over other methods. Stability and robustness of the proposed DSWPI are addressed. Effectiveness of the DSWPI is demonstrated through the real-time implementation on a practical DC position control system.
TL;DR: A dynamic model with heat transfer coefficients which depend on temperature and flow used to estimate the output temperatures of a heat exchanger provides a satisfactory approximation of the states of the heat exchangers in order to allow its implementation in a FDI system used to perform supervision tasks.
Abstract: This paper deals with fault detection and isolation (FDI) in sensors applied to a concentric-pipe counter-flow heat exchanger. The proposed FDI is based on the analytical redundancy implementing nonlinear high-gain observers which are used to generate residuals when a sensor fault is presented (as software sensors). By evaluating the generated residual, it is possible to switch between the sensor and the observer when a failure is detected. Experiments in a heat exchanger pilot validate the effectiveness of the approach. The FDI technique is easy to implement allowing the industries to have an excellent alternative tool to keep their heat transfer process under supervision. The main contribution of this work is based on a dynamic model with heat transfer coefficients which depend on temperature and flow used to estimate the output temperatures of a heat exchanger. This model provides a satisfactory approximation of the states of the heat exchanger in order to allow its implementation in a FDI system used to perform supervision tasks.
TL;DR: New robust lag, lag-lead, PI controller design methods for control systems with a fractional order interval transfer function (FOITF) are proposed using classical design methods with the Bode envelopes of the FOITF to satisfy the robust performance specifications of the fractionalOrder interval plant.
Abstract: This paper presents some classical controller design techniques for the fractional order case. New robust lag, lag-lead, PI controller design methods for control systems with a fractional order interval transfer function (FOITF) are proposed using classical design methods with the Bode envelopes of the FOITF. These controllers satisfy the robust performance specifications of the fractional order interval plant. In order to design a classical PID controller, an optimization technique based on fractional order reference model is used. PID controller parameters are obtained using the least squares optimization method. Different PID controller parameters that satisfy stability have been obtained for the same plant.
TL;DR: This article proposes a simple identification procedure for second order inverse response processes, based on the plant step response, which provides the model parameters in a sequential way, thus avoiding the solution of a nonlinear equation system.
Abstract: Simple algorithms for identification of inverse response models from step response are difficult to obtain because analytically the solution of a system of coupled nonlinear equations is required. In this article we propose a simple identification procedure for second order inverse response processes, based on the plant step response. The algorithm provides the model parameters in a sequential way, thus avoiding the solution of a nonlinear equation system. Moreover the algorithm is flexible because it can be suited to user requirements, thus modifying the algorithm performance. Finally error bounds on the identified parameters are provided which are useful if the model is used for control design purposes.
TL;DR: Autotuning using relay feedback is widely used to identify low order integrating plus dead time (IPDT) systems as the method is simple and is operated in closed-loop without interrupting the production process.
Abstract: Autotuning using relay feedback is widely used to identify low order integrating plus dead time (IPDT) systems as the method is simple and is operated in closed-loop without interrupting the production process. Oscillatory responses from the process due to ideal relay input are collected to calculate ultimate properties of the system that in turn are used to model the responses as functions of system model parameters. These theoretical models of relay response are validated. After adjusting the phase shift, input and output responses are used to find land mark points that are used to formulate algorithms for parameter estimation of the process model. The method is even applicable to distorted relay responses due to load disturbance or measurement noise. Closed-loop simulations are carried out using model based control strategy and performances are calculated.
TL;DR: The design and implementation of a recurrent neural network (RNN) based inferential state estimation scheme for an ideal reactive distillation column and the performance of RNN shows better state estimation capability as compared to other state estimation schemes in terms of qualitative and quantitative performance indices.
Abstract: In this research work, the authors have presented the design and implementation of a recurrent neural network (RNN) based inferential state estimation scheme for an ideal reactive distillation column. Decentralized PI controllers are designed and implemented. The reactive distillation process is controlled by controlling the composition which has been estimated from the available temperature measurements using a type of RNN called Time Delayed Neural Network (TDNN). The performance of the RNN based state estimation scheme under both open loop and closed loop have been compared with a standard Extended Kalman filter (EKF) and a Feed forward Neural Network (FNN). The online training/correction has been done for both RNN and FNN schemes for every ten minutes whenever new un-trained measurements are available from a conventional composition analyzer. The performance of RNN shows better state estimation capability as compared to other state estimation schemes in terms of qualitative and quantitative performance indices.
TL;DR: The receding horizon H(∞) control (RHHC) problem is investigated in this paper for a class of networked control systems (NCSs) with random delay and packet disordering by solving a semi-definite programming (SDP) with linear matrix inequalities (LMIs) constraint.
Abstract: The receding horizon H ∞ control (RHHC) problem is investigated in this paper for a class of networked control systems (NCSs) with random delay and packet disordering. A new model is proposed to describe the NCS with random delay which may be larger than one sampling period. The random delay is modeled as a Markov chain while the closed-loop system is described as a Markovian jump system. Sufficient conditions for the closed-loop NCS to be stochastically stable and the performance index to be upper bounded are derived by using the receding optimization principle. Furthermore, by solving a semi-definite programming (SDP) with linear matrix inequalities (LMIs) constraint, a piecewise-constant receding horizon H ∞ controller is obtained, and the designed piecewise-constant controller ensures that the closed-loop NCS achieves a prescribed H ∞ disturbance attenuation level. Finally, an illustrative example is given to demonstrate the effectiveness of the proposed method.
TL;DR: The proposed method of backstepping sliding mode control can accomplish accurate tracking circle trajectory performance, offering an improvement in the tracking error of more than 50% over that of the PID controller.
Abstract: Air motors are increasingly being used in pneumatic related industries because of their advantages of low operating cost and low maintenance. The DSP controller and the backstepping sliding mode control method were utilized in this study to control an X-Y pneumatic table for tracking trajectory. Due to the effects of the compressibility of air, friction between the motor and ball screw table and the dead-zone effect caused by the proportional valve, the system will yield different responses even with the same inlet pressure and will chatter at low speed. Hence under certain conditions, this method of backstepping sliding mode control can be applied to achieve better results than with the PID controller, such as for tracking circle error and tracking error of the two axes. According to the results, a steady-state error of 0.5 μm can be achieved. The proposed method of backstepping sliding mode control can accomplish accurate tracking circle trajectory performance, offering an improvement in the tracking error of more than 50% over that of the PID controller.
TL;DR: The simulation and experimental results of this proposed algorithm show an adequate dynamic to IM and can be extended to include synchronous motors as well, confirming the feasibility of the proposed strategy compared to the conventional one.
Abstract: This paper describes a torque ripple reduction technique with constant switching frequency for direct torque control (DTC) of an induction motor (IM). This method enables a minimum torque ripple control. In order to obtain a constant switching frequency and hence a torque ripple reduction, we propose a control technique for IM. It consists of controlling directly the electromagnetic torque by using a modulated hysteresis controller. The design methodology is based on space vector modulation (SVM) of electrical machines with digital vector control. MATLAB simulations supported with experimental study are used. The simulation and experimental results of this proposed algorithm show an adequate dynamic to IM; however, the research can be extended to include synchronous motors as well. The implementation of the proposed algorithm is described. It doesn't require any PI controller in the torque control loop. The hardware inverter is controlled digitally using a Texas Instruments TMS320F240 digital signal processor (DSP) with composed C codes for generating the required references. The results obtained from simulation and experiments confirmed the feasibility of the proposed strategy compared to the conventional one.
TL;DR: A Discrete Event System (DES) approach for Intrusion Detection System (IDS) for LAN specific attacks which do not require any extra constraint like static IP-MAC, changing the ARP etc.
Abstract: Address Resolution Protocol (ARP) is used for determining the link layer or Medium Access Control (MAC) address of a network host, given its Internet Layer (IP) or Network Layer address. ARP is a stateless protocol and any IP-MAC pairing sent by a host is accepted without verification. This weakness in the ARP may be exploited by malicious hosts in a Local Area Network (LAN) by spoofing IP-MAC pairs. Several schemes have been proposed in the literature to circumvent these attacks; however, these techniques either make IP-MAC pairing static, modify the existing ARP, patch operating systems of all the hosts etc. In this paper we propose a Discrete Event System (DES) approach for Intrusion Detection System (IDS) for LAN specific attacks which do not require any extra constraint like static IP-MAC, changing the ARP etc. A DES model is built for the LAN under both a normal and compromised (i.e., spoofed request/response) situation based on the sequences of ARP related packets. Sequences of ARP events in normal and spoofed scenarios are similar thereby rendering the same DES models for both the cases. To create different ARP events under normal and spoofed conditions the proposed technique uses active ARP probing. However, this probing adds extra ARP traffic in the LAN. Following that a DES detector is built to determine from observed ARP related events, whether the LAN is operating under a normal or compromised situation. The scheme also minimizes extra ARP traffic by probing the source IP-MAC pair of only those ARP packets which are yet to be determined as genuine/spoofed by the detector. Also, spoofed IP-MAC pairs determined by the detector are stored in tables to detect other LAN attacks triggered by spoofing namely, man-in-the-middle (MiTM), denial of service etc. The scheme is successfully validated in a test bed.