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Showing papers on "Open-loop controller published in 2011"


Journal ArticleDOI
TL;DR: This paper analyzes the stability problem of the grid-connected voltage-source inverter (VSI) with LC filters, which demonstrates that the possible grid-impedance variations have a significant influence on the system stability when conventional proportional-integrator (PI) controller is used for grid current control.
Abstract: This paper analyzes the stability problem of the grid-connected voltage-source inverter (VSI) with LC filters, which demonstrates that the possible grid-impedance variations have a significant influence on the system stability when conventional proportional-integrator (PI) controller is used for grid current control. As the grid inductive impedance increases, the low-frequency gain and bandwidth of the PI controller have to be decreased to keep the system stable, thus degrading the tracking performance and disturbance rejection capability. To deal with this stability problem, an H∞ controller with explicit robustness in terms of grid-impedance variations is proposed to incorporate the desired tracking performance and the stability margin. By properly selecting the weighting functions, the synthesized H∞ controller exhibits high gains at the vicinity of the line frequency, similar to the traditional proportional-resonant controller; meanwhile, it has enough high-frequency attenuation to keep the control loop stable. An inner inverter-output-current loop with high bandwidth is also designed to get better disturbance rejection capability. The selection of weighting functions, inner inverter-output-current loop design, and system disturbance rejection capability are discussed in detail in this paper. Both simulation and experimental results of the proposed H∞ controller as well as the conventional PI controller are given and compared, which validates the performance of the proposed control scheme.

388 citations


Journal ArticleDOI
TL;DR: In this paper, a 2 DOF planar robot was controlled by Fuzzy Logic Controller tuned with a particle swarm optimization and simulation results show that Fuzzies Logic Controller is better and more robust than the PID tuned by particle swarm optimized for robot trajectory control.
Abstract: In this paper, a 2 DOF planar robot was controlled by Fuzzy Logic Controller tuned with a particle swarm optimization. For a given trajectory, the parameters of Mamdani-type-Fuzzy Logic Controller (the centers and the widths of the Gaussian membership functions in inputs and output) were optimized by the particle swarm optimization with three different cost functions. In order to compare the optimized Fuzzy Logic Controller with different controller, the PID controller was also tuned with particle swarm optimization. In order to test the robustness of the tuned controllers, the model parameters and the given trajectory were changed and the white noise was added to the system. The simulation results show that Fuzzy Logic Controller tuned by particle swarm optimization is better and more robust than the PID tuned by particle swarm optimization for robot trajectory control.

231 citations


Journal ArticleDOI
TL;DR: In this article, a novel current control technique is proposed to control both active and reactive power flow from a renewable energy source feeding a microgrid system through a single-phase parallel-connected inverter.
Abstract: In this paper, a novel current control technique is proposed to control both active and reactive power flow from a renewable energy source feeding a microgrid system through a single-phase parallel-connected inverter. The parallel-connected inverter ensures active and reactive power flow from the grid with low-current total harmonic distortion even in the presence of nonlinear load. A p-q theory-based approach is used to find the reference current of the parallel-connected converter to ensure desired operating conditions at the grid terminal. The proposed current controller is simple to implement and gives superior performance over the conventional current controllers, such as rotating frame proportional-integral controller or stationary frame proportional resonant controller. The stability of the proposed controller is ensured by direct Lyapunov method. A new technique based on the spatial repetitive controller is also proposed to improve the performance of the current controller by estimating the grid and other periodic disturbances. Detailed experimental results are presented to show the efficacy of the proposed current control scheme along with the proposed nonlinear controller to control the active and reactive power flow in a single-phase microgrid under different operating conditions.

202 citations


Journal ArticleDOI
TL;DR: In this paper, an active fault-tolerant controller (AFTC) and a passive fault tolerant controller (PFTC) are designed for a 4.8 MW, variable speed, variable pitch wind turbine model with a fault in the pitch system.

193 citations


Journal ArticleDOI
TL;DR: In this article, the authors established a hierarchical platoon controller design framework comprising a feedback linearisation controller at the first layer and a guaranteed cost H� ₷-consuming controller, the kernel controller, at the second layer.
Abstract: The problem of autonomous platoon control via wireless communication network is studied in this study. Firstly, a novel hybrid model is established for the platoon's longitudinal movement, where disturbances of lead vehicle acceleration and wind gust, parameter uncertainties and intermediate uncertainties induced by communication network (e.g. time delay, quantisation and packet dropout) are given full considerations and involved in the model for the first time. Then, the authors establish a hierarchical platoon controller design framework comprising a feedback linearisation controller at the first layer and a guaranteed cost H ∞ controller at the second layer. By reducing the non-linear system to a linear model using the top layer feedback linearisation controller, a robust H ∞ controller, the kernel controller, is designed utilising novel techniques in robust control of time-delay systems. For the general objective of disturbance attenuation, string stability and robust platoon control to be achieved simultaneously, the robust H ∞ controller is complemented by additional conditions established for guaranteeing string stability and zero steady-state spacing errors. Simulations are given to show the efficiency of the proposed results.

170 citations


Journal ArticleDOI
TL;DR: In this paper, an artificial neural network (ANN) based controller is designed for the current control of the shunt active power filter and trained offline using data from the conventional proportional-integral controller.
Abstract: The application of artificial intelligence is growing fast in the area of power electronics and drives. The artificial neural network (ANN) is considered as a new tool to design control circuitry for power-quality (PQ) devices. In this paper, the ANN-based controller is designed for the current control of the shunt active power filter and trained offline using data from the conventional proportional-integral controller. A digital-signal-processor-based microcontroller is used for the real-time simulation and implementation of the control algorithm. An exhaustive simulation study is carried out to investigate the performance of the ANN controller and compare its performance with the conventional PI controller results. The system performance is also verified experimentally on a prototype model developed in the laboratory.

117 citations


Journal ArticleDOI
TL;DR: A novel sixth order nonlinear adaptive control algorithm is designed, which does not rely on nonrobust open loop integration of motor dynamics and guarantees, under persistency of excitation, local exponential rotor speed tracking.
Abstract: The tracking control problem is addressed for sensorless (nonsalient-pole surface) permanent magnet synchronous motors with unknown constant load torque. Assuming that only stator currents and voltages are available for feedback, a novel sixth order nonlinear adaptive control algorithm is designed, which does not rely on nonrobust open loop integration of motor dynamics and guarantees, under persistency of excitation, local exponential rotor speed tracking.

103 citations


Journal ArticleDOI
TL;DR: In this paper, a completely event-based two-degree-of-freedom proportional-integral controller is presented, which is based on decoupled solutions for the set-point following and the load disturbance rejection tasks.

98 citations


Journal ArticleDOI
TL;DR: An intelligent sliding-mode speed controller for achieving favorable decoupling control and high-precision speed tracking performance of permanent-magnet synchronous motor (PMSM) drives is proposed in this article.
Abstract: An intelligent sliding-mode speed controller for achieving favourable decoupling control and high-precision speed tracking performance of permanent-magnet synchronous motor (PMSM) drives is proposed. The intelligent controller consists of a sliding-mode controller (SMC) in the feedback loop in addition to an online trained wavelet-neural-network controller (WNNC) connected in parallel with the SMC to construct a robust wavelet-neural-network sliding-mode controller (RWNNSMC). The RWNNSMC controller combines the merits of the SMC with robust characteristics and the WNNC which combines the capability of artificial neural networks for online learning ability and the capability of wavelet decomposition for identification ability. The theoretical analyses of both SMC and WNNC speed controllers are developed. The WNN bound observer is utilised to predict the uncertain system dynamics to relax the requirement of uncertainty bound in the design of SMC. A computer simulation is developed to demonstrate the effectiveness of the proposed intelligent sliding-mode speed controller. An experimental system is established to verify the effectiveness of the proposed control system. All control algorithms are implemented in a TMS320C31 digital signal processor-based control computer. The simulated and experimental results confirm that the proposed RWNNSMC grants robust performance and precise response regardless of load disturbances and PMSM parameter uncertainties.

97 citations


Journal ArticleDOI
TL;DR: In this article, the authors proposed a Lyapunov approach to analysis and design of a class of nonlinear systems arising from power-electronic converters, where the problems considered include controller design for robust stability, and estimation of stability region and tracking domain.
Abstract: Power-electronic converters are intrinsically nonlinear. This paper proposes a Lyapunov approach to analysis and design of a class of nonlinear systems arising from power-electronic converters. The system has a bilinear term as the product of the state and the input-the duty cycle, which is subject to strict constraint (or saturation). The nonlinearities and the input saturation are considered in this paper by using piecewise-quadratic Lyapunov functions and by describing the system with a piecewise-linear differential inclusion. The problems considered include controller design for robust stability, and estimation of stability region and tracking domain. These analysis and design problems are converted into numerically efficient optimization algorithms involving linear-matrix inequalities (LMIs). A buck-boost dc-dc converter is used to demonstrate the proposed methods. The optimization results show that a simple state-feedback law can be constructed to achieve practically global stabilization and tracking, which is theoretically confirmed by the Lyapunov approach. An experimental buck-boost converter is constructed to verify the tracking of a square reference varying almost between the upper and the lower limit.

97 citations


Journal ArticleDOI
TL;DR: In this article, a nonlinear controller using backstepping technique is designed for the clutch-slip control, and the controller is designed such that the error dynamics is input-to-state stable.
Abstract: To improve the shift quality of vehicles with clutch-to-clutch gearshifts, a nonlinear controller using backstepping technique is designed for the clutch-slip control. Model uncertainties including steady-state errors and unmodeled dynamics are also considered as additive disturbance inputs, and the controller is designed such that the error dynamics is input-to-state stable. Lookup tables, which are widely used to represent complex nonlinear characteristics of engine systems, appear in their original form in the designed nonlinear controller. Finally, the designed controller is tested on an AMESim power train simulation model. Comparisons with an existing linear algorithm are given as well.

Journal ArticleDOI
TL;DR: Power-system stability improvement by a static synchronous series compensator (SSSC)-based damping controller is thoroughly investigated and compared with a recently published modern heuristic optimization technique under various disturbances to show the effectiveness and robustness of the proposed approach.
Abstract: Power-system stability improvement by a static synchronous series compensator (SSSC)-based damping controller is thoroughly investigated in this paper. Both local and remote signals with associated time delays are considered in the present study. The design problem of the proposed controller is formulated as an optimization problem, and differential evolution (DE) algorithm is employed to search for the optimal controller parameters. The performances of the proposed controllers are evaluated under different disturbances for both single-machine infinite-bus power system and multi-machine power system. The performance of the proposed controllers with variations in the signal transmission delays has also been investigated. Simulation results are presented and compared with a recently published modern heuristic optimization technique under various disturbances to show the effectiveness and robustness of the proposed approach. The performances of the proposed controllers are also evaluated under N −2 contingency situation.

01 Jan 2011
TL;DR: A mathematical tunable gain model free PID-like sliding mode fuzzy controller (GTSMFC) is designed to rich the best performance and reduce the limitation in fuzzy logic controller and sliding mode controller.
Abstract: In this study, a mathematical tunable gain model free PID-like sliding mode fuzzy controller (GTSMFC) is designed to rich the best performance. Sliding mode fuzzy controller is studied because of its model free, stable and high performance. Today, most of systems (e.g., robot manipulators) are used in unknown and unstructured environment and caused to provide sophisticated systems, therefore strong mathematical tools (e.g., nonlinear sliding mode controller) are used in artificial intelligent control methodologies to design model free nonlinear robust controller with high performance (e.g., minimum error, good trajectory, disturbance rejection). Non linear classical theories have been applied successfully in many applications, but they also have some limitation. One of the best nonlinear robust controller which can be used in uncertainty nonlinear systems, are sliding mode controller but pure sliding mode controller has some disadvantages therefore this research focuses on applied sliding mode controller in fuzzy logic theory to solve the limitation in fuzzy logic controller and sliding mode controller. One of the most important challenging in pure sliding mode controller and sliding mode fuzzy controller is sliding surface slope. This paper focuses on adjusting the gain updating factor and sliding surface slope in PID like sliding mode fuzzy controller to have the best performance and reduce the limitation.

Journal ArticleDOI
TL;DR: An adaptive proportional-integral-derivative (APID) control system to deal with the metallic sphere position control of a magnetic levitation system (MLS), which is an intricate and highly nonlinear system.
Abstract: This paper develops an adaptive proportional-integral-derivative (APID) control system to deal with the metallic sphere position control of a magnetic levitation system (MLS), which is an intricate and highly nonlinear system. The proposed control system consists of an adaptive PID controller and a fuzzy compensation controller. The adaptive PID controller is a main tracking controller, and the parameters of the adaptive PID controller are online tuned by the derived adaptation laws. In this design, the particle swarm optimization (PSO) technology is adopted to search the optimal learning-rates of the adaptive PID controller to increase the learning speed. The design of the fuzzy compensation controller can guarantee the stability of the control system. Since system-on-programmable-chip (SoPC) has several benefits including low cost, high speed, and small volume, the developed control scheme is implemented in the SoPC-based hardware. Finally, simulation and experimental results of the magnetic levitation system have been performed to verify the effectiveness of the proposed control scheme.

Journal ArticleDOI
TL;DR: In this article, an adaptive robust tracking controller for WMRs is proposed to cope with both parametric and nonparametric uncertainties in the robot model, where an adaptive nonlinear control law is designed based on input-output feedback linearization technique to get asymptotically exact cancellation of the parametric uncertainty in the WMR parameters.
Abstract: In this paper, the integrated kinematic and dynamic trajectory tracking control problem of wheeled mobile robots (WMRs) is addressed. An adaptive robust tracking controller for WMRs is proposed to cope with both parametric and nonparametric uncertainties in the robot model. At first, an adaptive nonlinear control law is designed based on input-output feedback linearization technique to get asymptotically exact cancellation of the parametric uncertainty in the WMR parameters. The designed adaptive feedback linearizing controller is modified by two methods to increase the robustness of the controller: (1) a leakage modification is applied to modify the integral action of the adaptation law and (2) the second modification is an adaptive robust controller, which is included to the linear control law in the outer loop of the adaptive feedback linearizing controller. The adaptive robust controller is designed such that it estimates the unknown constants of an upper bounding function of the uncertainty due to friction, disturbances and unmodeled dynamics. Finally, the proposed controller is developed for a type (2, 0) WMR and simulations are carried out to illustrate the robustness and tracking performance of the controller.

01 Jan 2011
TL;DR: In this article, the authors applied the Mamdani's error-based fuzzy logic controller with minimum rules to eliminate the nonlinear dynamic in SMC and computed torque controller with tunable gain (GTCTLC).
Abstract: One of the most active research areas in the field of robotics is robot manipulators control, because these systems are multi-input multi-output (MIMO), nonlinear, time variant and uncertainty. An artificial non linear robust controller design is major subject in this work. At present, robot manipulators are used in unknown and unstructured situation and caused to provide complicated systems, consequently nonlinear classical controllers are used in artificial intelligence control methodologies to design nonlinear robust controller with satisfactory performance (e.g., minimum error, good trajectory, disturbance rejection). Sliding mode controller (SMC) and computed torque controller (CTC) are the best nonlinear robust controllers which can be used in uncertainty nonlinear. Sliding mode controller has two most important challenges in uncertain systems: chattering phenomenon and nonlinear dynamic equivalent part. Computed torque controller works very well when all nonlinear dynamic parameters are known. This research is focused on the applied non-classical method (e.g., Fuzzy Logic) in robust classical method (e.g., Sliding Mode Controller and computed torque controller) in the presence of uncertainties and external disturbance to reduce the limitations. Applying the Mamdani’s error based fuzzy logic controller with minimum rules is the first goal that causes the elimination of the mathematical nonlinear dynamic in SMC and CTC. Second target focuses on the elimination of chattering phenomenon with regard to the variety of uncertainty and external disturbance in fuzzy sliding mode controller and computed torque like controller by optimization the tunable gain. Therefore fuzzy sliding mode controller with tunable gain (GTFSMC) and computed torque like controller with tunable gain (GTCTLC) will be presented in this paper.

Journal ArticleDOI
TL;DR: In this paper, a robust current control scheme for inductor-capacitor-inductor (LCL)-filtered distributed generation (DG) inverters featuring effective suppression of low and high-frequency instabilities and grid-induced distortion and disturbances is presented.
Abstract: This paper presents a robust current control scheme for inductor-capacitor-inductor (LCL)-filtered distributed generation (DG) inverters featuring effective suppression of low- and high-frequency instabilities and grid-induced distortion and disturbances. The conceptual design of the proposed control scheme is to maximize the disturbance rejection performance against grid disturbances and parametric uncertainties, and minimize the coupling among active damping, disturbance rejection, and tracking controllers. First, a simple and robust active damping controller is realized by drooping the inverter control voltage with the capacitor current. Second, the augmented damped dynamics is used to design a robust controller, which is composed of a tracking controller, dynamic grid-disturbance rejection controller, and uncertainty rejection controller. The tracking controller is designed to yield deadbeat control performance to maximize the dynamic performance of the converter. The grid-disturbance rejection controller is designed to provide a base-line of grid-induced dynamics within the closed-loop system as an internal model; therefore, effective mitigation of grid-induced distortion can be achieved without a priori knowledge of the frequency modes to be eliminated. The uncertainty rejection controller is designed to reject voltage disturbances associated with parameter variation and imperfect compensation of the grid-disturbance-rejection controller. Theoretical analysis and comparative test results are presented to demonstrate the effectiveness of the proposed control scheme.

Journal ArticleDOI
TL;DR: A neuro-fuzzy adaptive control approach for nonlinear dynamical systems, coupled with unknown dynamics, modeling errors, and various sorts of disturbances, is proposed and used to design a wheel slip regulating controller.

Journal ArticleDOI
TL;DR: In this paper, the authors investigated the control problem of switched singular systems aiming to compress their inconsistent state jumps when switch occurs between two different singular subsystems and proposed a hybrid impulsive controller consisting of a feedback controller and an impulsive control.
Abstract: In this study, the authors investigate the control problem of switched singular systems aiming to compress their inconsistent state jumps when switch occurs between two different singular subsystems. The proposed hybrid impulsive controller consists of a feedback controller and an impulsive controller. With introduction of the impulsive controller, the state at each switching instant for the closed-loop system can be changed. Based on the given controller structure, some sufficient conditions are derived under which the closed-loop system is admissible (regular, impulse free and stable) and such a controller has the capability of eliminating or minimising the instantaneous state jumps at switching instants. The validity and advantage of the proposed hybrid impulsive controller are illustrated using two examples.

Journal ArticleDOI
TL;DR: A novel master-slave controller is proposed, which renders the entire system stable with relatively good steady- and transient-state performances and the stability of the closed-loop system is proved.
Abstract: This paper addresses the controller design problem for teleoperation over networks such as the Internet. The forward and backward network transmission time delays are assumed to be asymmetric and time varying, which is the case for computer network communications. We propose a novel master-slave controller, which renders the entire system stable with relatively good steady- and transient-state performances. The relations among the parameters of the controller and the allowable maximum time delays are built in the form of linear matrix inequality. The designed controller is extended to the case that the velocity information is not available. A high-gain observer is designed to estimate the velocities of the master and slave joints online, and the controller is constructed on the basis of the estimated velocities. The stability of the closed-loop system is proved. Both simulations and experiments are performed to verify the correctness and effectiveness of the proposed method.

01 Jan 2011
TL;DR: This research focuses on the intelligent control of robot manipulator using Adaptive Fuzzy Gain scheduling computed torque controller (AFGSCTC) and various performance indices like the RMS error and Steady state error are used for test the controller performance.
Abstract: Refer to the research, a position adaptive fuzzy gain scheduling computed torque controller (AFGSCTC) design and application to robot manipulator has proposed in order to design high performance nonlinear controller in the presence of uncertainties. Regarding to the positive points in computed torque controller (CTC), fuzzy logic controller and adaptive method, the output has improved. Each method by adding to the previous controller has covered negative points. The main target in this research is analyses and design of the position controller for robot manipulator to reach an acceptable performance. Obviously, robot manipulator is nonlinear and a number of parameters are uncertain, this research focuses on design the best performance computed torque controller with regard to the fuzzy logic to select the best controller for the industrial manipulator. Although CTC controller has acceptable performance with known dynamic parameters but by regarding to uncertainty, the computed torque controller's output has fairly fluctuations. To eliminate CTC's fluctuations with regarding to uncertainty fuzzy logic method applied in computed torque controller. This controller works very well in uncertain environment or various dynamic parameters. This paper focuses on the intelligent control of robot manipulator using Adaptive Fuzzy Gain scheduling computed torque controller (AFGSCTC) and various performance indices like the RMS error and Steady state error are used for test the controller performance.

01 Jan 2011
TL;DR: This research focuses on applied fuzzy logic controller in sliding mode controller, which can be used in uncertainty nonlinear systems, and design a supervisory controller to adjusting the sliding surface slope in slide mode fuzzy controller.
Abstract: Robotic manipulators are multi-input multi-output (MIMO), nonlinear and most of dynamic parameters are uncertainty so design a high performance controller for these plants is very important. Today, strong mathematical tools used in new control methodologies to design adaptive nonlinear robust controller with acceptable performance. One of the best nonlinear robust controller which can be used in uncertainty nonlinear systems, are sliding mode controller but pure sliding mode controller has some disadvantages such as nonlinear dynamic uncertainties therefore to design model free sliding mode controller this research focuses on applied fuzzy logic controller in sliding mode controller. One of the most important challenging in pure sliding mode controller and sliding mode fuzzy controller is sliding surface slope coefficient therefore the second target in this research is design a supervisory controller to adjusting the sliding surface slope in sliding mode fuzzy controller.

Journal ArticleDOI
TL;DR: In this paper, a new tuning procedure is proposed for the ideal PID controller in series with the first-order noise filter, based on the recently proposed extension of the Ziegler-Nichols frequency-domain dynamics characterization of a process.

Proceedings ArticleDOI
21 Jun 2011
TL;DR: The results from the experiments show that the proposed a hybrid of fuzzy and fuzzy self-tuning PID controller has superior performance when applied to servo electro-hydraulic system (SEHS).
Abstract: Because of the existing hybrid fuzzy PID controller does not perform well when applied to servo electro-hydraulic system (SEHS). Forasmuch, when the system parameters changes will require a new adjustment variable of PID controller. Therefore, a hybrid of fuzzy and fuzzy self-tuning PID controller is proposed in this paper. The proposed control scheme is separated into two parts, fuzzy controller and fuzzy self-tuning PID controller. Fuzzy controller is used to control systems when the output value of system far away from the target value. Fuzzy self-tuning PID controller is applied when the output value is near the desired value. In the terms of adjusting the PID parameters are tuned by using fuzzy tuner as to obtain the optimum value. We demonstrate the performance of control scheme via experiments performed on the motor speed control of the SEHS. The results from the experiments show that the proposed a hybrid of fuzzy and fuzzy self-tuning PID controller has superior performance compared to a hybrid of fuzzy and PID controller.

01 Jan 2011
TL;DR: This research focuses on comparison between sliding mode algorithm and fuzzy logic controller and adaptive method in order to design high performance nonlinear controller in the presence of uncertainties.
Abstract: Refer to the research, review of sliding mode controller is introduced and application to robot manipulator has proposed in order to design high performance nonlinear controller in the presence of uncertainties. Regarding to the positive points in sliding mode controller, fuzzy logic controller and adaptive method, the output in most of research have improved. Each method by adding to the previous algorithm has covered negative points. Obviously robot manipulator is nonlinear, and a number of parameters are uncertain, this research focuses on comparison between sliding mode algorithm which analyzed by many researcher. Sliding mode controller (SMC) is one of the nonlinear robust controllers which it can be used in uncertainty nonlinear dynamic systems. This nonlinear controller has two challenges namely nonlinear dynamic equivalent part and chattering phenomenon. A review of sliding mode controller for robot manipulator will be investigated in this research.

Journal ArticleDOI
TL;DR: It is shown by the experimental results that the favorable position tracking performance for the DC motor driver can be achieved by the proposed APID control scheme after learning of the controller parameters.
Abstract: The proportional-integral-derivative (PID) controller has been extensively applied in practical industry due to its appealing characteristics such as simple architecture, easy design and parameter tuning without complicated computation. However, the PID controller usually needs some a priori manual retuning to make a successful industrial application. To attack this problem, this paper proposes an adaptive PID (APID) controller which is composed of a PID controller and a fuzzy compensator. Without requiring preliminary offline learning, the PID controller can automatically online tune the control gains based on the gradient descent method and the fuzzy compensator is designed to eliminate the effect of the approximation error introduced by the PID controller upon the system stability in the Lyapunov sense. Finally, the proposed APID control system is applied to a DC motor driver and implemented on a field-programmable gate array (FPGA) chip for possible low-cost and high-performance industrial applications. It is shown by the experimental results that the favorable position tracking performance for the DC motor driver can be achieved by the proposed APID control scheme after learning of the controller parameters.

01 Jan 2011
TL;DR: An on-line tunable gain model free PID-like fuzzy controller (GTFLC) is designed forthree degrees of freedom (3DOF) robot manipulator to rich the best performance.
Abstract: In this study, an on-line tunable gain model free PID-like fuzzy controller (GTFLC) is designed forthree degrees of freedom (3DOF) robot manipulator to rich the best performance. Fuzzy logiccontroller is studied because of its model free and high performance. Today, robot manipulatorsare used in unknown and unstructured environment and caused to provide sophisticated systems,therefore strong mathematical tools are used in new control methodologies to design adaptivenonlinear robust controller with acceptable performance (e.g., minimum error, good trajectory,disturbance rejection). The strategies of control robot manipulator are classified into two maingroups: classical and non-classical methods, however non linear classical theories have beenapplied successfully in many applications, but they also have some limitation. One of the mostimportant nonlinear non classical robust controller that can used in uncertainty nonlinear systems,are fuzzy logic controller. This paper is focuses on applied mathematical tunable gain method inrobust non classical method to reduce the fuzzy logic controller limitations. Therefore on-linetunable PID like fuzzy logic controller will be presented in this paper.

Journal ArticleDOI
TL;DR: A new fuzzy model based inverse controller design methodology based on a recursive optimization procedure that searches for an optimal inverse model control signal at every sampling time is presented and implemented and tested on the two real time processes and very satisfactory results has been reported.
Abstract: The use of inverse system model as a controller might be an efficient way in controlling non-linear systems. It is also a known fact that fuzzy logic modeling is a powerful tool in representing nonlinear systems. Therefore, inverse fuzzy model can be used as a controller for controlling nonlinear plants. In this context, firstly, a new fuzzy model based inverse controller design methodology is presented in this study. The design methodology introduced here is based on a recursive optimization procedure that searches for an optimal inverse model control signal at every sampling time. Since the task of optimization should be accomplished in between two sampling periods the use of a fast optimization algorithm becomes essential. For this reason, Big Bang-Big Crunch (BB-BC) optimization algorithm is used due to its low computational time and high global convergence properties. Even though, inverse model controllers may produce perfect control while operating in an open loop fashion, this open loop control would not be sufficient in the case of modeling mismatches or disturbances that might occur over the system. In order to overcome this problem, secondly, an on-line adaptation mechanism via BB-BC optimization algorithm is introduced in addition to BB-BC optimization based fuzzy model inverse controller. The adaptation mechanism is used to update the related parameters of the model while minimizing the absolute value of the instantaneous error between the system and model outputs. In this manner, the system output is somehow fed back, the overall control form can be considered as a closed-loop system. The new fuzzy model based inverse control scheme with the new online adaptation mechanism has been implemented and tested on the two real time processes; namely, heat transfer and pH processes and very satisfactory results has been reported.

Journal ArticleDOI
TL;DR: In this article, an artificial intelligence Neuro-Fuzzy (NF) technique was used to design a robust controller to meet the control objectives of a vehicle suspension system, which reduced the discomfort sensed by passengers which arises from road roughness and increased the ride handling associated with the pitching and rolling movements.
Abstract: The main objective of designed the controller for a vehicle suspension system is to reduce the discomfort sensed by passengers which arises from road roughness and to increase the ride handling associated with the pitching and rolling movements. This necessitates a very fast and accurate controller to meet as much control objectives, as possible. Therefore, this paper deals with an artificial intelligence Neuro-Fuzzy (NF) technique to design a robust controller to meet the control objectives. The advantage of this controller is that it can handle the nonlinearities faster than other conventional controllers. The approach of the proposed controller is to minimize the vibrations on each corner of vehicle by supplying control forces to suspension system when travelling on rough road. The other purpose for using the NF controller for vehicle model is to reduce the body inclinations that are made during intensive manoeuvres including braking and cornering. A full vehicle nonlinear active suspension system is introduced and tested. The robustness of the proposed controller is being assessed by comparing with an optimal Fractional Order (FOPID) controller. The results show that the intelligent NF controller has improved the dynamic response measured by decreasing the cost function.

Journal ArticleDOI
TL;DR: In this paper, a real-time implementation of an improved emotional controller for induction motor (IM) drives is presented, which is called brain-emotional-learning-based intelligent controller.
Abstract: This paper presents a real-time implementation of an improved emotional controller for induction motor (IM) drives. The proposed controller is called brain-emotional-learning-based intelligent controller. The utilization of the new controller is based on the emotion-processing mechanism in the brain and is essentially an action selection, which is based on sensory inputs and emotional cues. This intelligent control is based on the limbic system of the mammalian brain. The controller is successfully implemented in real time using a PC-based three-phase 2.5-kW laboratory squirrel-cage IM. In this paper, a novel but simple model of the IM drive system is achieved by using the intelligent controller, which simultaneously controls the motor flux and speed. This emotional intelligent controller has a simple computational structure with high auto learning features. The proposed emotional controller has been experimentally implemented in a laboratory IM drive, and it shows good promise for niche industrial-scale utilization.