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Yayın A global optimal control methodology and its application to a mobile robot model(Elsevier B.V., 2016) Dinçmen, ErkinA global optimal control algorithm is developed and applied to an omni-directional mobile robot model. The aim is to search and find the most intense signal source among other signal sources in the operation region of the robot. In other words, the control problem is to find the global extremum point when there are local extremas. The locations of the signal sources are unknown and it is assumed that the signal magnitudes are maximum at the sources and their magnitudes are decreasing away from the sources. The distribution characteristics of the signals are unknown, i.e. the gradients of the signal distribution functions are unknown. The control algorithm also doesn't need any position measurement of the robot itself. Only the signal magnitude should be measured via a sensor mounted on the robot. The simulation study shows the performance of the controller.Yayın A gain-switched self-optimizer for braking controller(John Wiley and Sons Ltd, 2017-06) Dinçmen, ErkinAn emergency braking controller is developed with improved operation characteristics near the maximum friction zone. The methodology is based on self-seeking a-priori unknown optimum operation point to maximize a performance function representing the optimal behavior of the considered dynamic system. Sliding mode with uncertain direction of control vector approach is utilized in the algorithm. An adaptive variable gain is utilized in the algorithm to improve its performance. Via the variable gain, both fast convergence to the a-priori unknown optimum operation point and reduced magnitude of oscillations in the braking moment inputs resulting less aggressive control action are achieved.Yayın Design of a global extremum seeking algorithm for an omni-directional robot model(Romanian Soc Control Tech Informatics, 2017-06) Dinçmen, ErkinA global extremum seeking algorithm is developed for a mobile robot model where the aim is to find the location of the most powerful signal source among the others. In other words, the control problem is to seek the global extremum point of a performance function when there are local extremas. The locations of the signal sources and signal distribution characteristics are unknown, i.e. the gradient of the performance function is unknown. The control algorithm also doesn't use any position measurement of the mobile robot itself. Henceforth, the controller is suitable for the missions where the robot moves in an unknown terrain with no GPS signal and no inertial measurements. Only the signal magnitude should be measured via a sensor mounted on the robot during the motion. A gradient estimator is designed to determine the motion direction towards the extremum point. When a local extremum is found, the robot will continue its search for another extremum points. Once each extremums have been visited, the robot will compare the signal levels on each source and identify the global extremum i.e. the most powerful signal source. In the absence of any position measurements, the robot can move towards the global extremum by repeating its motion history backwards. In the literature, this is the first global extremum seeking algorithm that has been developed for an omni-directional mobile robot model. Via the simulation studies it has been shown that the control algorithm can seek and find both stationary and non stationary signal sources and it can find the global extremum point when there are local extremas.Yayın Extremum seeking dead-zone pre-compensator for an industrial control system(Walter De Gruyter GMBH, 2018-06-26) Dinçmen, ErkinPID type industrial controllers such as PI, PD, PID are mature control algorithms and they are intensively used in industry due to their simplicity and easily implementability. However, they start to fail when there is an unknown or unpredictable nonlinear behavior in the plant or actuator. In this paper, a novel compensation algorithm is proposed for PD type industrial control systems, which possess an unknown dead-zone nonlinearity. An extremum-seeking technique is utilized in the compensation algorithm. The aim is to propose a new, effective and robust compensator which can be added easily to an existing industrial controller without any need to change/retune the controller settings/parameters. It is shown that by adding the compensator to an existing PD control system, the sensitivity of the controller to the dead-zone nonlinearity is removed.Yayın Extremum seeking control of uncertain systems(Işık University Press, 2017) Dinçmen, ErkinExtremum seeking is used in control problems where the reference trajectory or reference set point of the system is not known but it is searched in real time in order to maximize or minimize a performance function representing the optimal behaviour of the system. In this paper, extremum seeking algorithm is applied to the systems with parametric uncertainties.Yayın An emergency braking controller based on extremum seeking with experimental implementation(Springer Berlin Heidelberg, 2018-03-01) Dinçmen, Erkin; Altınel, TunçAn extremum seeking scheme is developed for maximizing the longitudinal tire forces of the road vehicles during emergency braking situations. If the road condition is known, then a conventional braking controller could generate required braking moment to track the slip set point which belongs to that road condition. However, estimating the road condition is not an easy task and it brings additional computation effort. Rather than that, a self optimization algorithm is presented in this paper without relying on road condition estimation. The developed controller searches optimum operation point for getting maximum friction force. Computer simulations show the effectiveness of the self optimization routine. To validate the real time applicability of the algorithm, an electromechanical braking test system is used for the experiments. Due to the limited measurements from the experimental system, force and moment observers are designed to calculate necessary control inputs for maximizing the friction potential, i.e. the braking force. Via the experimental study, it has been shown that the developed self optimizing controller is fast, accurate, and operable on a real braking system.Yayın Adaptive extremum seeking scheme for ABS control(IEEE, 2014) Dinçmen, ErkinA sliding mode based extremum seeking algorithm is applied to the ABS control problem where the optimum slip ratio is searched online for maximum braking force in unknown road conditions. By making the parameter of the search algorithm adaptive, an adaptive extremum seeking scheme is proposed to improve the behavior of the controlled system around the optimum operating point. Simulation study is presented to illustrate the effectiveness of the methodology.Yayın A cooperative neural network control structure and its application for systems having dead-zone nonlinearities(Springer International Publishing Ag, 2022-03) Dinçmen, ErkinAn adaptive control structure utilizing two feed-forward neural networks (NN) is proposed to deal with systems having unknown nonlinearities. One of the networks is trained to mimic the nonlinear system dynamics. Its training will be repeated with periods in order to keep it an updated valid model of the system all the times since the parameters and/or nonlinearities of the system may change during time. The other network, which is the Controller NN, adapts itself continuously by collaborating with the Model NN. The stability-convergence analysis of both networks is performed via Lyapunov method. An example system is chosen to show the applicability of the control algorithm. This example system is created by combining a linear dynamics model with a dead-zone function to represent a nonlinear system to be controlled. It should be noted that the proposed control structure can be used in any nonlinear system without knowing the system dynamics. The only information required by Model NN is the training set consisting input-output data pairs of the system. The Model NN is trained offline with this training set, and afterward the Controller NN adapts its weights online continuously during the control task with the help of Model NN. The performances of PD and PID controllers are also given for comparison purposes.Yayın Extremum-seeking control of ABS braking in road vehicles with lateral force improvement(IEEE-INST Electrical Electronics Engineers Inc, 2014-01) Dinçmen, Erkin; Güvenç, Bilin Aksun; Acarman, TankutAn ABS control algorithm based on extremum seeking is presented in this brief. The optimum slip ratio between the tire patch and the road is searched online without having to estimate road friction conditions. This is achieved by adapting the extremum-seeking algorithm as a self-optimization routine that seeks the peak point of the tire force-slip curve. As an additional novelty, the proposed algorithm incorporates driver steering input into the optimization procedure to determine the operating region of the tires on the "tire force"-"slip ratio" characteristic-curve. The algorithm operates the tires near the peak point of the force-slip curve during straight line braking. When the driver demands lateral motion in addition to braking, the operating regions of the tires are modified automatically, for improving the lateral stability of the vehicle by increasing the tire lateral forces. A validated, full vehicle model is presented and used in a simulation study to demonstrate the effectiveness of the proposed approach. Simulation results show the benefits of the proposed ABS controller.Yayın Self optimizing ABS control algorithm with application(Institute of Electrical and Electronics Engineers Inc, 2015) Dinçmen, Erkin; Altınel, TunçA self optimizing control algorithm is applied to the ABS control problem where the algorithm accomplishes to maximize friction potential of the tires during braking in unknown road conditions. Simulation studies are conducted to show effectiveness of the controller. The algorithm is also tested in an experimental setup. In order to control a real electromechanical braking system, necessary observers are designed and integrated with the algorithm. Experimental study shows the performance of the control algorithm.
