This article presents the speed and direction angle control of a wheeled mobile robot based on a fractional-order adaptive model-based PID-type sliding mode control technique. Taking into account the individual benefits of the fractional calculus and the adaptive model-based PID-type sliding mode control method, the fractional order and the adaptive model-based PID-type sliding mode control technique are combined and proposed as an effective controller for the first time in the literature for real-time control of the wheeled mobile robot under the external payload. In this proposed method, several critical issues are considered; first, a kinematic and dynamic model of the wheeled mobile robot is analysed considering the system’s uncertainties. Second, fractional-order calculus and the model-based PID-type sliding mode control is composed to realize the chattering-free control, accurate trajectory tracking response, finite time convergence and robustness for the wheeled mobile robot. Finally, an adaptive process is also employed to meet and overcome the unknown dynamics and uncertain parameters of the system, regardless of the previous information of the uncertainties. The experimental outcomes demonstrate that the proposed controller (fractional-order adaptive model-based PID-type sliding mode controller) delivers an accurate trajectory tracking performance, faster finite-time convergence as well as having a smaller speed error under the external payload when the adaptive model-based PID-type sliding mode control is compared.

In this study, trajectory tracking control of six–degrees of freedom robotic manipulator has been performed using the proposed fractional-order adaptive integral sliding mode control scheme. The proposed method is first composed by fractional-order and adaptive integral sliding mode control to achieve the finite-time convergence, chattering-free control inputs, better tracking performance and robustness for the robotic manipulator. Furthermore, an adaptive method has been utilized to evaluate and compensate the uncertain and unknown dynamics of the system without relying on the prior knowledge of the upper bounds. To illustrate the efficiency of the proposed fractional-order adaptive integral sliding mode control method, the real-time experimental studies have been performed for the six–degrees of freedom industrial robot manipulator. The experimental outcomes strongly verified that the proposed controller gives quite well trajectory tracking response and faster convergence compared with the classical integral sliding mode control under the external payload.

The engine cooling systems in the commercial vehicles have not developed as the other control systems despite the technological improvements. Additionally, researchers in the automotive industry and the universities have focused on the power production and the combustion. Therefore, the thermal management of internal combustion engines, which has the same importance, does not taken into consideration sufficiently. However, optimum management of heat transfer system in the engines has an important effect on many parameters such as the engine performance, lubrication quality, exhaust emissions and fuel efficiency. It is necessary to define the engine cooling fluid temperature and flow rate profiles, and to follow them sensitively by a controller system to be designed. In this paper, it is aimed to design and to produce a thermal management system for internal combustion engines in order to ensure optimal distribution of the heat transfer. The electrically driven coolant pump and DC motor controlled valve is considered as control inputs. Additionally, robust control approach based on lumped parameter control - oriented model of engine cooling system is presented. Finally, the proposed and traditional engine cooling systems are compared by means of exhaust emission values.

This article presents the self-tuning regulator control technique for a coupled tank liquid level system that often used in industry. An autoregressive with exogenous model has been used as the liquid process model with the self-tuning control implementation in order to track the desired tank level trajectories with disturbances and uncertainties of the system dynamics. The designed self-tuning controller has been sensitive to parameter variations of the nonlinear coupled tank system. The parameters of the proposed controller are periodically updated themselves during the process by means of online recursive least square method with the forgetting factor algorithm. In this way, the parameter variations and unwanted disturbances of the system are eliminated in real-time application. In order to demonstrate the efficiency of the self-tuning regulator control technique, the real-time studies have been executed. The obtained experimental results demonstrated that the proposed controller gives the better trajectory tracking performance and smaller magnitude in overshot and undershot than the designed classical proportional–integral and sliding mode controllers.

This paper presents a new method that uses a feed-forward adaptive second order sliding mode control (FF-ASSMC) for a coupled tank process system that is often used in industry. This proposed method is to combine a feedforward action with adaptive feedback for robust performance of the couple tank system for the first time. The reason for using this feedforward action with the feedback sliding mode control (SMC) is to reduce the effect of the measured disturbance on the coupled tank system. In addition to this, an adaptive second-order SMC proposes to track the desired tank’s level trajectories under disturbances and uncertainties. In order to illustrate the efficiency of the proposed FF-ASSMC method, the simulation and real time experimental studies have been realized. The simulation and experimental outcomes strongly verified that the proposed controller gives a quite successful trajectory tracking response and smaller magnitude overshot under external disturbances.

SUMMARY: In this paper, design, analysis and real-time trajectory tracking control of a 6-degree of freedom revolute spherical-spherical type parallel manipulator, actuated by six hybrid stepper motors, has been studied. Two different control approaches have been used to improve the trajectory tracking performance of the designed manipulator. The first approach considered a single input-single output (SISO) linear quadratic regulator (LQR) for trajectory tracking control of the manipulator. Another controller type based on a nonlinear sliding mode controller method has been utilized to take decoupled dynamic approximation model of the manipulator into account and to improve tracking performance of the manipulator. Real-time experimental results for the two different control techniques have been verified. Finally, according to the results, the nonlinear sliding mode controller method has improved the tracking performance of the designed manipulator.