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.

This article presents an optimization technique to develop minimum energy consumption trajectories for redundant/hyper-redundant manipulators with predefined kinematic and dynamic constraints. The optimization technique presents and combines two novel methods for trajectory optimization. In the first method, the system’s kinematic and dynamic constraints are handled in a sequential manner within the cost function to avoid running the inverse dynamics when the constraints are not satisfied. Thus, the complexity and computational effort of the optimization algorithm is significantly reduced. For the second method, a novel virtual link concept is introduced to replace all the redundant links to eliminate physical impossible configurations before running the inverse dynamic model for the trajectory optimization. The method is verified on a three-degree of freedom redundant manipulator and the result is also demonstrated with computer simulations based on an 8-link planar hyper-redundant manipulator.

This paper is devoted to designing a fractional order Proportional Integral Derivative (PID) type sliding mode control method (FO-PIDSMC) for a non-linear liquid level coupled tank process system. By considering the individual advantages of the FO calculus and PID type SMC method, this proposed FO-PIDSMC technique is designed to integrate the FO calculus method with PID type SMC scheme to obtain an accurate and robust liquid level tracking in terms of the predefined reference trajectory. The real-time experimental results of the proposed controller suggest a dramatic improvement over the traditional process system controller methods in both trajectory tracking and required control action.

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.

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.