Biped robot walking control on inclined planes with fuzzy parameter adaptation

The bipedal structure is suitable for a robot functioning in the human environment, and assuming assistive roles. However, the bipedal walk is a poses a difficult control problem. Walking on even floor is not satisfactory for the applicability of a humanoid robot. This paper presents a study on bipedal walk on inclined planes. A Zero Moment Point (ZMP) based reference generation technique is employed. The orientation of the upper body is adjusted online by a fuzzy logic system to adapt to different walking surface slopes. This system uses a sampling time larger than the one of the joint space position controllers. A newly defined measure of the oscillatory behavior of the body pitch angle and the average value of the pelvis pitch angle are used as inputs to the fuzzy adaptation system. A 12-degrees-of-freedom (DOF) biped robot model is used in the full-dynamics 3-D simulations. Simulations are carried out on even floor and inclined planes with different slopes. The results indicate that the fuzzy adaptation algorithms presented are successful in enabling the robot to climb slopes of 5.6 degrees (10 percent)

A survey on fractional order control techniques for unmanned aerial and ground vehicles

In recent years, numerous applications of science and engineering for modeling and control of unmanned aerial vehicles (UAVs) and unmanned ground vehicles (UGVs) systems based on fractional calculus have been realized. The extra fractional order derivative terms allow to optimizing the performance of the systems. The review presented in this paper focuses on the control problems of the UAVs and UGVs that have been addressed by the fractional order techniques over the last decade

Fuzzy sliding mode control of a multi-DOF parallel robot in rehabilitation environment

Multi-degrees of freedom (DOF) parallel robot, due to its compact structure and high operation accuracy, is a promising candidate for medical rehabilitation devices. However, its controllability relating to the nonlinear characteristics challenges its interaction with human subjects during the rehabilitation process. In this paper, we investigated the control of a parallel robot system using fuzzy sliding mode control (FSMC) for constructing a simple controller in practical rehabilitation, where a fuzzy logic system was used as the additional compensator to the sliding mode controller (SMC) for performance enhancement and chattering elimination. The system stability is guaranteed by the Lyapunov stability theorem. Experiments were conducted on a lower limb rehabilitation robot, which was built based on kinematics and dynamics analysis of the 6-DOF Stewart platform. The experimental results showed that the position tracking precision of the proposed FSMC is sufficient in practical applications, while the velocity chattering had been effectively reduced in comparison with the conventional FSMC with parameters tuned by fuzzy systems

Primjena tehnika mekog računalstva za upravljanje gibanjem robota

This paper considers the problem of the robot motion control in the presence of the major uncertainties such as it is varying load. Efficiency of one conventional and two soft computing model based control algorithms is investigated and compared trough the results of application on a direct drive robot. First control algorithm is a conventional computed torque based on the Lagrangian dynamic equations. Second method is a computed torque alike control with an adaptive fuzzy logic system that replaces Lagrangian model, and third is a continuous sliding mode control with an artificial neural network instead of the dynamic model. Both soft computing methods give excellent results, while inefficiency of the computed torque control confirms the disadvantages of the conventional model based motion control approaches.U članku se obrađuje problem upravljanja gibanjem robota uz djelovanje velikih neodređenosti kao što je promjenljivost tereta. Istražene su, i uspoređene na robotu s izravnim pogonima, jedna klasična metoda upravljanja i dvije metode zasnovane na tehnikama mekog računalstva. Prva je metoda upravljanja klasična metoda proračunavanja upravljačkog momenta pogonskih motora na osnovi Lagrangeovih jednadžbi koje opisuju dinamiku robota. Druga je metoda upravljanja slična klasičnoj metodi, ali se umjesto Lagrangeovih dinamičkih jednadžbi koristi adaptivni neizraziti sustav, a treća je metoda upravljanja zasnovana na kliznim režimima s primjenom neuronske mreže umjesto dinamičkog modela robota. Obje metode upravljanja zasnovane na tehnikama mekog računalstva dale su izvrsne rezultate u svim slučajevima, dok klasična metoda upravljanja nije dala dobre rezultate uz djelovanje neodređenosti u sustavu