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In this paper, we present and implement a hybrid approach to robust visual servoing for autonomous ground vehicles. A vision integrated model for nonholonomic mobile robots is derived that obviates the need for actual depth data for image-based visual servoing by assuming planar motion. A fractional order sliding-mode controller has been designed where the parameters of the sliding surface are adapted in real time. These adaptive laws are so derived that ensure finite-time convergence. An optical flow based heading restoration law is designed to handle the severe external perturbations, i.e., when the visual marker disappears from the field of view of the camera. The heading restoration law is combined with the reinforcement learning to solve this visibility problem. The proposed algorithm enables the robot to reach the home location even when the visual marker momentarily disappears from the camera field of view due to external disturbances. The proposed algorithm is validated in real time using Pioneer P3-DX robots through perturbation studies. Both simulation and experimental results prove the efficacy of the proposed scheme.

This paper addresses the problem of robust relative motion control in a multirobotic system using the artificial potential field (APF) method for path planning and fast adaptive gain nonsingular terminal sliding mode control (NTSMC) technique for designing a robust controller. A fast adaptive reaching law is also proposed to further improve the speed of convergence. The proposed sliding surface as well as the novel formation error utilizes only the relative position measurements of the follower with respect to the leader. The novel adaptive tuning algorithms are designed for tuning the controller parameters, in such a way that finite-time stability property of the NTSMC is retained. This will help to cope with uncertainties and varying operating conditions. An adaptive fuzzy-based fast reaching law is also proposed as an alternative to reduce the chattering. In the event of any critical system fault, to isolate the faulty robots and to facilitate the formation reconfiguration avoiding the collision between the healthy robots and the faulty ones, we have proposed a fault-tolerant APF module employing the fault parameters. The fault parameters are estimated using a residual-based synchronous fault-detection scheme. The efficacy of the proposed strategy has been validated through rigorous real-time experimentations.

This paper deals with the distributed fast and finite-time consensus problem of multiagent systems with bounded disturbances in a leader-follower-based frame work. A novel integral sliding mode-based robust finite-time event-triggered control strategy has been proposed. A fast reaching law is also utilized to improve the speed of convergence. The triggering condition is derived based on the defined novel measurement error, suited for systems with model uncertainties/disturbances. The expression for the lower bound for the interexecution time has been derived to ensure that the zeno behavior is avoided. The proposed nonlinear consensus protocol is such that the desired relative state deviation between the agents can be achieved with a directed graph topology. The theoretical results are validated through real-time experimentations done using Pioneer P3-DX as well as FireBird VI robots.

This work deals with the development of a decentralized optimal control algorithm, along with a robust observer, for the relative motion control of spacecraft in leader-follower based formation. An adaptive gain higher order sliding mode observer has been proposed to estimate the velocity as well as unmeasured disturbances from the noisy position measurements. A differentiator structure containing the Lipschitz constant and Lebesgue measurable control input, is utilized for obtaining the estimates. Adaptive tuning algorithms are derived based on Lyapunov stability theory, for updating the observer gains, which will give enough flexibility in the choice of initial estimates. Moreover, it may help to cope with unexpected state jerks. The trajectory tracking problem is formulated as a finite horizon optimal control problem, which is solved online. The control constraints are incorporated by using a nonquadratic performance functional. An adaptive update law has been derived for tuning the step size in the optimization algorithm, which may help to improve the convergence speed. Moreover, it is an attractive alternative to the heuristic choice of step size for diverse operating conditions. The disturbance as well as state estimates from the higher order sliding mode observer are utilized by the plant output prediction model, which will improve the overall performance of the controller. The nonlinear dynamics defined in leader fixed Euler-Hill frame has been considered for the present work and the reference trajectories are generated using Hill-Clohessy-Wiltshire equations of unperturbed motion. The simulation results based on rigorous perturbation analysis are presented to confirm the robustness of the proposed approach.

This paper deals with the design of a robust adaptive fuzzy nonsingular fast terminal sliding mode control strategy for the relative motion control of spacecraft in formation. A nonsingular terminal sliding surface, along with a fast reaching law, has been considered for fast and finite time convergence. Adaptive tuning algorithms are derived based on Lyapunov stability theory for updating the controller gains involved in the fast reaching law. In order to reduce the chattering, the discontinuous term in the reaching law has been replaced by a fuzzy inference mechanism. Lyapunov based adaptive tuning laws are derived for updating the fuzzy parameters involved. Numerical simulations based on nonlinear dynamics defined in leader centered Hill's frame, have been presented to prove the robustness of the proposed approach.

The formation control of satellites for remote sensing applications has received considerable attention during the past decade. This work deals with the development of a formation control strategy for the circular formation of a group of satellites. In this paper, artificial potential field method is used for path planning, and sliding mode control (SMC) technique is used for designing a robust controller. A fuzzy inference mechanism is utilized to reduce the chattering phenomenon inherent in the conventional SMC. An adaptive tuning algorithm is also derived based on Lyapunov stability theory to tune the fuzzy parameter. The proposed fuzzy-SMC-based technique is intended to compensate for the modeling uncertainties existing in practical applications. The results of simulations done for a group of five satellites making a circular formation confirm the stability and robustness of the present scheme.