This paper deals with the problem of the formation control of nonholonomic mobile robots in the leader–follower scenario without considering the leader information, as a result of its velocity and position. The kinematic model is reformulated as a formation model by incorporating the model uncertainties and external disturbance. The controller is presented in the two-step process. Firstly, the tracking problem is taken into consideration, which can be used as a platform to design a controller for the multi-agents. The proposed controller is designed based on a non-singular fast terminal sliding mode controller (FTSMC), which drives the tracking error to zero in finite time. It not only ensures the tracking but also handles the problem related to non-singularities. Moreover, the design control scheme is modified using high-gain observer to resolve the undefined fluctuations due to man-made errors in sensors. Secondly, the multi-agent tracking problem is considered; hence, a novel formation control is designed using FTSMC, which ensures the formation pattern as well as tracking. Furthermore, the obstacle avoidance algorithm is incorporated to avoid the collision, inside the region of interest. With the Lyapunov analysis, the stability of the proposed algorithm is verified. As a result, simulated graphs are shown to prove the efficacy of the proposed control scheme.

The article proposes a nonlinear optimal control method for the model of the wheeled inverted pendulum (WIP). This is a difficult control and robotics problem due to the system’s strong nonlinearities and due to its underactuation. First, the dynamic model of the WIP undergoes approximate linearization around a temporary operating point which is recomputed at each time step of the control method. The linearization procedure makes use of Taylor series expansion and of the computation of the associated Jacobian matrices. For the linearized model of the wheeled pendulum, an optimal (H-infinity) feedback controller is developed. The controller’s gain is computed through the repetitive solution of an algebraic Riccati equation at each iteration of the control algorithm. The global asymptotic stability properties of the control method are proven through Lyapunov analysis. Finally, by using the H-infinity Kalman Filter as a robust state estimator, the implementation of a state estimation-based control scheme becomes also possible.

This paper addresses the systematic approach to design formation control for kinematic model of unicycle-type nonholonomic mobile robots. These robots are difficult to stabilize and control due to their nonintegrable constraints. The difficulty of control increases when there is a requirement to control a cluster of nonholonomic mobile robots in specific formation. In this paper, the design of the control scheme is presented in a three-step process. First, a robust state-feedback point-to-point stabilization control is designed using sliding mode control. In the second step, the controller is modified so as to address the tracking problem for time-varying reference trajectories. The proposed control scheme is shown to provide the desired robustness properties in the presence of the parameter variation, in the region of interest. Finally, in third step, tracking problem of a single nonholonomic mobile robot extends to formation control for a group of mobile robots in the leader–follower scenario using integral terminal- based sliding mode control augmented with stabilizing control. Starting with the transformation of the mathematical model of robots, the proposed controller ensures that the robots maintain a constant distance between each other to avoid collision. The main problem with the proposed controller is that it requires all states specially velocities. Therefore, the state-feedback control scheme is then extended to output feedback by incorporating a highgain observer. With the help of Lyapunov analysis and appropriate simulations, it is shown that the proposed output-feedback control scheme achieves the required control objectives. Furthermore, the closed loop system trajectories reach to desired equilibrium point in finite time while maintaining the special pattern.