A well-known problem with distance-based formation control is the existence of multiple equilibrium points not associated with the desired formation. This problem can be potentially mitigated by introducing an additional controlled variable. In this article, we generalize the distance + angle-based scheme for 2-D formations of single-integrator agents by using directed graphs and triangulation of the n-agent formation. We show that under certain conditions on the control gains and desired formation shape, our controller ensures the asymptotic stability of the correct formation for almost all initial agent positions.

In this paper, finite time rigidity-based formation maneuvering control of single integrator multiagent systems is considered. The target formation graph is assumed to be minimally and infinitesimally rigid, and the desired group velocity is considered to be available only to a subset of the agents. A distributed nonsmooth velocity estimator is used for each agent to estimate the desired group velocity in finite time. Using Lyapunov and input to state stability notions, a finite time distance-based formation maneuvering controller is presented and it is proved that by using the controller, agents converge to the target formation and track the desired group velocity in finite time. Furthermore, it is demonstrated that the designed controller is implementable in local coordinate frames of the agents. Simulation results are provided to show the effectiveness of the proposed control scheme.

This paper provides a solution to the nonplanar multiagent formation control problem using graph rigidity. We consider a 3-D multiagent formation control where multiple agents are operating in one plane and some other agents are operating outside of that plane. This can be referred to as a layered formation control where the objective is for all agents to cooperatively acquire a predefined formation shape using a decentralized control law. The proposed control strategy is based on regulating the interagent distances. A rigorous stability analysis is presented that guarantees convergence of these distances to desired values. Simulation results are presented to support the theoretical results.

This work provides a solution to a non-planar multi-agent layered sensing and formation control problem using coning graphs. In particular, the problem addressed consists of one agent coordinating the actions of other interacting agents which are operating in a different plane. The objective is for the agents to cooperatively acquire a pre-defined formation shape using a decentralized control law. The proposed control strategy is based on inter-agent distances for single-integrator agent model and consists of formation acquisition term for non-planar agents. The simulation results that support the proposed approach are presented.

In this paper, we consider the problem of task-space tracking control of robot manipulators. Based on a quaternion representation of the end-effector orientation, we design a class of task-space controllers that ensure asymptotic end-effector position and orientation tracking. To facilitate the control design, we first develop model-based and adaptive full-state feedback controllers. We then present a model-based output feedback controller that eliminates link velocity measurements via a model-based observer. The application of the proposed control strategy to redundant robots is also discussed. Simulation results based on a six-link manipulator system are presented for the output feedback controller.

In this paper, we develop an adaptive torque control input for wheeled mobile robots (WMRs) that can be utilized in a modular manner with parameter estimate update laws to enable unified tracking and regulation, that is, a prediction error based update law ensures the parameter estimate vector is bounded, all of the signals are proven to be bounded. An additional stability analysis is provided to prove that if the adaptive update law is designed such that the prediction error is square-integrable and the estimated inertia matrix is positive-definite, the WMR tracking and regulation errors are globally asymptotically forced to a control term that can be made arbitrarily small.

The original paper of Su and Stepanenko (ibid., vol.14, p.651-5, 1998) presents the design of an adaptive/robust controller for uncertain electrically-driven robots with no velocity measurements. This note shows that the claim that velocity measurements are not required for control implementation is incorrect.

It is argued that, in the original paper by Yang, Lian and Fu (ibid., vol.13, p.140-8, 1997), there is an error which leads to inconsistent results concerning the stability of certain systems.

We consider the problem of designing a boundary controller for a flexible link robot arm with a payload mass at the link's free-end. Specifically, we utilize a nonlinear, hybrid dynamic system model (the model is hybrid in the sense that it comprises a distributed parameter, dynamic field equation coupled to discrete, dynamic boundary equations) to design a model-based control law which asymptotically stabilizes the link displacement while driving the actuator hub's position to a desired setpoint. We then illustrate how the control law can be redesigned as an adaptive controller which achieves the same control objective while compensating for parametric uncertainty including unknown payload mass. The control strategy is composed of a boundary control torque applied to the actuator hub and a boundary control force at the link's free-end. Experimental results are presented to illustrate the performance of the proposed control laws.

We present a global, output feedback, tracking controller for rigid-link, flexible-joint robots. Specifically, we design an exact model knowledge, Lyapunov-based controller which provides global asymptotic link position tracking despite the fact that only link position measurements are available.

This paper considers the problem of controlling the position and force of a constrained rigid-link electrically-driven robot manipulator actuated by brushed DC motors (BDC-RLED robot). Based on inexact knowledge of almost all of the system parameters and the lack of link velocity measurements, the integrator backstepping approach is used to design a voltage-level, adaptive position/force controller which ensures semi-global asymptotic tracking for the end-effector position, velocity, and force.

This paper presents an adaptive partial state feedback controller for rigid-link flexible-joint (RLFJ) robots. The controller compensates for parametric uncertainty throughout the entire mechanical system while only requiring measurement of link position and actuator position. To eliminate the need for measuring link velocity and actuator velocity a set of filters is utilized as a surrogate for the unmeasurable quantities. Based on this set of filters, an adaptive integrator backstepping procedure is used to develop a torque input controller which guarantees semiglobal asymptotic link position tracking while also ensuring that all signals remain bounded during closed-loop operation. Simulation results for a two-link RLFJ robot are utilized to validate the performance of the proposed controller.

In this paper, we design an adaptive position/force controller for robot manipulators during constrained motion. The proposed controller can compensate for parametric uncertainty while only requiring measurements of link position and end-effector force. A filtering technique is utilized to produce a pseudo-velocity error signal and thus, eliminate the need for link velocity measurements. The control strategy provides semiglobal asymptotic tracking performance for the end-effector position and the interaction force between the constraint and the end-effector. An experimental implementation of the proposed controller on a two-link planar robot is also presented.

In this paper, we consider the problem of designing a position/force controller for robot manipulators during constrained motion. The proposed controllers are based on exact knowledge of the system dynamics and do not require measurements of link velocity and end-effector force. The elimination of velocity measurements is accomplished by two different methods: 1) a model-based velocity observer, and 2) a high-pass filtering technique. Both of the controllers also include an open-loop force control strategy to achieve semi-global exponential end-effector position/velocity/force tracking.

In this paper, we present an adaptive partial state feedback position/force controller for rigid-link robot manipulators under constrained motion. The proposed controller can compensate for parametric uncertainty while only requiring measurements of link position and end-effector force. The control strategy provides semi-global asymptotic tracking performance for the position of the end-effector and the interaction force between the constraint and the end-effector.