This paper presents design of a robust controller with disturbance compensation for an indoor blimp robot and its realization. The movement of blimp in horizontal plane is modeled as a slider-like nonlinear system complemented with uncertain bounded disturbances. To design the output feedback controller, a homogeneous differentiator is used as an observer. Then the method for disturbance evaluation is designed, the perturbation estimate is next used in the controller for cancellation of the influence of exogenous disturbances. Control scheme is implemented on a concrete blimp, finally, the performance of blimp disturbance compensation based controller is verified in experiments.

Modular Robot Manipulators are user-configurable manipulators which provide rapid design and inexpensive implementation. To be easy-use, smart actuators embedded with position input and position feedback controller are adopted, these local controllers render the manipulators position controlled, but also result in limited performance and precision. This paper targets the case that the built-in controller does not provide desirable precision for set-point regulation. Firstly a joint-level model is established, of which the nominal model can be identified with derivative observer based on the position feedback, then an auxiliary adaptive controller coping with parametric uncertainty is proposed which leads to an error close to zero, a switching control strategy is introduced considering the actuator saturation. The proposed control method is implemented on a 5-DOF modular manipulator, with comparison to classic integral controller.

This paper proposes a motion planning approach for non-holonomic mobile robots. Firstly, motion planning using i-PID controller is presented. Then we improve the old potential field function to produce smooth repulsive force. Finally a new repulsive function of robot orientation and angular velocity is proposed to improve the performance of obstacle avoidance. The effectiveness and the robustness of the proposed method are shown thereafter via several simulations.

An intelligent PID controller (i-PID controller) is applied to control the nonholonomic mobile robot with measurement disturbance. Because of the particularity of the nonholonomic systems, this paper propose to use a switching parameter α in the i-PID controller. We show in simulations that the proposed method is able to control the nonholonomic mobile robots with measurement disturbance, and it can also stabilize the robot at a static point.

A single landmark based localization algorithm for unicycle mobile robots was provided in [1]. It is based on the algebraic localizability notion and an efficient differentiation algorithm in noisy environment ([2], [3]). Let us stress that this localization algorithm do not need to know the linear and the angular velocities which are reconstructed by this algorithm using the kinematic model. In this paper, a sensibility study leads to a new fusion algorithm in the multi landmark case using as a basis our posture differentiation based estimator. Some simulations and experimental results are presented in order to prove the effectiveness of the proposed method compared to the well known EKF method.

This paper proposes a single landmark based localization algorithm for non-holonomic mobile robots. In the case of a unicycle robot model, the localization problem is equivalent to the system observability. Based on this observation, the proposed localization method consists in finding a vector function which depends on the measurement vector and its derivatives. In order to compute estimates of the successive derivatives of the measurement vector, we will use a numerical differentiation method. When the robot is able to only measure the relative angle between itself and the landmark in 2D case, the algorithm estimates the posture of the robot, under the hypothesis that control inputs are known. But, sometimes it is also useful to be able to estimate the control input (for example when the robot slips). This is possible with the proposed algorithm by using a landmark in dimension three. The simulation results will be given in order to show the effectiveness of the proposed algorithm. Moreover, these results are compared with those obtained by an Extended Kalman Filter in order to underline the advantages of the new algorithm.

This paper presents an architecture for the navigation of an autonomous mobile robot evolving in an uncertain environment with obstacles. The proposed strategy consists in separating the path planning from the control algorithm. The path planning is done by computing the time optimal collision-free trajectory which takes into account the limitations on the linear and angular speeds of the vehicle. The position and shape of obstacles are computed by a vision algorithm using a single camera. A saturated controller based on integral sliding mode is designed to solve the tracking problem in the presence of input saturations and of the unknown disturbances. The effectiveness, perfect performance of obstacle avoidance, real-time and high robustness properties are demonstrated by experimental results.

This paper presents a closed form solution for the dynamic model of a parallel robot. This robot is utilized like a haptic interface for a surgical simulator used in the amnicentesis operation. The dynamic model is obtained by using the Lagrange formulation applied to parallel robot. It is proved that for a large class of parallel robots which has some properties, it is possible to avoid the explicit calculation of Lagrange multipliers. The aim is to simplify the calculation for a real-time application.

Some remarks and ideas for stabilizing Takagi-Sugeno fuzzy models are presented. The main contribution proposes to transform a nonlinear model into a regular form in order to reduce the stability conditions arising when using a classical parallel distributed compensation control law. This can be applied to state feedback control laws. Finally, two examples prove the efficiency of the proposed method.

Deals with discrete Takagi Sugeno fuzzy models. These models allow the representation of numerous nonlinear models, and powerful tools are available to derive control laws. Those ones are mainly based on a typical Lyapunov approach using well-known quadratic functions. The main difference in the proposed approach is the use of non-quadratic Lyapunov functions. It allows the definition of new stability conditions which are less conservative than in the quadratic case. Examples illustrate the efficiency of the proposed approaches.

This paper outlines a methodology to study the stability of Takagi-Sugeno's fuzzy models using a systems of linear matrix inequalities (LMIs). The Takagi-Sugeno's model is first introduced. A stability analysis is then performed using a quadratic Lyapunov candidate function. This paper proposes a relaxation of Tanaka's stability condition: the LMIs to be solved are not Lyapunov equations for each rule matrix, but convex combinations of them. The coefficients of these sums depend on the membership functions. A generalization to the case of stabilization via parallel distributed compensation regulators is also proposed, with an application to a model of inverted pendulum.