Jaime González-Sierra

Bio: Jaime González-Sierra is an academic researcher from CINVESTAV. The author has contributed to research in topics: Mobile robot & Robot. The author has an hindex of 5, co-authored 19 publications receiving 97 citations.

Robust tracking output-control for a quad-rotor: A continuous sliding-mode approach

Abstract: This paper deals with the problem of robust tracking output-control design for a Quad-Rotor. The proposed approach is based on continuous sliding-modes control (SMC) techniques and it is able to robustly track a desired trajectory for the Quad-Rotor despite some class of disturbances acting on the system. Such a robust tracking control is composed of a finite-time sliding-mode observer (SMO) and cascaded continuous SMCs providing uniform finite-time stability and uniform exponential stability, for the vertical and yaw tracking error, and for the horizontal tracking error, respectively; despite the disturbances on the system, and only using the measurable positions and angles. Simulation results illustrate the feasibility of the proposed tracking strategy.

Finite-Time Formation Control without Collisions for Multiagent Systems with Communication Graphs Composed of Cyclic Paths

Abstract: This paper addresses the formation control problem without collisions for multiagent systems. A general solution is proposed for the case of any number of agents moving on a plane subject to communication graph composed of cyclic paths. The control law is designed attending separately the convergence to the desired formation and the noncollision problems. First, a normalized version of the directed cyclic pursuit algorithm is proposed. After this, the algorithm is generalized to a more general class of topologies, including all the balanced formation graphs. Once the finite-time convergence problem is solved we focus on the noncollision complementary requirement adding a repulsive vector field to the previous control law. The repulsive vector fields display an unstable focus structure suitably scaled and centered at the position of the rest of agents in a certain radius. The proposed control law ensures that the agents reach the desired geometric pattern in finite time and that they stay at a distance greater than or equal to some prescribed lower bound for all times. Moreover, the closed-loop system does not exhibit undesired equilibria. Numerical simulations and real-time experiments illustrate the good performance of the proposed solution.

Quad-Rotor robust time-varying formation control: a Continuous Sliding-Mode Control approach

Abstract: This paper deals with the robust tracking problem for a group of Quad-Rotors forming a time-varying geometric pattern, i.e. formation control, in the presence of external disturbances. Such a robus...

Emulation of n-trailer Systems through Differentially Driven Multi-Agent Systems: Continuous- and Discrete- Time Approaches

Abstract: This paper proposes the emulation of a physical standard or generalized n?trailer through the decentralized control of a multi-agent system composed of several differentially driven mobile robots. The key point is to solve a time-varying version of the well known formation tracking or marching problem. The problem is solved both in discrete- and continuous-time cases. Four different control laws are proposed which require different variables to be available for feedback or feedforward, depending on the specifications of the experimental platform. The performance of the proposed control laws is illustrated through real-time experiments. It is shown that the discrete-time control law exhibits a performance comparable to that of the continuous-time control law with a sampling period 20 times larger than the one used in the continuous-time experiment.

Adaptive sliding mode control for finite-time stability of quad-rotor UAVs with parametric uncertainties.

Abstract: Adaptive control methods are developed for stability and tracking control of flight systems in the presence of parametric uncertainties. This paper offers a design technique of adaptive sliding mode control (ASMC) for finite-time stabilization of unmanned aerial vehicle (UAV) systems with parametric uncertainties. Applying the Lyapunov stability concept and finite-time convergence idea, the recommended control method guarantees that the states of the quad-rotor UAV are converged to the origin with a finite-time convergence rate. Furthermore, an adaptive-tuning scheme is advised to guesstimate the unknown parameters of the quad-rotor UAV at any moment. Finally, simulation results are presented to exhibit the helpfulness of the offered technique compared to the previous methods.

Continuous Sliding-Mode Control Strategies for Quadrotor Robust Tracking: Real-Time Application

Abstract: The design of robust tracking control for quadrotors is an important and challenging problem nowadays. In this paper, a robust tracking output-control strategy is proposed for a quadrotor under the influence of external disturbances and uncertainties. Such a strategy is composed of a finite-time sliding-mode observer, which estimates the full state from the measurable output and identifies some types of disturbances. It is also composed of a combination of PID controllers and continuous sliding-modes controllers that robustly track a desired time-varying trajectory with exponential convergence despite the influence of external disturbances and uncertainties. The closed-loop stability is provided based on the input-to-state stability (ISS) and finite-time ISS properties. Finally, experimental results in real time show the performance of the proposed control strategy.

Fixed-Time Leader-Following Consensus for Multiple Wheeled Mobile Robots

Abstract: This article deals with the problem of leader-following consensus for multiple wheeled mobile robots. Under a directed graph, a distributed observer is proposed for each follower to estimate the leader state in a fixed time. Based on the observer and a constructed nonlinear manifold, a novel protocol is designed such that the estimated leader state is tracked in a fixed time. Moreover, a switching protocol together with a linear manifold is proposed to ensure that fixed-time leader-following consensus is realized for any initial conditions without causing singularity issues. In contrast to alternative fixed-time consensus protocols in some existing results, the protocol proposed in this article is designed by constructing the nonlinear or linear manifold, which builds a new framework for fixed-time leader-following consensus. Furthermore, the obtained upper bound of settling time is explicitly linked with a single parameter in the protocol, which facilitates the adjustment of the bound under different performance requirements. Finally, the proposed protocol is applied to formation control of wheeled mobile robots.

Quadcopter Robust Adaptive Second Order Sliding Mode Control Based on PID Sliding Surface

Abstract: We present a robust adaptive second-order sliding mode controller that rejects external disturbances and uncertainties to improve the tracking performance of attitude and altitude in a quadcopter based on a Proportional–Integral–Derivative sliding surface. The algorithm provides a rapid adaptation and strict robustness of the flight control for the vehicle under the effect of perturbations. The proposed controller design is based on the theory of second order sliding mode technique that eliminates the chattering phenomenon present in first-order sliding mode controllers. In addition, we derive an adaptive law from the Lyapunov stability to ensure the robust control for the quadcopter even without knowing the upper bound for disturbances. Applying the same external disturbances, we use a numerical simulation to compare our algorithm to recent alternatives, such as normal adaptive sliding mode control, super-twisting sliding mode control, modified super-twisting sliding mode control, and nonsingular terminal sliding mode control. The results demonstrate the effectiveness of our proposed algorithm.

Adaptive-Neural-Network-Based Trajectory Tracking Control for a Nonholonomic Wheeled Mobile Robot With Velocity Constraints

Abstract: In this article, an adaptive neural network control scheme is presented for an uncertain wheeled mobile robot (WMR) with velocity constraints and nonholonomic constraints. In practice, dynamic parameters of the system, which may change in some conditions, are hard to obtain precisely, and the velocity of the WMR should be constrained for safety. To deal with the uncertainty of the robot, adaptive neural networks are used to approximate unknown robotic dynamics, and the barrier Lyapunov function is used to guarantee the constraint on velocity. The tracking error of the closed-loop system is proven to converge to a small neighborhood of zero. Both simulation studies and practical experiments are provided to illustrate the effectiveness of the proposed control scheme.