Distributed aggregative games for Euler–Lagrange systems with system parameter uncertainties

This paper introduces output feedback distributed optimization algorithms designed specifically for second‐order nonlinear multi‐agent systems. The agents are allowed to have heterogeneous dynamics, characterized by distinct nonlinearities, as long as they satisfy the Lipschitz continuity condition. For the case with unknown states, nonlinear state observers are designed first for each agent to reconstruct agents' unknown states. It is proven that the agents' unknown states are estimated accurately by the developed state observers. Then, based on the agents' state estimates and the gradient of each agent local cost function, a kind of output feedback distributed optimization algorithms are proposed for the considered multi‐agent systems. Under the proposed distributed optimization algorithms, all the agents' outputs asymptotically approach the minimizer of the global cost function which is the sum of all the local cost functions. By using Lyapunov stability theory, convex analysis, and input‐to‐state stability theory, the asymptotical convergence of the output feedback distributed optimization closed‐loop system is proven. Simulations are conducted to validate the efficacy of the proposed algorithms.

“…Construct a Lyapunov function V = 𝜖 T i P i 𝜖 i . Taking the derivative of V along systems (8) gives…”

Section: State Observer Designmentioning

confidence: 99%

“…V is negative definite. As a result, systems (8) are asymptotically stable and thus state observation error systems (7) are asymptotically stable.…”

Section: State Observer Designmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Output feedback distributed optimization algorithms of second‐order Lipschitz nonlinear multi‐agent systems

Li,

Yuan

2023

“…Here, the first and second equations represent the kinematics and dynamics of the mobile robot system, respectively. The mobile robot dynamics has the following three properties [47,48]:…”

Section: Dynamics and Kinematics Of A Mobile Robot Systemmentioning

confidence: 99%

A system decomposition method for region tracking control of a non‐holonomic mobile robot with dynamic parameter uncertainties

Yu,

Wu,

Yang

et al. 2023

The tracking control problem of non‐holonomic mobile robot systems has been extensively investigated in the past decades, however, most of the existing control strategies were developed specifically for the fixed‐point tracking. This technical note focuses on the region tracking control for a non‐holonomic mobile robot system with parameter uncertainties in the robot dynamics. With the system decomposition and adaptive control method, some restrictions imposed on the angular and linear velocities of the non‐holonomic mobile robot in recent literature are removed, enabling to track dynamic trajectories with any values of the angular and line velocities. The proposed adaptive control scheme can simultaneously solve both the regulation and region tracking problems of a non‐holonomic mobile robot with one passive wheel and two actuated wheels. By utilizing the designed control laws, the mobile robot system is able to globally reach inside a moving region specified by potential functions whose path can be a circular curve, a straight line, or sinusoidal curve, by using a single adaptive controller. Since the dynamic region can be specified arbitrarily small, the fixed‐point tracking can be regarded as a special case of region tracking studied in this paper. Compared with the traditional fixed‐point tracking, region tracking has more flexibility and better robustness. Numerical results are presented to show the effectiveness of the designed strategy.

“…Furthermore, achieving distributed consensus for networked Euler-Lagrange (EL) systems has recently become one of the most significant research topics because it can describe a lot of collaborative multiple robotic systems, such as manipulators, wheeled mobile robots, and flexible joint robots. Over the past decade, a large variety of research works have been done on the cooperative behavior for networked EL systems [3][4][5][6], whereas most of existing studies concentrate on the distributed consensus protocols in the deterministic framework. The system parameters and communication topology changing did not consider.…”

Section: Introductionmentioning

confidence: 99%

Achieving distributed consensus for networked uncertain Euler–Lagrange systems with average dwell time approach

Liu

et al. 2023

This paper proposes a novel distributed consensus achieving algorithm for switched networked Lagrange systems with uncertain parameters, in order to solve the abruptly occurrence problem of parameters changing and communication topologies switching. We first model the multirobot systems as switched networked Lagrange systems. Then, by introducing the network topology into the sliding mode vector, a unified distributed consensus tracking strategy is then proposed by systematically combining the average dwell time (ADT) approach and adaptive control method. Besides, a sufficient condition regarding the ADT among subsystems is derived to ensure the asymptotical consensus performance of the multirobot systems. A unified analysis methodology is developed to perform the convergence analysis for the closed‐loop system by Lyapunov stable theory. Finally, illustrative examples and simulations are provided to demonstrate and validate the theoretical results.