In order to reduce the time consumption in solving the problem of large-scale nonlinear 0-1 programming, an intelligent algorithm acceleration strategy based on the improved Markov neighborhood was presented by analyzing the characteristics of nonlinear 0-1 programming and the Markov process of intelligent algorithm. First, a rewritten model of nonlinear 0-1 programming problem was given. Next, an improved Markov neighborhood was constructed based on the rewritten model, and the reachable probability between two random statuses with its conditions under the improved Markov neighborhood was derived and proven. With a further analysis of the structure of nonlinear 0-1 programming together with the improved Markov neighborhood, a recursive updating strategy of the constraint and objective function was designed to accelerate the intelligent algorithms. The experimental results illustrate that the proposed strategy improves the operating efficiency of intelligent algorithms while keeping a correspondence with the original algorithms in search results.

Joint trajectory tracking control and flexible vibration suppression techniques for a Free-Floating Flexible Space Robot (FFFSR) were discussed under parameter uncertainty and limited torque. A composite controller containing a slow control subsystem for joint trajectory tracking and a fast control subsystem for flexible vibration description were proposed using singular perturbation method. A model-free Fuzzy Radial Basis Function Neural Network (FRBFNN) adaptive tracking control strategy was applied in the slow subsystem. FRBFNN was adopted to support the estimation of velocity signals performed by the observer, the approximation of the unknown nonlinear functions of the observer as well as the controller. The fast subsystem adopted an Extended State Observer (ESO) to estimate coordinate derivatives of flexible modal and uncertain disturbance, which could hardly be measured, and used Linear Quadratic Regulator (LQR) method to suppress the flexible vibration. Numerical simulation results show that the composite controller can achieve stable joint trajectory tracking in 2.5 s, and the flexible vibration amplitude is restricted in ±1×10 ^-3 m, when the control torque is limited within ±20 N·m and ±10 N·m.

To solve the problem that the state of Agents is immeasurable and only the stationary consensus can be achieved in heterogeneous multi-Agent systems composed of first-order and second-order Agents, a novel nonlinear consensus protocol with reference velocity was proposed. Firstly, consensus analysis was transformed to stability demonstration. Then, the Lyapunov function was constructed. Finally, the sufficient conditions for achieving consensus were obtained by using Lyapunov stability theory and LaSalle's invariance principle. The simulation results show that if the conditions can be satisfied, the consensus can be achieved.

A control law based on Function Sliding Mode Controller (FSMC) was proposed for trajectory tracking control of manipulator. The uncertainties of the system were achieved from dynamic model and sliding mode function. Then RBF neural network was used to approach uncertainties of the system. Because of the approximation error of neural network, especially at the initial phase, the function sliding mode controller and robust compensator were designed for error compensation of neural network. The function sliding mode controller was capable of overcoming chattering problem of common Sliding Mode Control (SMC), and improved the tracking ability of the system. The global stability of closed loop system was proved based on Lyapunov theory, the effectiveness of proposed control approach was also demonstrated by simulation results.

Concerning the collision avoidance problem for multi-robot system, a collision avoidance algorithm based on improved artificial coordinating field was advanced. Firstly, a method was adopted, which made obstacle convex and chose new target initiatively to resolve the deadlock problem with artificial coordinating field in non-protruding polygon obstacle surroundings. Secondly, a repelling force was modeled based on velocity and distance to overcome the problem of low space utilization ratio with artificial coordinating field, especially in the situation that the target was near by the obstacle. Lastly, a force mixer was designed, and it was applied to avoidance movement tremble. The experimental results indicate that, the algorithm is effective and reliable to resolve collision avoidance problem for multi-robot system, and it improves the adaptability of multi-robot system for complicated environment.