A Modified Direct Allocation Algorithm with Application to Redundant Actuators

Control allocation considers the problem of controlling instruction distribution for control systems with multiple and redundant actuators. This paper focuses on the direct allocation method, making the time requirement of the algorithm analogous compared with modified pseudoinverse redistribution methods, linear programming methods solved by simplex method, and sub-gradient optimization method. To reduce off-line computations of constructing the attainable moment set of actuators, a new approach based on the null space of the control effectiveness matrix is proposed, which is superior when the number of actuators is less than 10 compared with traditional method. To decrease on-line computations, an improvement method of searching the facet that is aligned with the desired moment is presented, shortening the search time by checking only the facets that lie around the desired moment. To find such facets, the vertices of the attainable moment set are normalized and saved during off-line computations. Simulation results show that at least 32.22% of off-line computation time would be saved using null space-based construction when the number of actuators is less than 10. In on-line computations, the modified method performs superiorly compared with the three aforementioned methods. Furthermore, it may solve the problem of control allocation efficiently when a remarkable large number of redundant actuators are configured.

Novel ARC-Fuzzy Coordinated Automatic Tracking Control of Four-Wheeled Mobile Robot

Four-wheeled,individual-driven,nonholonomic structured mobile robots are widely used in industries for automated work,inspection and explora-tion purposes.The trajectory tracking control of the four-wheel individual-driven mobile robot is one of the most blooming research topics due to its nonholonomic structure.The wheel velocities are separately adjusted to follow the trajectory in the old-fashioned kinematic control of skid-steered mobile robots.However,there is no consideration for robot dynamics when using a kinematic controller that solely addresses the robot chassis’s motion.As a result,the mobile robot has lim-ited performance,such as chattering during curved movement.In this research work,a three-tiered adaptive robust control with fuzzy parameter estimation,including dynamic modeling,direct torque control and wheel slip control is pro-posed.Fuzzy logic-based parameter estimation is a valuable tool for adjusting adaptive robust controller(ARC)parameters and tracking the trajectories with less tracking error as well as high tracking accuracy.This research considers the O type and 8 type trajectories for performance analysis of the proposed novel control technique.Our suggested approach outperforms the existing control methods such as Fuzzy,proportional–integral–derivative(PID)and adaptive robust controller with discrete projection(ARC–DP).The experimental results show that the scheduled performance index decreases by 2.77%and 4.76%.All the experimen-tal simulations obviously proved that the proposed ARC-Fuzzy performed well in smooth groud surfaces compared to other approaches.