A Novel Adaptive Spiral Dynamic Algorithm for Global Optimization

This paper presents a novel adaptive spiral dynamic algorithm for global optimization. Through a spiral model, spiral dynamic algorithm has a balanced exploration and exploitation strategy. Defining suitable value for the radius and displacement in its spiral model may lead the algorithm to converge with high speed. The dynamic step size produced by the model also allows the algorithm to avoid oscillation around the optimum point. However, for high dimension problems, the algorithm may easily get trapped into local optima. This is due to the incorporation of a constant radius and displacement in the model. In order to solve the problem, a novel adaptive formulation is proposed in this paper by varying the radius and displacement of the spiral model. The proposed algorithm is validated with various dimensions of unimodal and multimodal benchmark functions. Furthermore, it is applied to parameter optimization of an autoregressive with exogenous terms dynamic model of a flexible manipulator system. Comparison with the original spiral dynamic algorithm shows that the proposed algorithm has better accuracy. Moreover, the time domain and frequency domain responses of the flexible manipulator model shows that the proposed algorithm outperforms its predecessor algorithm

Design and real-time control of a new structure two-wheeled robot

The work presented in this thesis deals with the design and real-time implementation of a control system for a new configuration of two-wheeled robot. In real life applications, two wheeled robots are considered to carry payloads of different sizes at different positions anddifferent motion speeds along the vertical axis. Such parameters will have an impact on the robot stability and the control mechanism, hence their detailed study is essential for robust performance of the system. This workinvestigates the impact of the dynamic change of the payload position on the system damping characteristics whilstthe robot is in its balancing state.A mathematical model isdeveloped to describe and study the dynamics of the two-wheeled robot system.Accurate tilt angle measurement is achieved through applying a sensor fusion realized by complementary filter. A PID control strategy is considered to balance and position the robot assuming a fixed location of the payload. Then the controller isextended to provide the robot with the ability of self-standing fromits rest position withouthuman interaction.The developed controller and the sensor fusion filter are implemented on a microcontroller development board. The results show that the implementation of the controller fulfils the requirement to balance the robot.The two-wheeled robot test rig was modified to accommodate the payload actuation unit and improve the overall performance. Consequentially, the controller of the robot is also modified with the sensor fusion algorithm enhanced by implementing Kalman filter. The controller comprise a PID feedback with a feedforward approach. Furthermore, gain scheduling approach is utilized to ensure smooth and fast braking of the two-wheeled robotThe control approachis extended to an intelligent controller, where a PD-like fuzzy controller is design. A binary coding technique is developed forreal-time implementation of the fuzzy controller. Such coding and implementation eliminates the need to store a biglookup table for the controllerrules. The controlleris tested in laboratory experimentsanditsrobustness is demonstrated with application of various disturbance forces on the system.In order to evaluate the performance of the new configuration two-wheeled robot, various experiments are conducted under different conditions. The resultsdemonstrate that the proposed two-wheeled robot configuration and the proposed control approaches form a solid foundation and aframework for assisted mobility of disabled and elderly peopl

A Novel Adaptive Spiral Dynamic Algorithm for Global Optimization

This paper presents a novel adaptive spiral dynamic algorithm for global optimization. Through a spiral model, spiral dynamic algorithm has a balanced exploration and exploitation strategy. Defining suitable value for the radius and displacement in its spiral model may lead the algorithm to converge with high speed. The dynamic step size produced by the model also allows the algorithm to avoid oscillation around the optimum point. However, for high dimension problems, the algorithm may easily get trapped into local optima. This is due to the incorporation of a constant radius and displacement in the model. In order to solve the problem, a novel adaptive formulation is proposed in this paper by varying the radius and displacement of the spiral model. The proposed algorithm is validated with various dimensions of unimodal and multimodal benchmark functions. Furthermore, it is applied to parameter optimization of an autoregressive with exogenous terms dynamic model of a flexible manipulator system. Comparison with the original spiral dynamic algorithm shows that the proposed algorithm has better accuracy. Moreover, the time domain and frequency domain responses of the flexible manipulator model shows that the proposed algorithm outperforms its predecessor algorithm