Biped locomotion has two characteristics: 1) repeating impact at the moment when the foot contacts with the terrain, 2) limitation to the torque of the ankle. The second is required in order to make the foot of the supporting leg stay on the terrain. Since the impulsive effect can be a disturbance which makes the robot fall down, the controller of the biped robot is required to make the undesired effect of the impulsive phenomenon as small as possible. Although it is common to design the controller with a high-gain feedback in order to eliminate the disturbance, the torque of the ankle is not limited. In the paper, a control method is proposed so that the system with impact is stabilized with limited inputs. A simple biped model controlled by the proposed controller is simulated numerically and the result shows the efficiency of the method.

A novel image-based visual approach for controlling nonholonomic mobile robots to track a moving target is presented. The mobile robot is endowed with a fixed camera, and a visual feedback controller is used to control the mobile robot to track a moving target of interest. A three dimensional state space representation of the camera-target visual interaction model fully defined in the image plane is used. In the case of an unknown height moving target symbol traced by camera, the global stability is proved using an adaptive backstepping control law. Based on the Lyapunov direct method, the closed-loop stability is guaranteed. Experimental results of a mobile robot with two actuated wheels equiped with a fixed camera are provided for illustrating the tracking ability of the controller.

A mobile robot is one of the well-known nonholonomic systems. The integration of a kinematic controller and a torque controller for the dynamic model of a nonholonomic mobile robot has been presented (Fierro and Lewis, 1995). In this paper, an adaptive extension of the controller is proposed. If an adaptive tracking controller for the kinematic model with unknown parameters exists, an adaptive tracking controller for the dynamic model with unknown parameters can be designed by using an adaptive backstepping approach. A design example for a mobile robot with two actuated wheels is provided. In this design, a new kinematic adaptive controller is proposed, then a torque adaptive controller is derived by using the kinematic controller.

A new information processing architecture is extracted from the immune system. By focusing on informational features of the immune system (i.e. specificity, diversity, tolerance, and memory), an immune algorithm is proposed. The algorithm proceeds in three steps: diversity generation, establishment of self-tolerance, and memorizing non-self. The algorithm may be used typically to model the system by distributed agents where the system (the self) as well as the environment (the non-self) are unknown or cannot be modeled. Agent-based architecture based on the local memory hypothesis and network-based architecture based on the network hypothesis are discussed. Agent-based architecture is elaborated with the application to an adaptive system where the knowledge about environment is not available. Adaptive noise neutralization is formalized and simulated for a simple plant.

Two control schemes, termed extended hybrid control and extended impedance control, respectively, are proposed for compliant motion control of redundant manipulators. In the two control schemes, the basic compliant motion task is accomplished while the redundancy is utilized to realize some additional constraints that optimize any user-defined objective function. Some experimental results on a three-DOF planar redundant manipulator are presented to illustrate the two proposed schemes and demonstrate their capabilities for optimizing various objective functions.>

Two control schemes, called extended hybrid control and extended impedance control respectively, are developed for assuring the compliant motion of redundant manipulators. In the two control schemes, the basic compliant motion task is accomplished while the redundancy is utilized to realize some additional constraints which optimize any user-defined objective functions. Further, real-time implementations are given and some experimental results on a 3-DOF planar redundant manipulator are also presented to illustrate the two proposed schemes and demonstrate their capabilities for optimizing various objective functions.>

A failure diagnosis model which consists of a set of units that are faulty, a set of measurements to detect a faulty unit, and an incidence matrix representing the binary relation between these two sets is presented. A binary relation is defined by whether or not a fault of one unit is detected by a measurement. Considering this failure diagnosis model as a simplicial complex in topological geometry, the relationship between the diagnostic aspects of the model and the topological properties of the corresponding simplicial complex is studied. The diagnosability of a failure diagnosis model with multiple faults is expressed as a covering property of each simplex in a simplicial complex. The capability of distinguishing a faulty unit by a given number of measurement is determined by examining the global connective structure of the simplicial complex. This analysis of connectivity is done by performingq-analysis on a simplicial complex. It is noted hat all possible combinations of fault patterns are considered under a permissible number of faults. However, in actual systems, only restricted fault patterns are possible in which faulty units are functionally connected with each other, even in multiple fault situations.