This study explores an evolutionary analysis on a negotiation model based on Masbiole (Multiagent Systems with Symbiotic Learning and Evolution) which has been proposed as a new methodology of Multiagent Systems (MAS) based on symbiosis in the ecosystem. In Masbiole, agents evolve in consideration of not only their own benefits and losses, but also the benefits and losses of opponent agents. To aid effective application of Masbiole, we develop a competitive negotiation model where rigorous and advanced intelligent decision-making mechanisms are required for agents to achieve solutions. A Negotiation Protocol is devised aiming at developing a set of rules for agents' behavior during evolution. Simulations use a newly developed evolutionary computing technique, called Genetic Network Programming (GNP) which has the directed graph-type gene structure that can develop and design the required intelligent mechanisms for agents. In a typical scenario, competitive negotiation solutions are reached by concessions that are usually predetermined in the conventional MAS. In this model, however, not only concession is determined automatically by symbiotic evolution (making the system intelligent, automated, and efficient) but the solution also achieves Pareto optimal automatically.
This paper demonstrates a satisfaction-based method for solving multi-objective programming problems in a multi-level decision structure through the renewed use of a weighted additive fuzzy goal programming (weighted additive-FGP) approach. The weighted additive-FGP enables us to indicate decision maker's preferences toward the unit's goals and decision vectors that are controlled by the decision maker in the pth-level. This paper presents the algorithm reflecting the influence of a higher-level decision on the decision of a lower level, with the respective decision maker having the authority to place emphasis on certain decision variables. A numerical example clearly illustrates the proposed solution procedure.
This paper presents a leg torque estimation system for a passive motion that uses an incompletely restrained parallel wire driven mechanism. After comparing completely and incompletely restrained parallel wire driven systems, we organize the characteristics of both systems for human torque estimation. Defining the work spaces of four kinds for the incompletely restrained mechanism, we analyze the realization of passive tracking for a leg. Then we demonstrate that the walking motion can be achieved using low-power actuators. A case example of design is introduced to manufacture a prototype for the leg torque estimation. Finally, the result of the leg torque estimation is presented through experiments conducted using a prototype system.
This paper proposes a bias-compensated least squares (BCLS) method in closed loop environment where the noise is assumed to be stationary. The feedback controller is assumed to be linear, time-invariant, and discrete-time, and the feedback system is assumed to be asymptotically stable. The convergence of the proposed algorithm is analyzed and it is shown that a kind of persistent excitation (PE) condition on the reference input is necessary.
In this paper, we propose an adaptive generalized state tracking control on the descriptor form which is more general and natural than the state space form. The generalized state tracking problem covers not only state tracking but also output tracking problems. The proposed method guarantees asymptotic stability of the tracking error even if unknown parameters which may cause instability of controlled systems exist. The proposed adaptive adjusting laws are designed by solving a generalized Lyapunov equation. Some conditions assumed in the proposed method can be checked directly from the descriptor form.
This paper describes the suppression of the influence of scintillation encountered in working with rangefinders. In an under-sampling method for pulsed laser rangefinders, we can change the order of sampling time of the reference signal. Simulation studies show that we can extend the spectra of scintillation onto the higher frequency range. It is done by the sampling of phase shift in non-consecutive orders, and by a rearrangement of under-sampled data when a distance is to be calculated. Through this process, the increase in the drift of the measurement data is suppressed.
This paper provides a practical and meaningful application of controller parameter tuning. Here, we propose a simultaneous attainment of a desired controller and a mathematical model of a plant by utilizing the fictitious reference iterative tuning (FRIT), which is a useful method of controller parameter tuning with only one-shot experimental data, in the internal model control (IMC) architecture. Particularly, this paper focuses on systems with unstable zeros which cannot be eliminated in many applications. We explain how the utilization of the FRIT is effective for obtaining not only the desired control parameter values but also an appropriate mathematical model of the plant. In order to show the effectiveness and the validity of the proposed method, we give illustrative examples.
This paper proposes a new energy saving method of mechanical systems. In the proposed method, the potential energy stored in mechanical springs is effectively utilized to make periodic motions. In other words, the proposed system is based on resonance. Particularly, we propose an inertia adaptive control method in which a mass is moved in order to change the moment of inertia and change the desired motion cycle. Convergence to desired periodic motions is mathematically proven and performance of the proposed method is demonstrated by several simulation results.
This paper presents a method of operator-based nonlinear vibration control for a flexible arm using a Shape Memory Alloy (SMA) actuator with hysteresis. SMA actuators have hysteretic characteristic and so it is difficult to design a controller which satisfies desired performance. In order to eliminate the effect of the hysteresis, a nonlinear compensator is designed by using a hysteresis model, which is described by an operator-based Prandtl-Ishlinskii (PI) hysteresis model. Based on the concept of the Lipschitz operator and the robust right coprime factorization condition, nonlinear vibration controllers are designed, and robust stability of the closed-loop system with unconsidered vibration modes of the flexible arm as perturbation is guaranteed. Moreover, a tracking operator is designed to ensure the output tracking performance. Finally, numerical simulation and experimental results are presented to show the effectiveness of the proposed design method.