In this paper, we consider a design of the model reference control systems with adjustable parameters for linear systems with time-varying parametric uncertainties. To discuss this problem, we focus on the output error between the plant and the reference model, and adopt the reachable domain of this error as a performance index. This reachable domain is known as an output reachable set. Based on the analysis technique of output reachable sets, we propose a new design technique of the model reference controller, and demonstrate its efficacy by numerical case studies.
In this paper, we describe the self-generation of gait pattern in quadruped walking robot. The gait of robot is generated by the neural network CPG : Central Pattern Generator, and the robot learns the gait pattern by finding the optimal weights in CPG. In addition to the traditional optimization methods such as GA : Genetic Algorithm, and LSM : Likelihood Search Method, we propose the new optimization method VQSM : Vector Quantizing Search Method, which finds gradient from the finite quantized vectors to be applicable to the discontinuous search space, and which inherits intensification and diversification of search from LSM to find the global optimum in the search space. The simulation result of self-generation of gait pattern shows that VQSM has an advantage of optimization over LSM and an advantage of computational amount over GA. It is also shown that, like the gait of animals, according to walking speed, the optimal gait becomes Bound from Trot.
In this paper, we present a robust controller design method which achieves not only robust stability but also performance robustness for a linear multivariable system with norm bounded or structured additive uncertainties. The performance robustness means that the deterioration of control performance is suppressed when we compare the time response for the real system with the desirable one generated by using the nominal system directly. In this approach, we assume that the control law consists of a state feedback with the feedback gain which is designed in order to generate the desirable transient behavior for the nominal system and a compensation input for the uncertainties. The compensation input is determined so that the upper bound of a quadratic cost function for the error system between the real and the nominal system is minimized. We show that stability of the error system is reduced to the solvability of a Riccati Equation and give a guide to set up a design parameter. Finally, numerical examples are presented.
We have proposed a hierarchical new public transportation operating control system aiming at dissolution of traffic congestion and the road traffic problem of the environmental pollution. In the lowest level of this system, there is the Dial-a-Ride problem. Real-time processing needs to be smoothly performed with time restriction of a getting-on-and-off vehicle demand, or a departure interval. In this paper, a method of randomizing the departure interval with consideration to the entrainment efficiency of a vehicle is proposed. Moreover, we propose a method of evaluating fitness which is considering the entrainment efficiency of vehicle, that adopts the technique used genetic algorithm for the round path planning. As a result, we confirm the real-time control by adopting irregular departure method is more economical than that using plural departure methods, and the method of evaluating fitness for improved entrainment efficiency is useful.
We propose a computational model which includes adaptive mutation and sexual selection, and investigate functional aspects of the model by examining self-adaptation processes of mutation under the sexual selection. In mating, each female observes males' traits in a phenotypic space, then chooses a male according to her own preference. Therefore, the selection pressure for males is different from that for females. This method was applied for the maximum search problem of a 2-dimensional complicated function. The simulation result showed that the proposed method can escape local optima by the runaway effect of males' traits and females' preferences, and this process leads the system to the intermittent evolution. In this phase, an asymmetrical mutation was driven, which provided the different roles of searching strategies depending on sex. The females were conservative with low mutation rates, while the males were innovative with higher mutation rates. As a result, the proposed method was able to search larger maxima than the conventional methods.
This paper deals with a controller synthesis problem for precise speed control systems of ultrasonic motors (USMs) considering nonlinear characteristics of USMs. For this problem, we firstly propose a parameter varying plant model which represents the nonlinear characteristics by using information of amplitude of stator vibration as a model parameters. Secondly, to provide higher performance for the systems, we design a parameter varying controller in a systematic way by applying gain-scheduled H∞ control technique for the parameter varying plant model. In addition, control experiments show the validity of the proposed method.
This paper discusses a complex arrangement problem for maximizing the number of charging slabs for an aluminum reheating furnaces. It is important to decide the slabs arrangement that many number of slabs enable to charge into a furnace to improve the productivity and reduce the fuel costs. Usually, the meta-heuristic approach for instance genetic algorithm (GA) or the simulated annealing (SA) has been used to solve the combinatorial optimization problem such as a cutting stock problem or a rectangle-packing problem. This problem is similar to above problems, but it is quite different from them in considering the constraint of rolling sequence, slab transportation, and change of constraint dynamically when the slabs are extracted from a furnace according to rolling sequence. In this paper, we propose constraint logic programming (CLP) based approach. The remarkable points of this approach are the addition of redundant constraints, application of slab grouping method and so on to improve the solution time. We confirm the effectiveness of the proposed approach by numerical experiments and show that it can obtain a good solution in practical time.