We consider input-to-state-stability gain (ISS-gain) design for a differentially flat system disturbed by bounded noise. Firstly, we design a C^∞ differential strict control Lyapunov function (CLF) for the augmented linear system on the extended state space. The CLF satisfies predetermined L₂ norms performance by solving state feedback H_∞ control problems to attenuate persistent disturbance levels. Then, an Input-state-stability CLF (ISS-CLF) is derived from the CLF by applying a dynamic extension method and a minimum projection method. The ISS-CLF and the predetermined L₂ norms performance give the analytic ISS gain function. Finally, we specify the L₂ norms performance bounds of the disturbance attenuation controller for the differentially flat system. The effectiveness of the proposed method is confirmed by computer simulation of marine vessel control.

In this paper, we propose a method of shaping a reference signal so that a desired response of an uncertain linear system can be achieved. The signal shaping can be done by using the data-driven control schemes, thereby improving the closed-loop performance without knowing the model. Since the proposed method do not change any closed-loop controllers equipped with the target system, the method is useful for working plants. The effectiveness of the proposed method is shown through an experiment of using a Lego Mindstorm EV3.

In this paper, we consider a design method of state feedback controllers for discrete-time linear systems with stochastic parameters that vary accordingly to independent and identically distributed (i.i.d.) process. If the parameters obey the normal distribution, then we cannot strictly guarantee the “conventional deterministic control performance” due to the unlimited parameter variations. Then, we propose incorporating the “stochastic stability”, which has been confirmed to be equivalent to quadratic stability in stochastic sense, into the conventional deterministic H_∞ performance. We derive a design condition on state feedback controllers that achieve deterministic H_∞ performance and stochastic stability simultaneously via extended linear matrix inequalities (LMIs) approach. The effectiveness of the proposed method is illustrated through a numerical example.

In this paper, we propose an algorithm for state estimation and attack detection in distributed observer system and derive the condition for achieving the estimation and detection. In detail, the algorithm using the notion of virtual states can be used in each local observer for distributedly attack detection by oneself. In the perspective of attack, we define, not only measurement attack, but an observer communication attack which is the falsification of the transmitted data between local observers and also define a combination attack which combines the observer communication attack and measurement one. We derive the condition for estimation and detection under the combination attack as the theorem and, finally, verify the effectiveness of the proposed algorithm by numerical simulations.

In this paper, we propose a null-space compensation control for linear first-order systems with redundant two input channels. In the input redundant systems, control input vector generally has null-space component of the plant parameter vector. The null-space component does not contribute to the generation of the control force which drives the plant state. If a control input that does not include the null-space component can be generated, efficient control is achieved from the viewpoint of minimizing the norm of the control input. In the proposed method, an adaptive control method is used to design a control system that compensates for the null-space component, even if the plant parameter vector is unknown. The effectiveness is shown by numerical examples.

Floating offshore wind turbines have attracted attention recently. In this paper, we design a blade pitch angle controller by H^∞ preview control. This control law uses wind speed preview information. We investigate the performance of controllers with and without consideration for uncertainty on the preview information and discuss the suitable preview length in terms of H^∞/H² norm and wind turbine's control objective.

This paper describes the development and flight control of a variable pitch propeller quad tilt rotor drone with 12 degrees of freedom. As results of the thrust response test of the propeller alone and the step response test of the attitude control of the entire drone, it was shown that the proposed drone is more responsive than the fixed pitch propeller configuration.

This paper presents an approximate method to solve a bi-level optimization problem which is composed of an upper and a lower level. The upper level determines the optimal value of an unknown parameter in the lower level, in consideration of the lower level optimal solution depending on the parameter, based on the upper objective and constraint functions, while the lower level optimal solution is determined under the parameter assigned by the upper level, based on the lower objective and constraint functions. When the upper level can obtain only response data of the lower level optimal solution corresponding to the parameter assigned by the upper level, upper level performs optimization by composing an approximate model of the optimal response mapping of the lower level successively. The process is an integrated procedure by alternating optimization by meta-heuristics and active learning in which effective parameter data are generated for searching the upper level optimal solution successively. Results of computer simulation for simple problems are shown to confirm effectiveness of the presented integrated optimization method for bi-level optimization problems.