In this paper, the problem of sensitivity reduction by feedback is formulated as an optimization problem and separated from the problem of stabilization. Stable feedback schemes obtainable from a given plant are parameterized. Salient properties of sensitivity reducing schemes are derived, and it is shown that plant uncertainty reduces the ability of feedback to reduce sensitivity. The theory is developed for input-output systems in a general setting of Banach algebras, and then specialized to a class of multivariable, time-invariant systems characterized by n × n matrices of H? frequency response functions, either with or without zeros in the right half-plane. The approach is based on the use of a weighted seminorm on the algebra of operators to measure sensitivity, and on the concept of an approximate inverse. Approximate invertibility of the plant is shown to be a necessary and sufficient condition for sensitivity reduction. An indicator of approximate invertibility, called a measure of singularity, is introduced. The measure of singularity of a linear time-invariant plant is shown to be determined by the location of its right half-plane zeros. In the absence of plant uncertainty, the sensitivity to output disturbances can be reduced to an optimal value approaching the singularity measure. In particular, if there are no right half-plane zeros, sensitivity can be made arbitrarily small. The feedback schemes used in the optimization of sensitiviiy resemble the lead-lag networks of classical control design. Some of their properties, and methods of constructing them in special cases are presented.

Feedback and Optimal Sensitivity: Model Reference Transformations, Multiplicative Seminorms, and Approximate Inverses

Sequential Monte Carlo による強化学習メタパラメータ調整

http://www.cell.com/article/S2405844022006879/pdf

Metaheuristic algorithms for PID controller parameters tuning: review, approaches and open problems

With the manipulator performs fixed-point tasks, it becomes adversely affected by external disturbances, parameter variations, and random noise. Therefore, it is essential to improve the robust and accuracy of the controller. In this article, a self-tuning particle swarm optimization (PSO) fuzzy PID positioning controller is designed based on fuzzy PID control. The quantization and scaling factors in the fuzzy PID algorithm are optimized by PSO in order to achieve high robustness and high accuracy of the manipulator. First of all, a mathematical model of the manipulator is developed, and the manipulator positioning controller is designed. A PD control strategy with compensation for gravity is used for the positioning control system. Then, the PID controller parameters dynamically are minute-tuned by the fuzzy controller 1. Through a closed-loop control loop to adjust the magnitude of the quantization factors–proportionality factors online. Correction values are outputted by the modified fuzzy controller 2. A quantization factor–proportion factor online self-tuning strategy is achieved to find the optimal parameters for the controller. Finally, the control performance of the improved controller is verified by the simulation environment. The results show that the transient response speed, tracking accuracy, and follower characteristics of the system are significantly improved.

Self-Tuning Control of Manipulator Positioning Based on Fuzzy PID and PSO Algorithm

Inconel 718 (IN-718) has excellent mechanical and chemical properties at high temperature, which has been widely applied in aerospace, ocean, and chemical industries. Meanwhile, the super high temperature properties lead to its poor machinability and machined surface integrity. Good machinability and surface integrity of IN-718 have always been challenging topics in the field of mechanical machining. The machinability and surface integrity of IN-718 was reviewed in this paper. The influences of chemical elements, microstructure, cutting parameters, and cutting environments on machinability were discussed. Cutting force, specific energy, and tool wear were analyzed as the main factors of machinability evaluation index. The characteristics of machined surface integrity including surface morphology (such as surface defects and surface roughness), microstructure modifications (such as plastic deformation, grain size, and white layer) and mechanical properties (such as microhardness and residual stress) related to IN-718 were presented. The state-of-the-art of machining IN-718 showed that most current research focused on its poor machinability and surface integrity in the aspect of material characteristics. There is lack of research on machinability from the viewpoint of geometrical structure of the part to be machined. Therefore, it is important to further study the manufacturability (the difficulty of the process from material to part) of IN-718 components with complex geometrical surface and profiles to achieve shape control and precise design.

Recent progress of machinability and surface integrity for mechanical machining Inconel 718: a review

In this work, we are interested to the PID control of nonlinear systems and more specially the control of a robot manipulator. The idea is to determine the optimal parameters ($$K_{p}, K_{i}$$ and $$K_{d}$$) of the controller using a novel algorithm of optimization called whale optimizer algorithm (WOA). To study the effectiveness of WOA-PID controller, its performance is compared with other controllers such as particle swarm optimization-PID (PSO-PID) and grey wolf optimizer-PID (GWO-PID). The model of robot manipulator and all controllers were tested using Simulink/MATLAB. Simulation results obtained clearly indicate the superiority of WOA-PID controller over the other controllers for trajectory tracking, better settling time, and ITAE errors.

Whale optimizer algorithm to tune PID controller for the trajectory tracking control of robot manipulator

This paper aims to contribute in solving the problem of model-based body motion estimation by using data coming from visual sensors. We consider the case of state estimation in jump Markov nonlinear systems. The Interacting Multiple Model (IMM) algorithm is specially designed to track accurately targets whose state and/or measurement (assumed to be linear) models changes during motion transition. However, when these models are nonlinear, the IMM algorithm must be modified in order to guarantee an accurate track. In this paper we propose to compare the results given by an IMM algorithm Extended Kalman filter based (IMM-EKF) versus those given by an IMM algorithm Unscented Kalman filter based (IMM-UKF) in tracking target assumed to be highly maneuverable.

IMM-UKF algorithm and IMM-EKF algorithm for tracking highly maneuverable target: a comparison

In this paper, we present an efficient filtering algorithm to perform accurate estimation in jump Markov nonlinear systems, which we aim to contribute in solving the problem of model-based body motion estimation by using data coming from visual sensors. The interacting multiple model (IMM) algorithm is specially designed to track accurately targets whose state and/or measurement (assumed to be linear) models changes during motion transition. However, when these models are nonlinear, the IMM algorithm must be modified in order to guarantee an accurate track. In this paper we propose to avoid the extended Kalman filter because of its limitations and substitute it with the unscented Kalman filter which seems to be more efficient especially according to the simulation results obtained with the nonlinear IMM algorithm (NIMM).

Abdennour Sebbagh

Papers

Whale optimizer algorithm to tune PID controller for the trajectory tracking control of robot manipulator

IMM-UKF algorithm and IMM-EKF algorithm for tracking highly maneuverable target: a comparison

A nonlinear algorithm for maneuvering target visual-based tracking

Small signal model designing and robust decentralized tilt integral derivative TID controller synthesizing for twin rotor MIMO system

Small signal model designing and robust decentralized tilt integral derivative TID controller synthesizing for twin rotor MIMO system