Linear matrix inequality based synthesis of PI controllers for PMSM with uncertain parameters

This paper addresses the design of robust PI controllers for permanent magnet synchronous motors in terms of a linear matrix inequality based problem. A polytopic model of the plant is obtained and validated for the motor uncertain parameters belonging to intervals. The design procedure proposed here encompasses: i. suitable plant uncertainties inclusion and the use of practical design control constraints; ii. robust PI computation based on linear matrix inequalities with a very fast solution; iii. simulation analyses; and iv. experimental evaluations. The robust PI controller can produce superior speed regulation than a PI controller designed only for the nominal parameters, including better disturbance rejection and H-infinity performance. Experimental results confirm the viability of the proposal, which can be seen as an efficient alternative to trade off performance and robustness for PI controllers in this application233310319CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICO - CNPQCOORDENAÇÃO DE APERFEIÇOAMENTO DE PESSOAL DE NÍVEL SUPERIOR - CAPES306197/2015-4não te

Hierarchical modeling and speed control of networked induction motor systems

This paper proposes a hierarchical modeling method and a fuzzy speed control strategy for nonlinear networked induction motor systems subject to network induced time delay and packets dropout. The networked induction motor control system consists of a networked speed controller and a local controller. Fuzzy gain scheduling is applied on the networked speed controller to guarantee the robustness against complicated variations on the communication network. The state predictor is to compensate the time delay occurred in data transmission in the feedback channel. In stability analysis, the upper allowed limits of the time delay and packets dropout are calculated using the Lyapunov-Krasovskii theorem, respectively. Simulation and experimental results are given to illustrate the effectiveness of the proposed approach

Non-fragile H∞ control with randomly occurring gain variations, distributed delays and channel fadings

This study is concerned with the non-fragile H∞ control problem for a class of discrete-time systems subject to randomly occurring gain variations (ROGVs), channel fadings and infinite-distributed delays. A new stochastic phenomenon (ROGVs), which is governed by a sequence of random variables with a certain probabilistic distribution, is put forward to better reflect the reality of the randomly occurring fluctuation of controller gains implemented in networked environments. A modified stochastic Rice fading model is then exploited to account for both channel fadings and random time-delays in a unified representation. The channel coefficients are a set of mutually independent random variables which abide by any (not necessarily Gaussian) probability density function on [0, 1]. Attention is focused on the analysis and design of a non-fragile H∞ outputfeedback controller such that the closed-loop control system is stochastically stable with a prescribed H∞ performance. Through intensive stochastic analysis, sufficient conditions are established for the desired stochastic stability and H∞ disturbance attenuation, and the addressed non-fragile control problem is then recast as a convex optimisation problem solvable via the semidefinite programme method. An example is finally provided to demonstrate the effectiveness of the proposed design method

A Strategy Optimization Approach for Mission Deployment in Distributed Systems

In order to increase operational efficiency, reduce delays, and/or maximize profit, almost all the organizations have split their mission into several tasks which are deployed in distributed system. However, due to distributivity, the mission is prone to be vulnerable to kinds of cyberattacks. In this paper, we propose a mission deployment scheme to optimize mission payoff in the face of different attack strategies. Using this scheme, defenders can achieve “appropriate security” and force attackers to jointly safeguard the mission situation

Finite-Time Chaos Control of a Complex Permanent Magnet Synchronous Motor System

This paper investigates the finite-time chaos control of a permanent magnet synchronous motor system with complex variables. Based on the finite-time stability theory, two control strategies are proposed to realize stabilization of the complex permanent magnet synchronous motor system in a finite time. Two numerical simulations have been conducted to demonstrate the validity and feasibility of the theoretical analysis

Networked Control System for the Guidance of a Four-Wheel Steering Agricultural Robotic Platform

A current trend in the agricultural area is the development of mobile robots and autonomous vehicles for precision agriculture (PA). One of the major challenges in the design of these robots is the development of the electronic architecture for the control of the devices. In a joint project among research institutions and a private company in Brazil a multifunctional robotic platform for information acquisition in PA is being designed. This platform has as main characteristics four-wheel propulsion and independent steering, adjustable width, span of 1,80 m in height, diesel engine, hydraulic system, and a CAN-based networked control system (NCS). This paper presents a NCS solution for the platform guidance by the four-wheel hydraulic steering distributed control. The control strategy, centered on the robot manipulators control theory, is based on the difference between the desired and actual position and considering the angular speed of the wheels. The results demonstrate that the NCS was simple and efficient, providing suitable steering performance for the platform guidance. Even though the simplicity of the NCS solution developed, it also overcame some verified control challenges in the robot guidance system design such as the hydraulic system delay, nonlinearities in the steering actuators, and inertia in the steering system due the friction of different terrains

Control strategy based on wavelet transform and neural network for hybrid power system

Published version of an article in the journal: Journal of Applied Mathematics. Also available from the publisher at: http://dx.doi.org/10.1155/2013/375840 Open AccessThis paper deals with an energy management of a hybrid power generation system. The proposed control strategy for the energy management is based on the combination of wavelet transform and neural network arithmetic. The hybrid system in this paper consists of an emulated wind turbine generator, PV panels, DC and AC loads, lithium ion battery, and super capacitor, which are all connected on a DC bus with unified DC voltage. The control strategy is responsible for compensating the difference between the generated power from the wind and solar generators and the demanded power by the loads. Wavelet transform decomposes the power difference into smoothed component and fast fluctuated component. In consideration of battery protection, the neural network is introduced to calculate the reference power of battery. Super capacitor (SC) is controlled to regulate the DC bus voltage. The model of the hybrid system is developed in detail under Matlab/Simulink software environment

Hierarchical modeling and speed control of networked induction motor systems

This paper proposes a hierarchical modeling method and a fuzzy speed control strategy for nonlinear networked induction motor systems subject to network induced time delay and packets dropout. The networked induction motor control system consists of a networked speed controller and a local controller. Fuzzy gain scheduling is applied on the networked speed controller to guarantee the robustness against complicated variations on the communication network. The state predictor is to compensate the time delay occurred in data transmission in the feedback channel. In stability analysis, the upper allowed limits of the time delay and packets dropout are calculated using the Lyapunov-Krasovskii theorem, respectively. Simulation and experimental results are given to illustrate the effectiveness of the proposed approach

Multiobjective Optimization of PID Controller of PMSM

PID controller is used in most of the current-speed closed-loop control of permanent magnet synchronous motors (PMSM) servo system. However, Kp, Ki, and Kd of PID are difficult to tune due to the multiple objectives. In order to obtain the optimal PID parameters, we adopt a NSGA-II to optimize the PID parameters in this paper. According to the practical requirement, several objective functions are defined. NSGA-II can search the optimal parameters according to the objective functions with better robustness. This approach provides a more theoretical basis for the optimization of PID parameters than the aggregation function method. The simulation results indicate that the system is valid, and the NSGA-II can obtain the Pareto front of PID parameters

Motion Control of Four-Wheel Independently Actuated Electric Ground Vehicles considering Tire Force Saturations

A vehicle stability control approach for four-wheel independently actuated (FWIA) electric vehicles is presented. The proposed control method consists of a higher-level controller and a lower-level controller. An adaptive control-based higher-level controller is designed to yield the vehicle virtual control efforts to track the desired vehicle motions due to the possible modeling inaccuracies and parametric uncertainties. The lower-level controller considering tire force saturation is given to allocate the required control efforts to the four in-wheel motors for providing the desired tire forces. An analytic method is given to distribute the high-level control efforts, without using the numerical-optimization-based control allocation algorithms. Simulations based on a high-fidelity, CarSim, and full-vehicle model show the effectiveness of the control approach