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This work presents the results acquired during simulation studies done for a 3D free-floating satellite behaviour with input-output decoupling approach. The research object is a free-floating satellite with a 3 DoF rigid 3D manipulator where a noise disturbance was introduced. Different approaches are used to compensate the noise influence. Systems using a visual aid to determine the position of manipulator joints are not ideal and introduce some uncertainties. What is more, determining the position from joints encoders is not error-free while computing angular velocity from numerical differentiation introduces even greater disturbance to the system. A couple of scenarios were investigated where state of the manipulator, including its position and velocity, was disturbed with homogeneous noise. Also the control inputs of the manipulator were disturbed. Simulation results show that the biggest impact on the control quality has a scenario where the satellite’s state has been disturbed with additive noise.

This paper considers a problem of tracking control design for different types of nonholonomic mobile manipulators. The mobile platform is in form of a unicycle. In the first step, an input–output decoupling controller is developed. The proposed selection of output functions is in more general form than the output functions previously introduced by others [Yamamoto and Yun]. It makes possible to move simultaneously, the mobile platform and the manipulator built on it. Regularity conditions that guarantee the existence of the input–output decoupling control law are presented. In the second step, trajectory and path tracking controllers are formulated and presented. Theoretical considerations are illustrated with simulations for the mobile manipulator consisting of a vertical, three degree of freeedom (DOF) pendulum (with holonomic or nonholonomic drives) mounted atop of a unicycle.

This paper introduces a velocity control strategy for Surface-Mounted Permanent Magnet Synchronous Motors SM-PMSM using exact linearization and input-output decoupling techniques, which are rooted in the principles of differential geometry. The primary aim of this control approach is to establish a static state feedback mechanism and to convert the nonlinear PMSM model into a linear, decoupled, and controllable system. Initially, the state model that represents the PMSM dynamics within the d-q reference frame is defined. Subsequently, the process of designing the control through linearization and input-output decoupling is outlined. Lastly, the synthesis of the compensator is grounded in the pole placement method, aiming to drive the direct current towards zero and ensure optimal torque operation. Simulation outcomes conducted on Matlab/Simulink demonstrate the efficacy of the speed control strategy, which is facilitated by a straightforward algorithm for practical implementation. However, it is inadequate against variations in machine parameters and load torque disturbances.

This study achieves compensation of a physical twin rotor multiple-input and multiple-output system in two steps: (i) input–output decoupling its transfer function model, obtained by linearising its non-linear model around an operating point, using an open-loop, minimal precompensator and (ii) effecting 2-degree of freedom single-input and single-output (SISO) compensations for the resulting SISO-decoupled units. While step (i) ensures decoupling in the responses, the other performances (such as robustness, tracking, disturbance rejection, etc.) can be achieved using SISO compensations in step (ii) above. The performances of the compensated system in respect of decoupling, loop robustness and disturbance rejection are verified through simulations and experiments. The results are also compared with the existing ones.

The paper addresses the input–output decoupling problem for discrete-time nonlinear systems. The algebraic method based on difference algebra and differential forms is used to solve the problem by measurement feedback, i.e., by feedback depending only on some measured functions of state variables. Constructive necessary and sufficient solvability conditions are given separately for cases when the system is described by the state equations or by the input–output equations. By specifying the measured functions, one recovers the known conditions for the state feedback or obtains the conditions for the output feedback solution.

This paper presents a nonlinear control strategy utilizing the linearization and input-output decoupling approach for a nonlinear dynamic model of proton exchange membrane fuel cells (PEMFCs). The multiple-input single-output (MISO) nonlinear model of the PEMFC is derived first. The dynamic model is then transformed into a multiple-input multiple-output (MIMO) square system by adding additional states and outputs so that the linearization and input-output decoupling approach can be directly applied. A PI tracking control is also introduced to the state feedback control law in order to reduce the steady-state errors due to parameter uncertainty. This paper also proposes an adaptive genetic algorithm (AGA) for the multi-objective optimization design of the tracking controller. The comprehensive results of simulation demonstrate that the PEMFC with nonlinear control has better transient and steady-state performance compared to conventional linear techniques.

This paper studies the problems of modeling and input-output decoupling of generic hypersonic vehicles. Dynamical equations of hypersonic vehicles are derived using Lagrangian approach, which capture the dominating characteristics and primary interactions. Then, based on the simplified model, the original decoupling problem is reformulated as an asymptotical stability problem of the corresponding error system. The popular dynamic inversion is employed to design the decoupling controller, which can achieve steady-state decoupling. However, external disturbance will greatly destroy the effect of decoupling before the system reaches steady state. To this end, based on the error system, robust H ∞ theorem can be easily used to address this issue by reducing the impact of disturbance on error system outputs, which ultimately results in approximate decoupling. Moreover, the degree of approximate decoupling can be enhanced by choosing a small performance index γ . Simulations verify the effectiveness of proposed controllers.

This paper studies the input-output decoupling control for the nonlinear vehicle model consisting of three degrees of freedom. The technique of quasi-linearization is used to simplify the vehicle model, which preserves inherent coupling effects between longitudinal acceleration/braking force, steering angles and the vehicle states. By choosing the combined control inputs, the input-output map of the vehicle dynamical system is reconstructed. Based on the model, the input-output decoupling controller is proposed. Furthermore, an asymptotically stable observer is presented. A modified form of mean value theorem is used to design the observer for the nonlinear vehicle system with bounded Jacobian. The observer gain can be obtained by solving linear matrix inequalities (LMIs). Several simulations are carried out to show the improvements in vehicle handling and stability due to the inputoutput decoupling control.

Abstract The method introduced here is applicable for multi-input multi-output, linear, and time-invariant systems. The state and output equations of the system, which are originally expressed in the t-domain, are first transformed into the s-domain. Then, input-output decoupling is achieved by generating the actual control variables as combinations of virtual control variables in such a way that each output is controlled by only the dedicated one of the virtual control variables. As the next stage, appropriate linear controllers are designed to generate the virtual control variables with feedback, feedforward, and disturbance rejection features. The design method is algebraic and involves the assignment of not only the closed-loop poles but also the type numbers associated with the reference and disturbance inputs. The multivariable transformation filter that converts the virtual control variables into actual ones is formed properly to prevent any possibility of internal instability.

The robust Morgan's problem, via restricted static state feedback and a constant precompensator, is studied for nonsquare linear time-invariant systems with nonlinear uncertain structure. Sufficient solvability conditions are established. A class of static controller matrices, independent from the uncertainties, to solve the problem is explicitly characterized. For this class of controllers, the resulting form of the robustly decoupled closed-loop system is analytically determined. Finally, sufficient conditions are established for the solvability of the robust Morgan's problem with simultaneous robust stability, via restricted state feedback. The present results are successfully applied to control a vertical takeoff and landing aircraft.