Controller design for a class of nonlinear MIMO coupled system using multiple models and second level adaptation

A flexible mixed-optimization with H∞ control for coupled twin rotor MIMO system based on the method of inequality (MOI)- An experimental study

This article introduces a cutting-edge H∞ model-based control method for uncertain Multi Input Multi Output (MIMO) systems, specifically focusing on UAVs, through a flexible mixed-optimization framework using the Method of Inequality (MOI). The proposed approach adaptively addresses crucial challenges such as unmodeled dynamics, noise interference, and parameter variations. Central to the design is a two-step controller development process. The first step involves Nonlinear Dynamic Inversion (NDI) and system decoupling for simplification, while the second step integrates H∞ control with MOI for optimal response tuning. This strategy is distinguished by its adaptability and focus on balancing robust stability and performance, effectively managing the intricate cross-coupling dynamics in UAV systems. The effectiveness of the proposed approach is validated through simulations conducted in MATLAB/Simulink environment. Results demonstrated the efficiency of the proposed robust control approach as evidenced by reduced steady-state error, diminished overshoot, and faster system response times, thus significantly outperforming traditional control methods.

Switched step integral backstepping control for nonlinear motion systems with application to a laboratory helicopter

In this paper, the energy efficiency of the widespread application of backstepping control to a class of nonlinear motion systems is investigated. A Switched Step Integral Backstepping Control (SSIBC) scheme is introduced to improve immunity to measurement noise and to increase the energy efficiency of conventional backstepping in practice. The SSIBC is realized by switching between two candidate controllers obtained at different steps of the iterative backstepping design process. A bi-state dependent hysteresis rule is developed to supervise stable switching between the different regimes in the presence of noise. The proposed method is experimentally verified on a MIMO twin rotor laboratory helicopter involving coupled nonlinear dynamics, inaccessible states and uncertainties. Experimental results show that in addition to a reduction in power consumption, the SSIBC reduces saturation of the control signal and visible motor jerking in contrast with conventional backstepping. Additional comparisons with a previously proposed optimized decoupling PID controller also show significant improvement in precision achieved with higher energy efficiency. Experimental results obtained with the introduction of an external disturbance into the system also show the robustness of the proposed SSIBC.

Design of a multivariable stimulus for Emotional-Learning based control of a 2-DOF laboratory helicopter

Emotional-Learning based controllers are becoming increasingly popular due to their non-parametric and flexible design approach. However, most of the existing Emotional-Learning based control strategies are designed specifically for individual loops and are not suitable for superior performance in a strongly coupled MIMO system. In this technical note, a multi-variable Emotional-Learning based strategy for trajectory tracking in a strongly coupled MIMO system is proposed. This strategy incorporates an improved stimulus design that deals with tracking, regulation, disturbance-rejection and coupling effects in a systematic way. The strategy also addresses the deleterious effects of mechanical resonance associated with flexible structures from the perspective of stimulus design. The proposed strategy is validated through simulations and hardware based experiments on a 2-DOF laboratory helicopter. Effectiveness of the proposed strategy is illustrated through comparisons with an optimized multi-variable LQG controller.

Particle swarm-based and neuro-based FOPID controllers for a Twin Rotor System with improved tracking performance and energy reduction

This paper examines two approaches in tuning fractional order proportional-integral-differential (FOPID) control named as neuro-based FOPID (NNFOPID) and particle swarm-based FOPID (PSOFOPID) for pitch control of a Twin Rotor Aerodynamic System (TRAS). For the neuro-based FOPID control, the innovations are the modification of output equation in the artificial neural network and the implementation of the Rectified Linear Unit (ReLU) activation function. The advantages of the proposed approach are a lighter network and the ability to tune more practical controller parameters without a deep knowledge of the system to achieve a satisfying pitch tracking response. As for the particle swarm-based FOPID control, the application of PSO with spreading factor algorithm is extended for tuning the FOPID controller gains and the innovation here is a new procedure in setting the initial search range. The important advantages of this proposed swarm-based algorithm are the avoidance of being trapped in local optima and reduction of the search area respectively. The performances of the proposed controllers are proven by extensive simulations and experimental verifications based on five standard criteria: square-wave characteristics, reference to disturbance ratio, evaluation time, energy consumption of the control signal and tracking performance. The performances of the proposed controllers are compared against an optimised PID control in three system conditions, namely Case I) without coupling effect and wind disturbance, Case II) with coupling effect only and Case III) with wind disturbance only. Together, this study finds that NNFOPID control offers an accurate system positioning by a 34% reduction in steady-state error with the lowest energy consumption and minimum evaluation time in Case II. In terms of the tracking performance and robustness for Case II, the superiority of PSOFOPID control is confirmed by a 27% reduction in the tracking error and the lowest oscillation value. The experimental results also validate the robustness and energy consumption of both controllers in Case III. It is envisaged that the proposed control designs can be very useful in tuning FOPID controller gains for high performance, low energy, and robust aerodynamics systems.

Improved Active Disturbance Rejection-Based Decentralized Control for MIMO Nonlinear Systems: Comparison with The Decoupled Control Scheme

A decentralized control scheme is developed in this paper based on an improved active disturbance rejection control (IADRC) for output tracking of square Multi-Input-Multi-Output (MIMO) nonlinear systems and compared with the decoupled control scheme. These nonlinear MIMO systems were subjected to exogenous disturbances and composed of high couplings between subsystems, input couplings, and uncertain elements. In the decentralized control scheme, it was assumed that the input couplings and subsystem couplings were both parts of the generalized disturbance. Moreover, the generalized disturbance included other components, such as exogenous disturbances and system uncertainties, and it was estimated within the context of Active Disturbance rejection Control (ADRC) via a novel nonlinear higher order extended state observer (NHOESO) from the measured output and canceled from the input channel in a real-time fashion. Then, based on the designed NHOESO, a separate feedback control law was developed for each subsystem to achieve accurate output tracking for given reference input. With the proposed decentralized control scheme, the square MIMO nonlinear system was converted into approximately separate linear time invariant Single-Input-Single-Output (SISO) subsystems. Numerical simulations in a MATLAB environment showed the effectiveness of the proposed technique, where it was applied on a hypothetical MIMO nonlinear system with strong couplings and vast uncertainties. The proposed decentralized control scheme reduced the total control signal energy by 20.8% as compared to the decoupled control scheme using Conventional ADRC (CADRC), while the reduction was 27.18% using the IADRC.

Improved integral backstepping control of variable speed motion systems with application to a laboratory helicopter

This paper proposes an improved method of integral backstepping for real time control of a laboratory helicopter with variable speed rotors known as the Two-Rotor Aero-dynamic System (TRAS). The coupled system is decomposed into the horizontal subsystem (HS) and the vertical subsystem (VS) and traditional backstepping, augmented with direct integral action is designed for each subsystem. The transient response to both constant and time varying references is then simultaneously improved by modifying an already proposed method called dual boundary conditional integration. A switching technique is also employed to enhance the tracking response of the undamped HS for its bi-directional motor which exhibits jerking effects. Experimental results show that the proposed approach yields improved transient and tracking performance when compared to previously proposed methods exploiting conditional integration earlier proposed for improving the transient response of controlled nonlinear systems with integral action. The results also show the robustness of the proposed method in the presence of the coupling effects and additional external disturbance applied to the system in the form of a wind gust.