Model-Free Sliding Mode Control Method

Crassidis, Agamemnon L.; Reis, Raul Mittmann

doi:10.11159/cdsr16.100

Cited by 7 publications

(11 citation statements)

References 4 publications

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“…To be able to compute the control input, the gain matrix needs to be invertible. However, this is only satisfied when the # of inputs equals the # of outputs, in fully-actuated systems, in which case the application of the model-free sliding mode control becomes similar to that proposed by Crassdis and Reis in [7].…”

Section: Control Law For Siso and Square Mimo Systemsmentioning

confidence: 99%

“…Crassidis and Mizov [6 developed a model-free sliding mode controller which relies only on previous control inputs and state measurements to drive a system's states towards the desired trajectory. Crassidis and Reis [7] derived a similar controller to that introduced by Crassidis and Mizov in [6], but employed a different approach towards the formulation of the control input, while also requiring only previous control input and state measurements. The method was applied to linear and nonlinear single-input single-output (SISO) systems, with the presence of measurement noise.…”

Section: Introductionmentioning

confidence: 99%

“…The main contribution of this paper is to extend the work done by Crassidis and Reis in [7] into applications on MIMO systems, both fully-actuated and underactuated. The only characteristics of the system required to be known are the order of the system, shape of the input matrix, and an estimate of the control input gain bounds.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

A Model-Free Control System Based on the Sliding Mode Control Method with Applications to Multi-Input-Multi-Output Systems

Tin¹

2017

Proceedings of the 4th International Conference of Control, Dynamic Systems, and Robotics (CDSR'17)

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-In this paper, a model-free sliding mode control technique for linear and nonlinear uncertain multi-input multi-output (MIMO) systems is proposed. The developed method does not require a mathematical model of the dynamic system. Instead, the controller relies on state measurements and estimates of the error between previous and current control inputs to stabilize the system. Knowledge of the system's order, shape of the control input matrix, and control gain bounds, if non-unitary, are the only variables required to develop the controller. Lyapunov's stability criterion is used in the derivation process to ensure closed-loop asymptotic stability. High frequency chattering, often observed with the sliding mode control method, is eliminated using a smoothing boundary layer. Simulations are performed on a nonlinear two mass-spring-damper system and a quadrotor model to examine the performance of the proposed control law.

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Section: Control Law For Siso and Square Mimo Systemsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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A Model-Free Control System Based on the Sliding Mode Control Method with Applications to Multi-Input-Multi-Output Systems

Tin¹

2017

Proceedings of the 4th International Conference of Control, Dynamic Systems, and Robotics (CDSR'17)

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“…The control algorithm was independent of the system model and was only dependent on the system states, order of the system and previous control inputs. Reis and Crassidis extended this work to Single-Input-Single-Output (SISO) systems with unitary and non-unitary gains [5] assuming the bounds of control input gain matrix was known. Reis also suggested the tuning method of the control algorithm in the presence of noise and successfully implemented the algorithm on nonlinear and linear SISO systems.…”

Section: Introductionmentioning

confidence: 99%

“…The work developed in this paper is to successfully implement the MFSMC derived in [4], [5], [6], and [7] on a realtime quadcopter type Unmanned Aircraft System (UAS) and compare the tracking performance and power consumption to a traditional PID-type controller. Simulations characterising the quadcopter hardware is performed prior to targeting the realtime model.…”

Section: Introductionmentioning

confidence: 99%

A Model-Free Control Algorithm Based On The Sliding Mode Control Method With Applications to Unmanned Aircraft Systems

Sreeraj¹,

Kaputa²,

Crassidis³

2019

International Conference of Control, Dynamic Systems, and Robotics

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Control methods require the use of a system model for the design and tuning of the controllers in meeting and/or exceeding the control system performance objectives. However, system models contain errors and uncertainties that also may be complex to develop and to generalize for a large class of systems such as those for unmanned aircraft systems. In particular, the sliding control method is a superior robust nonlinear control approach due to the direct handling of nonlinearities and uncertainties that can be used in tracking problems for unmanned aircraft system. However, the derivation of the sliding mode control law is tedious since a unique and distinct control law needs to be derived for every individual system and cannot be applied to general systems that may encompass all classifications of unmanned aircraft systems. In this paper, a model-free control algorithm based on the sliding mode control method is developed and generalized for all classes of unmanned aircraft systems used in robust tracking control applications. The model-free control algorithm is derived with knowledge of the system's order, state measurements, and control input gain matrix shape and bounds and is not dependent on a mathematical system model. The derived control law is tested using a high-fidelity simulation of a quadrotortype unmanned aircraft system and the results are compared to a traditional PID controller for tracking performance and power consumption. Realistic type hardware inputs from joysticks and IMUs was simulated for the analysis. Finally, the model-free control algorithm was implemented on a quadrotor-type unmanned aircraft system testbed used in real flight experimental testing. The experimental tracking performance and power consumption was analysed and compared to a traditional PID-type controller.

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Complete model-free sliding mode control (CMFSMC)

Zhu

2021

Sci Rep

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This study presents a complete model-free sliding mode control (CMFSMC) framework for the control of continuous-time non-affine nonlinear dynamic systems with unknown models. The novelty lies in the introduction of two equalities to assign the derivative of the sliding functions, which generally bridges the designs of those model-based SMC and model-free SMC. The study includes a double SMC (DSMC) design, state observer design, and desired reference state vector design (whole system performance), which all do not require plant nominal models. The preconditions required in the CMFSMC are the plant dynamic order and the boundedness of plant and disturbances. U-model based control (U-control) is incorporated to configure the whole control system, that is (1) taking model-free double SMC as a robust dynamic inverter to cancel simultaneously both nonlinearity and dynamics of the underlying plants, (2) taking a model-free state observer to estimate the state vector, (3) taking invariant controller to specify the whole control system performance in a linear output feedback control and to provide desired reference state vector. The related properties are studied to support the concept/configuration development and the analytical formulations. Simulated case studies demonstrate the developed framework and show off the transparent design procedure for applications and expansions.

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Model-Free Sliding Mode Control Method

Cited by 7 publications

References 4 publications

A Model-Free Control System Based on the Sliding Mode Control Method with Applications to Multi-Input-Multi-Output Systems

A Model-Free Control System Based on the Sliding Mode Control Method with Applications to Multi-Input-Multi-Output Systems

A Model-Free Control Algorithm Based On The Sliding Mode Control Method With Applications to Unmanned Aircraft Systems

Complete model-free sliding mode control (CMFSMC)

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