Multi-objective generalized predictive control for switching systems under unknown switching sequences.

This paper describes a new generalized predictive control to track and stabilize a class of discrete time switching system. The focus is specifically centered on classes of switching systems characterized by unstable modes, undetermined switching signal, anon-minimumphase, and variable dead-times. To overcome this type of issue, an effective predictive control law is established by solving a dynamic multi-objective optimization function. Control problems are formulated in order to stabilize and regulate the system response around the targeted reference. The theoretical background of the proposed method is inspired by the standard generalized predictive control (GPC), in such a way that all desirable features are retained as possible. As a result, the obtained controller is more efficient in terms of stability and tracking. In fact within the framework of this research, the control problem has been formulated by taking into account behaviors of subsystems as well as the switching phase. The optimization of the problem is established in such a way that the obtained control law will be adapted to system dynamics, regardless of the mode. A number of simulation tests are established to evaluate the performance of the developed method. Four benchmark examples were considered for the simulation tests. Simulation results have shown the potential of the developed strategy to control and stabilize switching systems under unknown switching sequences. For further evaluation, the closed-loop performance of the developed strategy has been compared to that obtained with the Multi-Criteria Predictive Control (MOMPC) method. Comparison results have highlighted the effectiveness of the proposed method in terms of stability and tracking than MOMPC method.

An adaptive sliding mode observer for inverted pendulum under mass variation and disturbances with experimental validation.

In this paper, a new robust adaptive estimation approach is designed for the inverted pendulum. The estimation scheme is composed by an auxiliary high gain observer in cascade with an adaptive sliding mode observer. The auxiliary high gain observer is designed to estimate auxiliary outputs in order to solve the dissatisfaction of observer matching condition related to the presence of disturbances. Then, using the estimated auxiliary outputs, the adaptive sliding mode observer is synthesized to estimate conjointly the states, the unknown parameter (the pendulum mass which appears nonlinearly in the dynamics of the pendulum model) and the unknown disturbances. The stability analysis is established using the Lyapunov approach. Numerical simulations are carried out to validate theoretical results. Furthermore, experimental tests are realized using a real pendulum setup (a product of Feedback Instruments) to highlight the good performances of the proposed estimation method in practice.

Experimental sensorless control for a coupled two-tank system using high gain adaptive observer and nonlinear generalized predictive strategy.

In this paper an adaptive control for a coupled two-tank system is proposed. This control strategy uses a generalized predictive controller, whose main method is to minimize a multistage cost function defined over a prediction horizon. Furthermore, to implement this controller in the framework of the sensorless control from the only measurement of the liquid level in the bottom tank, an adaptive interconnected high gain observer is developed for estimating the liquid level in the upper tank and the two constant parameters of the system. Two design features are worth to be emphasized. Firstly, the control calibration is achieved through the tuning of only two scalar design parameters. Secondly, the exponential convergence to zero of the state observation and parameter estimation errors is established under a well defined condition. Finally, the theoretical results are corroborated through simulation and experimental results which highlight the efficiency and applicability of the proposed observer-controller scheme.

Cuckoo Search Approach for Parameter Identification of an Activated Sludge Process.

A parameter identification problem for a hybrid model is presented. The latter describes the operation of an activated sludge process used for waste water treatment. Parameter identification problem can be considered as an optimization one by minimizing the error between simulation and experimental data. One of the new and promising metaheuristic methods for solving similar mathematical problem is Cuckoo Search Algorithm. It is inspired by the parasitic brood behavior of cuckoo species. To confirm the effectiveness and the efficiency of the proposed algorithm, simulation results will be compared with other algorithms, firstly, with a classical method which is the Nelder-Mead algorithm and, secondly, with intelligent methods such as Genetic Algorithm and Particle Swarm Optimization approaches.

Generalized predictive control for a coupled four tank MIMO system using a continuous-discrete time observer.

This paper deals with the problem of the observer based control design for a coupled four-tank liquid level system. For this MIMO system's dynamics, motivated by a desire to provide precise and sensorless liquid level control, a nonlinear predictive controller based on a continuous-discrete observer is presented. First, an analytical solution from the model predictive control (MPC) technique is developed for a particular class of nonlinear MIMO systems and its corresponding exponential stability is proven. Then, a high gain observer that runs in continuous-time with an output error correction time that is updated in a mixed continuous-discrete fashion is designed in order to estimate the liquid levels in the two upper tanks. The effectiveness of the designed control schemes are validated by two tests; The first one is maintaining a constant level in the first bottom tank while making the level in the second bottom tank to follow a sinusoidal reference signal. The second test is more difficult and it is made using two trapezoidal reference signals in order to see the decoupling performance of the system's outputs. Simulation and experimental results validate the objective of the paper.